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Sample records for annotation databases improves

  1. Estimating the annotation error rate of curated GO database sequence annotations

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    Brown Alfred L

    2007-05-01

    Full Text Available Abstract Background Annotations that describe the function of sequences are enormously important to researchers during laboratory investigations and when making computational inferences. However, there has been little investigation into the data quality of sequence function annotations. Here we have developed a new method of estimating the error rate of curated sequence annotations, and applied this to the Gene Ontology (GO sequence database (GOSeqLite. This method involved artificially adding errors to sequence annotations at known rates, and used regression to model the impact on the precision of annotations based on BLAST matched sequences. Results We estimated the error rate of curated GO sequence annotations in the GOSeqLite database (March 2006 at between 28% and 30%. Annotations made without use of sequence similarity based methods (non-ISS had an estimated error rate of between 13% and 18%. Annotations made with the use of sequence similarity methodology (ISS had an estimated error rate of 49%. Conclusion While the overall error rate is reasonably low, it would be prudent to treat all ISS annotations with caution. Electronic annotators that use ISS annotations as the basis of predictions are likely to have higher false prediction rates, and for this reason designers of these systems should consider avoiding ISS annotations where possible. Electronic annotators that use ISS annotations to make predictions should be viewed sceptically. We recommend that curators thoroughly review ISS annotations before accepting them as valid. Overall, users of curated sequence annotations from the GO database should feel assured that they are using a comparatively high quality source of information.

  2. A computational platform to maintain and migrate manual functional annotations for BioCyc databases.

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    Walsh, Jesse R; Sen, Taner Z; Dickerson, Julie A

    2014-10-12

    BioCyc databases are an important resource for information on biological pathways and genomic data. Such databases represent the accumulation of biological data, some of which has been manually curated from literature. An essential feature of these databases is the continuing data integration as new knowledge is discovered. As functional annotations are improved, scalable methods are needed for curators to manage annotations without detailed knowledge of the specific design of the BioCyc database. We have developed CycTools, a software tool which allows curators to maintain functional annotations in a model organism database. This tool builds on existing software to improve and simplify annotation data imports of user provided data into BioCyc databases. Additionally, CycTools automatically resolves synonyms and alternate identifiers contained within the database into the appropriate internal identifiers. Automating steps in the manual data entry process can improve curation efforts for major biological databases. The functionality of CycTools is demonstrated by transferring GO term annotations from MaizeCyc to matching proteins in CornCyc, both maize metabolic pathway databases available at MaizeGDB, and by creating strain specific databases for metabolic engineering.

  3. Improving Microbial Genome Annotations in an Integrated Database Context

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    Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; Anderson, Iain; Mavromatis, Konstantinos; Kyrpides, Nikos C.; Ivanova, Natalia N.

    2013-01-01

    Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/. PMID:23424620

  4. Improving microbial genome annotations in an integrated database context.

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    I-Min A Chen

    Full Text Available Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/.

  5. PCAS – a precomputed proteome annotation database resource

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    Luo Jingchu

    2003-11-01

    Full Text Available Abstract Background Many model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification of proteins. Employing most available computational algorithms, mainly motif or domain recognition algorithms, we set up to develop an online proteome annotation system with integrated proteome annotation data to complement existing resources. Results We report here the development of PCAS (ProteinCentric Annotation System as an online resource of pre-computed proteome annotation data. We applied most available motif or domain databases and their analysis methods, including hmmpfam search of HMMs in Pfam, SMART and TIGRFAM, RPS-PSIBLAST search of PSSMs in CDD, pfscan of PROSITE patterns and profiles, as well as PSI-BLAST search of SUPERFAMILY PSSMs. In addition, signal peptide and TM are predicted using SignalP and TMHMM respectively. We mapped SUPERFAMILY and COGs to InterPro, so the motif or domain databases are integrated through InterPro. PCAS displays table summaries of pre-computed data and a graphical presentation of motifs or domains relative to the protein. As of now, PCAS contains human IPI, mouse IPI, and rat IPI, A. thaliana, C. elegans, D. melanogaster, S. cerevisiae, and S. pombe proteome. PCAS is available at http://pak.cbi.pku.edu.cn/proteome/gca.php Conclusion PCAS gives better annotation coverage for model proteomes by employing a wider collection of available algorithms. Besides presenting the most confident annotation data, PCAS also allows customized query so users can inspect statistically less significant boundary information as well. Therefore, besides providing general annotation information, PCAS could be used as a discovery platform. We plan to update PCAS twice a year. We will upgrade PCAS when new proteome annotation algorithms

  6. Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database.

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    Winsor, Geoffrey L; Griffiths, Emma J; Lo, Raymond; Dhillon, Bhavjinder K; Shay, Julie A; Brinkman, Fiona S L

    2016-01-04

    The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. Designing a Lexical Database for a Combined Use of Corpus Annotation and Dictionary Editing

    DEFF Research Database (Denmark)

    Kristoffersen, Jette Hedegaard; Troelsgård, Thomas; Langer, Gabriele

    2016-01-01

    In a combined corpus-dictionary project, you would need one lexical database that could serve as a shared “backbone” for both corpus annotation and dictionary editing, but it is not that easy to define a database structure that applies satisfactorily to both these purposes. In this paper, we...... will exemplify the problem and present ideas on how to model structures in a lexical database that facilitate corpus annotation as well as dictionary editing. The paper is a joint work between the DGS Corpus Project and the DTS Dictionary Project. The two projects come from opposite sides of the spectrum (one...... adjusting a lexical database grown from dictionary making for corpus annotating, one building a lexical database in parallel with corpus annotation and editing a corpus-based dictionary), and we will consider requirements and feasible structures for a database that can serve both corpus and dictionary....

  8. H2DB: a heritability database across multiple species by annotating trait-associated genomic loci.

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    Kaminuma, Eli; Fujisawa, Takatomo; Tanizawa, Yasuhiro; Sakamoto, Naoko; Kurata, Nori; Shimizu, Tokurou; Nakamura, Yasukazu

    2013-01-01

    H2DB (http://tga.nig.ac.jp/h2db/), an annotation database of genetic heritability estimates for humans and other species, has been developed as a knowledge database to connect trait-associated genomic loci. Heritability estimates have been investigated for individual species, particularly in human twin studies and plant/animal breeding studies. However, there appears to be no comprehensive heritability database for both humans and other species. Here, we introduce an annotation database for genetic heritabilities of various species that was annotated by manually curating online public resources in PUBMED abstracts and journal contents. The proposed heritability database contains attribute information for trait descriptions, experimental conditions, trait-associated genomic loci and broad- and narrow-sense heritability specifications. Annotated trait-associated genomic loci, for which most are single-nucleotide polymorphisms derived from genome-wide association studies, may be valuable resources for experimental scientists. In addition, we assigned phenotype ontologies to the annotated traits for the purposes of discussing heritability distributions based on phenotypic classifications.

  9. Assessment of community-submitted ontology annotations from a novel database-journal partnership.

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    Berardini, Tanya Z; Li, Donghui; Muller, Robert; Chetty, Raymond; Ploetz, Larry; Singh, Shanker; Wensel, April; Huala, Eva

    2012-01-01

    As the scientific literature grows, leading to an increasing volume of published experimental data, so does the need to access and analyze this data using computational tools. The most commonly used method to convert published experimental data on gene function into controlled vocabulary annotations relies on a professional curator, employed by a model organism database or a more general resource such as UniProt, to read published articles and compose annotation statements based on the articles' contents. A more cost-effective and scalable approach capable of capturing gene function data across the whole range of biological research organisms in computable form is urgently needed. We have analyzed a set of ontology annotations generated through collaborations between the Arabidopsis Information Resource and several plant science journals. Analysis of the submissions entered using the online submission tool shows that most community annotations were well supported and the ontology terms chosen were at an appropriate level of specificity. Of the 503 individual annotations that were submitted, 97% were approved and community submissions captured 72% of all possible annotations. This new method for capturing experimental results in a computable form provides a cost-effective way to greatly increase the available body of annotations without sacrificing annotation quality. Database URL: www.arabidopsis.org.

  10. Expanded microbial genome coverage and improved protein family annotation in the COG database.

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    Galperin, Michael Y; Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V

    2015-01-01

    Microbial genome sequencing projects produce numerous sequences of deduced proteins, only a small fraction of which have been or will ever be studied experimentally. This leaves sequence analysis as the only feasible way to annotate these proteins and assign to them tentative functions. The Clusters of Orthologous Groups of proteins (COGs) database (http://www.ncbi.nlm.nih.gov/COG/), first created in 1997, has been a popular tool for functional annotation. Its success was largely based on (i) its reliance on complete microbial genomes, which allowed reliable assignment of orthologs and paralogs for most genes; (ii) orthology-based approach, which used the function(s) of the characterized member(s) of the protein family (COG) to assign function(s) to the entire set of carefully identified orthologs and describe the range of potential functions when there were more than one; and (iii) careful manual curation of the annotation of the COGs, aimed at detailed prediction of the biological function(s) for each COG while avoiding annotation errors and overprediction. Here we present an update of the COGs, the first since 2003, and a comprehensive revision of the COG annotations and expansion of the genome coverage to include representative complete genomes from all bacterial and archaeal lineages down to the genus level. This re-analysis of the COGs shows that the original COG assignments had an error rate below 0.5% and allows an assessment of the progress in functional genomics in the past 12 years. During this time, functions of many previously uncharacterized COGs have been elucidated and tentative functional assignments of many COGs have been validated, either by targeted experiments or through the use of high-throughput methods. A particularly important development is the assignment of functions to several widespread, conserved proteins many of which turned out to participate in translation, in particular rRNA maturation and tRNA modification. The new version of the

  11. Discovering gene annotations in biomedical text databases

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    Ozsoyoglu Gultekin

    2008-03-01

    Full Text Available Abstract Background Genes and gene products are frequently annotated with Gene Ontology concepts based on the evidence provided in genomics articles. Manually locating and curating information about a genomic entity from the biomedical literature requires vast amounts of human effort. Hence, there is clearly a need forautomated computational tools to annotate the genes and gene products with Gene Ontology concepts by computationally capturing the related knowledge embedded in textual data. Results In this article, we present an automated genomic entity annotation system, GEANN, which extracts information about the characteristics of genes and gene products in article abstracts from PubMed, and translates the discoveredknowledge into Gene Ontology (GO concepts, a widely-used standardized vocabulary of genomic traits. GEANN utilizes textual "extraction patterns", and a semantic matching framework to locate phrases matching to a pattern and produce Gene Ontology annotations for genes and gene products. In our experiments, GEANN has reached to the precision level of 78% at therecall level of 61%. On a select set of Gene Ontology concepts, GEANN either outperforms or is comparable to two other automated annotation studies. Use of WordNet for semantic pattern matching improves the precision and recall by 24% and 15%, respectively, and the improvement due to semantic pattern matching becomes more apparent as the Gene Ontology terms become more general. Conclusion GEANN is useful for two distinct purposes: (i automating the annotation of genomic entities with Gene Ontology concepts, and (ii providing existing annotations with additional "evidence articles" from the literature. The use of textual extraction patterns that are constructed based on the existing annotations achieve high precision. The semantic pattern matching framework provides a more flexible pattern matching scheme with respect to "exactmatching" with the advantage of locating approximate

  12. CAGE_peaks_annotation - FANTOM5 | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data List Contact us FANTOM...file File name: CAGE_peaks_annotation File URL: ftp://ftp.biosciencedbc.jp/archive/fantom...on Download License Update History of This Database Site Policy | Contact Us CAGE_peaks_annotation - FANTOM5 | LSDB Archive ...

  13. Evaluation of relational and NoSQL database architectures to manage genomic annotations.

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    Schulz, Wade L; Nelson, Brent G; Felker, Donn K; Durant, Thomas J S; Torres, Richard

    2016-12-01

    While the adoption of next generation sequencing has rapidly expanded, the informatics infrastructure used to manage the data generated by this technology has not kept pace. Historically, relational databases have provided much of the framework for data storage and retrieval. Newer technologies based on NoSQL architectures may provide significant advantages in storage and query efficiency, thereby reducing the cost of data management. But their relative advantage when applied to biomedical data sets, such as genetic data, has not been characterized. To this end, we compared the storage, indexing, and query efficiency of a common relational database (MySQL), a document-oriented NoSQL database (MongoDB), and a relational database with NoSQL support (PostgreSQL). When used to store genomic annotations from the dbSNP database, we found the NoSQL architectures to outperform traditional, relational models for speed of data storage, indexing, and query retrieval in nearly every operation. These findings strongly support the use of novel database technologies to improve the efficiency of data management within the biological sciences. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Artemis and ACT: viewing, annotating and comparing sequences stored in a relational database.

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    Carver, Tim; Berriman, Matthew; Tivey, Adrian; Patel, Chinmay; Böhme, Ulrike; Barrell, Barclay G; Parkhill, Julian; Rajandream, Marie-Adèle

    2008-12-01

    Artemis and Artemis Comparison Tool (ACT) have become mainstream tools for viewing and annotating sequence data, particularly for microbial genomes. Since its first release, Artemis has been continuously developed and supported with additional functionality for editing and analysing sequences based on feedback from an active user community of laboratory biologists and professional annotators. Nevertheless, its utility has been somewhat restricted by its limitation to reading and writing from flat files. Therefore, a new version of Artemis has been developed, which reads from and writes to a relational database schema, and allows users to annotate more complex, often large and fragmented, genome sequences. Artemis and ACT have now been extended to read and write directly to the Generic Model Organism Database (GMOD, http://www.gmod.org) Chado relational database schema. In addition, a Gene Builder tool has been developed to provide structured forms and tables to edit coordinates of gene models and edit functional annotation, based on standard ontologies, controlled vocabularies and free text. Artemis and ACT are freely available (under a GPL licence) for download (for MacOSX, UNIX and Windows) at the Wellcome Trust Sanger Institute web sites: http://www.sanger.ac.uk/Software/Artemis/ http://www.sanger.ac.uk/Software/ACT/

  15. Artemis and ACT: viewing, annotating and comparing sequences stored in a relational database

    Science.gov (United States)

    Carver, Tim; Berriman, Matthew; Tivey, Adrian; Patel, Chinmay; Böhme, Ulrike; Barrell, Barclay G.; Parkhill, Julian; Rajandream, Marie-Adèle

    2008-01-01

    Motivation: Artemis and Artemis Comparison Tool (ACT) have become mainstream tools for viewing and annotating sequence data, particularly for microbial genomes. Since its first release, Artemis has been continuously developed and supported with additional functionality for editing and analysing sequences based on feedback from an active user community of laboratory biologists and professional annotators. Nevertheless, its utility has been somewhat restricted by its limitation to reading and writing from flat files. Therefore, a new version of Artemis has been developed, which reads from and writes to a relational database schema, and allows users to annotate more complex, often large and fragmented, genome sequences. Results: Artemis and ACT have now been extended to read and write directly to the Generic Model Organism Database (GMOD, http://www.gmod.org) Chado relational database schema. In addition, a Gene Builder tool has been developed to provide structured forms and tables to edit coordinates of gene models and edit functional annotation, based on standard ontologies, controlled vocabularies and free text. Availability: Artemis and ACT are freely available (under a GPL licence) for download (for MacOSX, UNIX and Windows) at the Wellcome Trust Sanger Institute web sites: http://www.sanger.ac.uk/Software/Artemis/ http://www.sanger.ac.uk/Software/ACT/ Contact: artemis@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:18845581

  16. CSE database: extended annotations and new recommendations for ECG software testing.

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    Smíšek, Radovan; Maršánová, Lucie; Němcová, Andrea; Vítek, Martin; Kozumplík, Jiří; Nováková, Marie

    2017-08-01

    Nowadays, cardiovascular diseases represent the most common cause of death in western countries. Among various examination techniques, electrocardiography (ECG) is still a highly valuable tool used for the diagnosis of many cardiovascular disorders. In order to diagnose a person based on ECG, cardiologists can use automatic diagnostic algorithms. Research in this area is still necessary. In order to compare various algorithms correctly, it is necessary to test them on standard annotated databases, such as the Common Standards for Quantitative Electrocardiography (CSE) database. According to Scopus, the CSE database is the second most cited standard database. There were two main objectives in this work. First, new diagnoses were added to the CSE database, which extended its original annotations. Second, new recommendations for diagnostic software quality estimation were established. The ECG recordings were diagnosed by five new cardiologists independently, and in total, 59 different diagnoses were found. Such a large number of diagnoses is unique, even in terms of standard databases. Based on the cardiologists' diagnoses, a four-round consensus (4R consensus) was established. Such a 4R consensus means a correct final diagnosis, which should ideally be the output of any tested classification software. The accuracy of the cardiologists' diagnoses compared with the 4R consensus was the basis for the establishment of accuracy recommendations. The accuracy was determined in terms of sensitivity = 79.20-86.81%, positive predictive value = 79.10-87.11%, and the Jaccard coefficient = 72.21-81.14%, respectively. Within these ranges, the accuracy of the software is comparable with the accuracy of cardiologists. The accuracy quantification of the correct classification is unique. Diagnostic software developers can objectively evaluate the success of their algorithm and promote its further development. The annotations and recommendations proposed in this work will allow

  17. Towards Viral Genome Annotation Standards, Report from the 2010 NCBI Annotation Workshop.

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    Brister, James Rodney; Bao, Yiming; Kuiken, Carla; Lefkowitz, Elliot J; Le Mercier, Philippe; Leplae, Raphael; Madupu, Ramana; Scheuermann, Richard H; Schobel, Seth; Seto, Donald; Shrivastava, Susmita; Sterk, Peter; Zeng, Qiandong; Klimke, William; Tatusova, Tatiana

    2010-10-01

    Improvements in DNA sequencing technologies portend a new era in virology and could possibly lead to a giant leap in our understanding of viral evolution and ecology. Yet, as viral genome sequences begin to fill the world's biological databases, it is critically important to recognize that the scientific promise of this era is dependent on consistent and comprehensive genome annotation. With this in mind, the NCBI Genome Annotation Workshop recently hosted a study group tasked with developing sequence, function, and metadata annotation standards for viral genomes. This report describes the issues involved in viral genome annotation and reviews policy recommendations presented at the NCBI Annotation Workshop.

  18. Towards Viral Genome Annotation Standards, Report from the 2010 NCBI Annotation Workshop

    Directory of Open Access Journals (Sweden)

    Qiandong Zeng

    2010-10-01

    Full Text Available Improvements in DNA sequencing technologies portend a new era in virology and could possibly lead to a giant leap in our understanding of viral evolution and ecology. Yet, as viral genome sequences begin to fill the world’s biological databases, it is critically important to recognize that the scientific promise of this era is dependent on consistent and comprehensive genome annotation. With this in mind, the NCBI Genome Annotation Workshop recently hosted a study group tasked with developing sequence, function, and metadata annotation standards for viral genomes. This report describes the issues involved in viral genome annotation and reviews policy recommendations presented at the NCBI Annotation Workshop.

  19. The Co-regulation Data Harvester: Automating gene annotation starting from a transcriptome database

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    Tsypin, Lev M.; Turkewitz, Aaron P.

    Identifying co-regulated genes provides a useful approach for defining pathway-specific machinery in an organism. To be efficient, this approach relies on thorough genome annotation, a process much slower than genome sequencing per se. Tetrahymena thermophila, a unicellular eukaryote, has been a useful model organism and has a fully sequenced but sparsely annotated genome. One important resource for studying this organism has been an online transcriptomic database. We have developed an automated approach to gene annotation in the context of transcriptome data in T. thermophila, called the Co-regulation Data Harvester (CDH). Beginning with a gene of interest, the CDH identifies co-regulated genes by accessing the Tetrahymena transcriptome database. It then identifies their closely related genes (orthologs) in other organisms by using reciprocal BLAST searches. Finally, it collates the annotations of those orthologs' functions, which provides the user with information to help predict the cellular role of the initial query. The CDH, which is freely available, represents a powerful new tool for analyzing cell biological pathways in Tetrahymena. Moreover, to the extent that genes and pathways are conserved between organisms, the inferences obtained via the CDH should be relevant, and can be explored, in many other systems.

  20. (reprocessed)CAGE_peaks_annotation - FANTOM5 | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data List Contact us FANTOM...: ftp://ftp.biosciencedbc.jp/archive/fantom5/datafiles/reprocessed/hg38_latest/extra/CAGE_peaks_annotation/ ...e URL: ftp://ftp.biosciencedbc.jp/archive/fantom5/datafiles/reprocessed/mm10_latest/extra/CAGE_peaks_annotat...te History of This Database Site Policy | Contact Us (reprocessed)CAGE_peaks_annotation - FANTOM5 | LSDB Archive ...

  1. DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis

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    Baseler Michael W

    2007-11-01

    Full Text Available Abstract Background Due to the complex and distributed nature of biological research, our current biological knowledge is spread over many redundant annotation databases maintained by many independent groups. Analysts usually need to visit many of these bioinformatics databases in order to integrate comprehensive annotation information for their genes, which becomes one of the bottlenecks, particularly for the analytic task associated with a large gene list. Thus, a highly centralized and ready-to-use gene-annotation knowledgebase is in demand for high throughput gene functional analysis. Description The DAVID Knowledgebase is built around the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of gene/protein identifiers from a variety of public genomic resources into DAVID gene clusters. The grouping of such identifiers improves the cross-reference capability, particularly across NCBI and UniProt systems, enabling more than 40 publicly available functional annotation sources to be comprehensively integrated and centralized by the DAVID gene clusters. The simple, pair-wise, text format files which make up the DAVID Knowledgebase are freely downloadable for various data analysis uses. In addition, a well organized web interface allows users to query different types of heterogeneous annotations in a high-throughput manner. Conclusion The DAVID Knowledgebase is designed to facilitate high throughput gene functional analysis. For a given gene list, it not only provides the quick accessibility to a wide range of heterogeneous annotation data in a centralized location, but also enriches the level of biological information for an individual gene. Moreover, the entire DAVID Knowledgebase is freely downloadable or searchable at http://david.abcc.ncifcrf.gov/knowledgebase/.

  2. Annotation error in public databases: misannotation of molecular function in enzyme superfamilies.

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    Alexandra M Schnoes

    2009-12-01

    Full Text Available Due to the rapid release of new data from genome sequencing projects, the majority of protein sequences in public databases have not been experimentally characterized; rather, sequences are annotated using computational analysis. The level of misannotation and the types of misannotation in large public databases are currently unknown and have not been analyzed in depth. We have investigated the misannotation levels for molecular function in four public protein sequence databases (UniProtKB/Swiss-Prot, GenBank NR, UniProtKB/TrEMBL, and KEGG for a model set of 37 enzyme families for which extensive experimental information is available. The manually curated database Swiss-Prot shows the lowest annotation error levels (close to 0% for most families; the two other protein sequence databases (GenBank NR and TrEMBL and the protein sequences in the KEGG pathways database exhibit similar and surprisingly high levels of misannotation that average 5%-63% across the six superfamilies studied. For 10 of the 37 families examined, the level of misannotation in one or more of these databases is >80%. Examination of the NR database over time shows that misannotation has increased from 1993 to 2005. The types of misannotation that were found fall into several categories, most associated with "overprediction" of molecular function. These results suggest that misannotation in enzyme superfamilies containing multiple families that catalyze different reactions is a larger problem than has been recognized. Strategies are suggested for addressing some of the systematic problems contributing to these high levels of misannotation.

  3. Annotation error in public databases: misannotation of molecular function in enzyme superfamilies.

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    Schnoes, Alexandra M; Brown, Shoshana D; Dodevski, Igor; Babbitt, Patricia C

    2009-12-01

    Due to the rapid release of new data from genome sequencing projects, the majority of protein sequences in public databases have not been experimentally characterized; rather, sequences are annotated using computational analysis. The level of misannotation and the types of misannotation in large public databases are currently unknown and have not been analyzed in depth. We have investigated the misannotation levels for molecular function in four public protein sequence databases (UniProtKB/Swiss-Prot, GenBank NR, UniProtKB/TrEMBL, and KEGG) for a model set of 37 enzyme families for which extensive experimental information is available. The manually curated database Swiss-Prot shows the lowest annotation error levels (close to 0% for most families); the two other protein sequence databases (GenBank NR and TrEMBL) and the protein sequences in the KEGG pathways database exhibit similar and surprisingly high levels of misannotation that average 5%-63% across the six superfamilies studied. For 10 of the 37 families examined, the level of misannotation in one or more of these databases is >80%. Examination of the NR database over time shows that misannotation has increased from 1993 to 2005. The types of misannotation that were found fall into several categories, most associated with "overprediction" of molecular function. These results suggest that misannotation in enzyme superfamilies containing multiple families that catalyze different reactions is a larger problem than has been recognized. Strategies are suggested for addressing some of the systematic problems contributing to these high levels of misannotation.

  4. annot8r: GO, EC and KEGG annotation of EST datasets

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    Schmid Ralf

    2008-04-01

    Full Text Available Abstract Background The expressed sequence tag (EST methodology is an attractive option for the generation of sequence data for species for which no completely sequenced genome is available. The annotation and comparative analysis of such datasets poses a formidable challenge for research groups that do not have the bioinformatics infrastructure of major genome sequencing centres. Therefore, there is a need for user-friendly tools to facilitate the annotation of non-model species EST datasets with well-defined ontologies that enable meaningful cross-species comparisons. To address this, we have developed annot8r, a platform for the rapid annotation of EST datasets with GO-terms, EC-numbers and KEGG-pathways. Results annot8r automatically downloads all files relevant for the annotation process and generates a reference database that stores UniProt entries, their associated Gene Ontology (GO, Enzyme Commission (EC and Kyoto Encyclopaedia of Genes and Genomes (KEGG annotation and additional relevant data. For each of GO, EC and KEGG, annot8r extracts a specific sequence subset from the UniProt dataset based on the information stored in the reference database. These three subsets are then formatted for BLAST searches. The user provides the protein or nucleotide sequences to be annotated and annot8r runs BLAST searches against these three subsets. The BLAST results are parsed and the corresponding annotations retrieved from the reference database. The annotations are saved both as flat files and also in a relational postgreSQL results database to facilitate more advanced searches within the results. annot8r is integrated with the PartiGene suite of EST analysis tools. Conclusion annot8r is a tool that assigns GO, EC and KEGG annotations for data sets resulting from EST sequencing projects both rapidly and efficiently. The benefits of an underlying relational database, flexibility and the ease of use of the program make it ideally suited for non

  5. Methods for eliciting, annotating, and analyzing databases for child speech development.

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    Beckman, Mary E; Plummer, Andrew R; Munson, Benjamin; Reidy, Patrick F

    2017-09-01

    Methods from automatic speech recognition (ASR), such as segmentation and forced alignment, have facilitated the rapid annotation and analysis of very large adult speech databases and databases of caregiver-infant interaction, enabling advances in speech science that were unimaginable just a few decades ago. This paper centers on two main problems that must be addressed in order to have analogous resources for developing and exploiting databases of young children's speech. The first problem is to understand and appreciate the differences between adult and child speech that cause ASR models developed for adult speech to fail when applied to child speech. These differences include the fact that children's vocal tracts are smaller than those of adult males and also changing rapidly in size and shape over the course of development, leading to between-talker variability across age groups that dwarfs the between-talker differences between adult men and women. Moreover, children do not achieve fully adult-like speech motor control until they are young adults, and their vocabularies and phonological proficiency are developing as well, leading to considerably more within-talker variability as well as more between-talker variability. The second problem then is to determine what annotation schemas and analysis techniques can most usefully capture relevant aspects of this variability. Indeed, standard acoustic characterizations applied to child speech reveal that adult-centered annotation schemas fail to capture phenomena such as the emergence of covert contrasts in children's developing phonological systems, while also revealing children's nonuniform progression toward community speech norms as they acquire the phonological systems of their native languages. Both problems point to the need for more basic research into the growth and development of the articulatory system (as well as of the lexicon and phonological system) that is oriented explicitly toward the construction of

  6. PedAM: a database for Pediatric Disease Annotation and Medicine.

    Science.gov (United States)

    Jia, Jinmeng; An, Zhongxin; Ming, Yue; Guo, Yongli; Li, Wei; Li, Xin; Liang, Yunxiang; Guo, Dongming; Tai, Jun; Chen, Geng; Jin, Yaqiong; Liu, Zhimei; Ni, Xin; Shi, Tieliu

    2018-01-04

    There is a significant number of children around the world suffering from the consequence of the misdiagnosis and ineffective treatment for various diseases. To facilitate the precision medicine in pediatrics, a database namely the Pediatric Disease Annotations & Medicines (PedAM) has been built to standardize and classify pediatric diseases. The PedAM integrates both biomedical resources and clinical data from Electronic Medical Records to support the development of computational tools, by which enables robust data analysis and integration. It also uses disease-manifestation (D-M) integrated from existing biomedical ontologies as prior knowledge to automatically recognize text-mined, D-M-specific syntactic patterns from 774 514 full-text articles and 8 848 796 abstracts in MEDLINE. Additionally, disease connections based on phenotypes or genes can be visualized on the web page of PedAM. Currently, the PedAM contains standardized 8528 pediatric disease terms (4542 unique disease concepts and 3986 synonyms) with eight annotation fields for each disease, including definition synonyms, gene, symptom, cross-reference (Xref), human phenotypes and its corresponding phenotypes in the mouse. The database PedAM is freely accessible at http://www.unimd.org/pedam/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. Automated testing of arrhythmia monitors using annotated databases.

    Science.gov (United States)

    Elghazzawi, Z; Murray, W; Porter, M; Ezekiel, E; Goodall, M; Staats, S; Geheb, F

    1992-01-01

    Arrhythmia-algorithm performance is typically tested using the AHA and MIT/BIH databases. The tools for this test are simulation software programs. While these simulations provide rapid results, they neglect hardware and software effects in the monitor. To provide a more accurate measure of performance in the actual monitor, a system has been developed for automated arrhythmia testing. The testing system incorporates an IBM-compatible personal computer, a digital-to-analog converter, an RS232 board, a patient-simulator interface to the monitor, and a multi-tasking software package for data conversion and communication with the monitor. This system "plays" patient data files into the monitor and saves beat classifications in detection files. Tests were performed using the MIT/BIH and AHA databases. Statistics were generated by comparing the detection files with the annotation files. These statistics were marginally different from those that resulted from the simulation. Differences were then examined. As expected, the differences were related to monitor hardware effects.

  8. MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects.

    Science.gov (United States)

    Holt, Carson; Yandell, Mark

    2011-12-22

    Second-generation sequencing technologies are precipitating major shifts with regards to what kinds of genomes are being sequenced and how they are annotated. While the first generation of genome projects focused on well-studied model organisms, many of today's projects involve exotic organisms whose genomes are largely terra incognita. This complicates their annotation, because unlike first-generation projects, there are no pre-existing 'gold-standard' gene-models with which to train gene-finders. Improvements in genome assembly and the wide availability of mRNA-seq data are also creating opportunities to update and re-annotate previously published genome annotations. Today's genome projects are thus in need of new genome annotation tools that can meet the challenges and opportunities presented by second-generation sequencing technologies. We present MAKER2, a genome annotation and data management tool designed for second-generation genome projects. MAKER2 is a multi-threaded, parallelized application that can process second-generation datasets of virtually any size. We show that MAKER2 can produce accurate annotations for novel genomes where training-data are limited, of low quality or even non-existent. MAKER2 also provides an easy means to use mRNA-seq data to improve annotation quality; and it can use these data to update legacy annotations, significantly improving their quality. We also show that MAKER2 can evaluate the quality of genome annotations, and identify and prioritize problematic annotations for manual review. MAKER2 is the first annotation engine specifically designed for second-generation genome projects. MAKER2 scales to datasets of any size, requires little in the way of training data, and can use mRNA-seq data to improve annotation quality. It can also update and manage legacy genome annotation datasets.

  9. Structuring osteosarcoma knowledge: an osteosarcoma-gene association database based on literature mining and manual annotation.

    Science.gov (United States)

    Poos, Kathrin; Smida, Jan; Nathrath, Michaela; Maugg, Doris; Baumhoer, Daniel; Neumann, Anna; Korsching, Eberhard

    2014-01-01

    Osteosarcoma (OS) is the most common primary bone cancer exhibiting high genomic instability. This genomic instability affects multiple genes and microRNAs to a varying extent depending on patient and tumor subtype. Massive research is ongoing to identify genes including their gene products and microRNAs that correlate with disease progression and might be used as biomarkers for OS. However, the genomic complexity hampers the identification of reliable biomarkers. Up to now, clinico-pathological factors are the key determinants to guide prognosis and therapeutic treatments. Each day, new studies about OS are published and complicate the acquisition of information to support biomarker discovery and therapeutic improvements. Thus, it is necessary to provide a structured and annotated view on the current OS knowledge that is quick and easily accessible to researchers of the field. Therefore, we developed a publicly available database and Web interface that serves as resource for OS-associated genes and microRNAs. Genes and microRNAs were collected using an automated dictionary-based gene recognition procedure followed by manual review and annotation by experts of the field. In total, 911 genes and 81 microRNAs related to 1331 PubMed abstracts were collected (last update: 29 October 2013). Users can evaluate genes and microRNAs according to their potential prognostic and therapeutic impact, the experimental procedures, the sample types, the biological contexts and microRNA target gene interactions. Additionally, a pathway enrichment analysis of the collected genes highlights different aspects of OS progression. OS requires pathways commonly deregulated in cancer but also features OS-specific alterations like deregulated osteoclast differentiation. To our knowledge, this is the first effort of an OS database containing manual reviewed and annotated up-to-date OS knowledge. It might be a useful resource especially for the bone tumor research community, as specific

  10. Annotated checklist and database for vascular plants of the Jemez Mountains

    Energy Technology Data Exchange (ETDEWEB)

    Foxx, T. S.; Pierce, L.; Tierney, G. D.; Hansen, L. A.

    1998-03-01

    Studies done in the last 40 years have provided information to construct a checklist of the Jemez Mountains. The present database and checklist builds on the basic list compiled by Teralene Foxx and Gail Tierney in the early 1980s. The checklist is annotated with taxonomic information, geographic and biological information, economic uses, wildlife cover, revegetation potential, and ethnographic uses. There are nearly 1000 species that have been noted for the Jemez Mountains. This list is cross-referenced with the US Department of Agriculture Natural Resource Conservation Service PLANTS database species names and acronyms. All information will soon be available on a Web Page.

  11. Correction of the Caulobacter crescentus NA1000 genome annotation.

    Directory of Open Access Journals (Sweden)

    Bert Ely

    Full Text Available Bacterial genome annotations are accumulating rapidly in the GenBank database and the use of automated annotation technologies to create these annotations has become the norm. However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 non-coding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. These results demonstrate that a comparison of the location of peaks third codon position GC content to the location of protein coding regions could be used to verify the annotation of any genome that has a GC content that is greater than 60%.

  12. ACID: annotation of cassette and integron data

    Directory of Open Access Journals (Sweden)

    Stokes Harold W

    2009-04-01

    Full Text Available Abstract Background Although integrons and their associated gene cassettes are present in ~10% of bacteria and can represent up to 3% of the genome in which they are found, very few have been properly identified and annotated in public databases. These genetic elements have been overlooked in comparison to other vectors that facilitate lateral gene transfer between microorganisms. Description By automating the identification of integron integrase genes and of the non-coding cassette-associated attC recombination sites, we were able to assemble a database containing all publicly available sequence information regarding these genetic elements. Specialists manually curated the database and this information was used to improve the automated detection and annotation of integrons and their encoded gene cassettes. ACID (annotation of cassette and integron data can be searched using a range of queries and the data can be downloaded in a number of formats. Users can readily annotate their own data and integrate it into ACID using the tools provided. Conclusion ACID is a community resource providing easy access to annotations of integrons and making tools available to detect them in novel sequence data. ACID also hosts a forum to prompt integron-related discussion, which can hopefully lead to a more universal definition of this genetic element.

  13. Xylella fastidiosa comparative genomic database is an information resource to explore the annotation, genomic features, and biology of different strains

    Directory of Open Access Journals (Sweden)

    Alessandro M. Varani

    2012-01-01

    Full Text Available The Xylella fastidiosa comparative genomic database is a scientific resource with the aim to provide a user-friendly interface for accessing high-quality manually curated genomic annotation and comparative sequence analysis, as well as for identifying and mapping prophage-like elements, a marked feature of Xylella genomes. Here we describe a database and tools for exploring the biology of this important plant pathogen. The hallmarks of this database are the high quality genomic annotation, the functional and comparative genomic analysis and the identification and mapping of prophage-like elements. It is available from web site http://www.xylella.lncc.br.

  14. Amino acid sequences of predicted proteins and their annotation for 95 organism species. - Gclust Server | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us Gclust Server Amino acid sequences of predicted proteins and their annotation for 95 organis...m species. Data detail Data name Amino acid sequences of predicted proteins and their annotation for 95 orga...nism species. DOI 10.18908/lsdba.nbdc00464-001 Description of data contents Amino acid sequences of predicted proteins...Database Description Download License Update History of This Database Site Policy | Contact Us Amino acid sequences of predicted prot...eins and their annotation for 95 organism species. - Gclust Server | LSDB Archive ...

  15. Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases.

    Science.gov (United States)

    Wollbrett, Julien; Larmande, Pierre; de Lamotte, Frédéric; Ruiz, Manuel

    2013-04-15

    In recent years, a large amount of "-omics" data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic.

  16. Tidying up international nucleotide sequence databases: ecological, geographical and sequence quality annotation of its sequences of mycorrhizal fungi.

    Science.gov (United States)

    Tedersoo, Leho; Abarenkov, Kessy; Nilsson, R Henrik; Schüssler, Arthur; Grelet, Gwen-Aëlle; Kohout, Petr; Oja, Jane; Bonito, Gregory M; Veldre, Vilmar; Jairus, Teele; Ryberg, Martin; Larsson, Karl-Henrik; Kõljalg, Urmas

    2011-01-01

    Sequence analysis of the ribosomal RNA operon, particularly the internal transcribed spacer (ITS) region, provides a powerful tool for identification of mycorrhizal fungi. The sequence data deposited in the International Nucleotide Sequence Databases (INSD) are, however, unfiltered for quality and are often poorly annotated with metadata. To detect chimeric and low-quality sequences and assign the ectomycorrhizal fungi to phylogenetic lineages, fungal ITS sequences were downloaded from INSD, aligned within family-level groups, and examined through phylogenetic analyses and BLAST searches. By combining the fungal sequence database UNITE and the annotation and search tool PlutoF, we also added metadata from the literature to these accessions. Altogether 35,632 sequences belonged to mycorrhizal fungi or originated from ericoid and orchid mycorrhizal roots. Of these sequences, 677 were considered chimeric and 2,174 of low read quality. Information detailing country of collection, geographical coordinates, interacting taxon and isolation source were supplemented to cover 78.0%, 33.0%, 41.7% and 96.4% of the sequences, respectively. These annotated sequences are publicly available via UNITE (http://unite.ut.ee/) for downstream biogeographic, ecological and taxonomic analyses. In European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena/), the annotated sequences have a special link-out to UNITE. We intend to expand the data annotation to additional genes and all taxonomic groups and functional guilds of fungi.

  17. Evaluation of three automated genome annotations for Halorhabdus utahensis.

    Directory of Open Access Journals (Sweden)

    Peter Bakke

    2009-07-01

    Full Text Available Genome annotations are accumulating rapidly and depend heavily on automated annotation systems. Many genome centers offer annotation systems but no one has compared their output in a systematic way to determine accuracy and inherent errors. Errors in the annotations are routinely deposited in databases such as NCBI and used to validate subsequent annotation errors. We submitted the genome sequence of halophilic archaeon Halorhabdus utahensis to be analyzed by three genome annotation services. We have examined the output from each service in a variety of ways in order to compare the methodology and effectiveness of the annotations, as well as to explore the genes, pathways, and physiology of the previously unannotated genome. The annotation services differ considerably in gene calls, features, and ease of use. We had to manually identify the origin of replication and the species-specific consensus ribosome-binding site. Additionally, we conducted laboratory experiments to test H. utahensis growth and enzyme activity. Current annotation practices need to improve in order to more accurately reflect a genome's biological potential. We make specific recommendations that could improve the quality of microbial annotation projects.

  18. MimoSA: a system for minimotif annotation

    Directory of Open Access Journals (Sweden)

    Kundeti Vamsi

    2010-06-01

    Full Text Available Abstract Background Minimotifs are short peptide sequences within one protein, which are recognized by other proteins or molecules. While there are now several minimotif databases, they are incomplete. There are reports of many minimotifs in the primary literature, which have yet to be annotated, while entirely novel minimotifs continue to be published on a weekly basis. Our recently proposed function and sequence syntax for minimotifs enables us to build a general tool that will facilitate structured annotation and management of minimotif data from the biomedical literature. Results We have built the MimoSA application for minimotif annotation. The application supports management of the Minimotif Miner database, literature tracking, and annotation of new minimotifs. MimoSA enables the visualization, organization, selection and editing functions of minimotifs and their attributes in the MnM database. For the literature components, Mimosa provides paper status tracking and scoring of papers for annotation through a freely available machine learning approach, which is based on word correlation. The paper scoring algorithm is also available as a separate program, TextMine. Form-driven annotation of minimotif attributes enables entry of new minimotifs into the MnM database. Several supporting features increase the efficiency of annotation. The layered architecture of MimoSA allows for extensibility by separating the functions of paper scoring, minimotif visualization, and database management. MimoSA is readily adaptable to other annotation efforts that manually curate literature into a MySQL database. Conclusions MimoSA is an extensible application that facilitates minimotif annotation and integrates with the Minimotif Miner database. We have built MimoSA as an application that integrates dynamic abstract scoring with a high performance relational model of minimotif syntax. MimoSA's TextMine, an efficient paper-scoring algorithm, can be used to

  19. Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases

    Science.gov (United States)

    2013-01-01

    Background In recent years, a large amount of “-omics” data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. Results We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. Conclusions BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic. PMID:23586394

  20. Combining gene prediction methods to improve metagenomic gene annotation

    Directory of Open Access Journals (Sweden)

    Rosen Gail L

    2011-01-01

    Full Text Available Abstract Background Traditional gene annotation methods rely on characteristics that may not be available in short reads generated from next generation technology, resulting in suboptimal performance for metagenomic (environmental samples. Therefore, in recent years, new programs have been developed that optimize performance on short reads. In this work, we benchmark three metagenomic gene prediction programs and combine their predictions to improve metagenomic read gene annotation. Results We not only analyze the programs' performance at different read-lengths like similar studies, but also separate different types of reads, including intra- and intergenic regions, for analysis. The main deficiencies are in the algorithms' ability to predict non-coding regions and gene edges, resulting in more false-positives and false-negatives than desired. In fact, the specificities of the algorithms are notably worse than the sensitivities. By combining the programs' predictions, we show significant improvement in specificity at minimal cost to sensitivity, resulting in 4% improvement in accuracy for 100 bp reads with ~1% improvement in accuracy for 200 bp reads and above. To correctly annotate the start and stop of the genes, we find that a consensus of all the predictors performs best for shorter read lengths while a unanimous agreement is better for longer read lengths, boosting annotation accuracy by 1-8%. We also demonstrate use of the classifier combinations on a real dataset. Conclusions To optimize the performance for both prediction and annotation accuracies, we conclude that the consensus of all methods (or a majority vote is the best for reads 400 bp and shorter, while using the intersection of GeneMark and Orphelia predictions is the best for reads 500 bp and longer. We demonstrate that most methods predict over 80% coding (including partially coding reads on a real human gut sample sequenced by Illumina technology.

  1. Mouse SNP Miner: an annotated database of mouse functional single nucleotide polymorphisms

    Directory of Open Access Journals (Sweden)

    Ramensky Vasily E

    2007-01-01

    Full Text Available Abstract Background The mapping of quantitative trait loci in rat and mouse has been extremely successful in identifying chromosomal regions associated with human disease-related phenotypes. However, identifying the specific phenotype-causing DNA sequence variations within a quantitative trait locus has been much more difficult. The recent availability of genomic sequence from several mouse inbred strains (including C57BL/6J, 129X1/SvJ, 129S1/SvImJ, A/J, and DBA/2J has made it possible to catalog DNA sequence differences within a quantitative trait locus derived from crosses between these strains. However, even for well-defined quantitative trait loci ( Description To help identify functional DNA sequence variations within quantitative trait loci we have used the Ensembl annotated genome sequence to compile a database of mouse single nucleotide polymorphisms (SNPs that are predicted to cause missense, nonsense, frameshift, or splice site mutations (available at http://bioinfo.embl.it/SnpApplet/. For missense mutations we have used the PolyPhen and PANTHER algorithms to predict whether amino acid changes are likely to disrupt protein function. Conclusion We have developed a database of mouse SNPs predicted to cause missense, nonsense, frameshift, and splice-site mutations. Our analysis revealed that 20% and 14% of missense SNPs are likely to be deleterious according to PolyPhen and PANTHER, respectively, and 6% are considered deleterious by both algorithms. The database also provides gene expression and functional annotations from the Symatlas, Gene Ontology, and OMIM databases to further assess candidate phenotype-causing mutations. To demonstrate its utility, we show that Mouse SNP Miner successfully finds a previously identified candidate SNP in the taste receptor, Tas1r3, that underlies sucrose preference in the C57BL/6J strain. We also use Mouse SNP Miner to derive a list of candidate phenotype-causing mutations within a previously

  2. AcEST(EST sequences of Adiantum capillus-veneris and their annotation) - AcEST | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us AcEST AcEST(EST sequences of Adiantum capillus-veneris and their annotation) Data detail Dat...a name AcEST(EST sequences of Adiantum capillus-veneris and their annotation) DOI 10.18908/lsdba.nbdc00839-0...01 Description of data contents EST sequence of Adiantum capillus-veneris and its annotation (clone ID, libr...le search URL http://togodb.biosciencedbc.jp/togodb/view/archive_acest#en Data acquisition method Capillary ...ainst UniProtKB/Swiss-Prot and UniProtKB/TrEMBL databases) Number of data entries Adiantum capillus-veneris

  3. Graph-based sequence annotation using a data integration approach

    Directory of Open Access Journals (Sweden)

    Pesch Robert

    2008-06-01

    Full Text Available The automated annotation of data from high throughput sequencing and genomics experiments is a significant challenge for bioinformatics. Most current approaches rely on sequential pipelines of gene finding and gene function prediction methods that annotate a gene with information from different reference data sources. Each function prediction method contributes evidence supporting a functional assignment. Such approaches generally ignore the links between the information in the reference datasets. These links, however, are valuable for assessing the plausibility of a function assignment and can be used to evaluate the confidence in a prediction. We are working towards a novel annotation system that uses the network of information supporting the function assignment to enrich the annotation process for use by expert curators and predicting the function of previously unannotated genes. In this paper we describe our success in the first stages of this development. We present the data integration steps that are needed to create the core database of integrated reference databases (UniProt, PFAM, PDB, GO and the pathway database Ara- Cyc which has been established in the ONDEX data integration system. We also present a comparison between different methods for integration of GO terms as part of the function assignment pipeline and discuss the consequences of this analysis for improving the accuracy of gene function annotation.

  4. Protein sequence annotation in the genome era: the annotation concept of SWISS-PROT+TREMBL.

    Science.gov (United States)

    Apweiler, R; Gateau, A; Contrino, S; Martin, M J; Junker, V; O'Donovan, C; Lang, F; Mitaritonna, N; Kappus, S; Bairoch, A

    1997-01-01

    SWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation, a minimal level of redundancy and high level of integration with other databases. Ongoing genome sequencing projects have dramatically increased the number of protein sequences to be incorporated into SWISS-PROT. Since we do not want to dilute the quality standards of SWISS-PROT by incorporating sequences without proper sequence analysis and annotation, we cannot speed up the incorporation of new incoming data indefinitely. However, as we also want to make the sequences available as fast as possible, we introduced TREMBL (TRanslation of EMBL nucleotide sequence database), a supplement to SWISS-PROT. TREMBL consists of computer-annotated entries in SWISS-PROT format derived from the translation of all coding sequences (CDS) in the EMBL nucleotide sequence database, except for CDS already included in SWISS-PROT. While TREMBL is already of immense value, its computer-generated annotation does not match the quality of SWISS-PROTs. The main difference is in the protein functional information attached to sequences. With this in mind, we are dedicating substantial effort to develop and apply computer methods to enhance the functional information attached to TREMBL entries.

  5. The duplicated genes database: identification and functional annotation of co-localised duplicated genes across genomes.

    Directory of Open Access Journals (Sweden)

    Marion Ouedraogo

    Full Text Available BACKGROUND: There has been a surge in studies linking genome structure and gene expression, with special focus on duplicated genes. Although initially duplicated from the same sequence, duplicated genes can diverge strongly over evolution and take on different functions or regulated expression. However, information on the function and expression of duplicated genes remains sparse. Identifying groups of duplicated genes in different genomes and characterizing their expression and function would therefore be of great interest to the research community. The 'Duplicated Genes Database' (DGD was developed for this purpose. METHODOLOGY: Nine species were included in the DGD. For each species, BLAST analyses were conducted on peptide sequences corresponding to the genes mapped on a same chromosome. Groups of duplicated genes were defined based on these pairwise BLAST comparisons and the genomic location of the genes. For each group, Pearson correlations between gene expression data and semantic similarities between functional GO annotations were also computed when the relevant information was available. CONCLUSIONS: The Duplicated Gene Database provides a list of co-localised and duplicated genes for several species with the available gene co-expression level and semantic similarity value of functional annotation. Adding these data to the groups of duplicated genes provides biological information that can prove useful to gene expression analyses. The Duplicated Gene Database can be freely accessed through the DGD website at http://dgd.genouest.org.

  6. Graph-based sequence annotation using a data integration approach.

    Science.gov (United States)

    Pesch, Robert; Lysenko, Artem; Hindle, Matthew; Hassani-Pak, Keywan; Thiele, Ralf; Rawlings, Christopher; Köhler, Jacob; Taubert, Jan

    2008-08-25

    The automated annotation of data from high throughput sequencing and genomics experiments is a significant challenge for bioinformatics. Most current approaches rely on sequential pipelines of gene finding and gene function prediction methods that annotate a gene with information from different reference data sources. Each function prediction method contributes evidence supporting a functional assignment. Such approaches generally ignore the links between the information in the reference datasets. These links, however, are valuable for assessing the plausibility of a function assignment and can be used to evaluate the confidence in a prediction. We are working towards a novel annotation system that uses the network of information supporting the function assignment to enrich the annotation process for use by expert curators and predicting the function of previously unannotated genes. In this paper we describe our success in the first stages of this development. We present the data integration steps that are needed to create the core database of integrated reference databases (UniProt, PFAM, PDB, GO and the pathway database Ara-Cyc) which has been established in the ONDEX data integration system. We also present a comparison between different methods for integration of GO terms as part of the function assignment pipeline and discuss the consequences of this analysis for improving the accuracy of gene function annotation. The methods and algorithms presented in this publication are an integral part of the ONDEX system which is freely available from http://ondex.sf.net/.

  7. Algal Functional Annotation Tool: a web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data

    Directory of Open Access Journals (Sweden)

    Merchant Sabeeha S

    2011-07-01

    Full Text Available Abstract Background Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. Description The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of

  8. Dictionary-driven protein annotation.

    Science.gov (United States)

    Rigoutsos, Isidore; Huynh, Tien; Floratos, Aris; Parida, Laxmi; Platt, Daniel

    2002-09-01

    Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were

  9. The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation.

    Science.gov (United States)

    Profiti, Giuseppe; Martelli, Pier Luigi; Casadio, Rita

    2017-07-03

    BAR 3.0 updates our server BAR (Bologna Annotation Resource) for predicting protein structural and functional features from sequence. We increase data volume, query capabilities and information conveyed to the user. The core of BAR 3.0 is a graph-based clustering procedure of UniProtKB sequences, following strict pairwise similarity criteria (sequence identity ≥40% with alignment coverage ≥90%). Each cluster contains the available annotation downloaded from UniProtKB, GO, PFAM and PDB. After statistical validation, GO terms and PFAM domains are cluster-specific and annotate new sequences entering the cluster after satisfying similarity constraints. BAR 3.0 includes 28 869 663 sequences in 1 361 773 clusters, of which 22.2% (22 241 661 sequences) and 47.4% (24 555 055 sequences) have at least one validated GO term and one PFAM domain, respectively. 1.4% of the clusters (36% of all sequences) include PDB structures and the cluster is associated to a hidden Markov model that allows building template-target alignment suitable for structural modeling. Some other 3 399 026 sequences are singletons. BAR 3.0 offers an improved search interface, allowing queries by UniProtKB-accession, Fasta sequence, GO-term, PFAM-domain, organism, PDB and ligand/s. When evaluated on the CAFA2 targets, BAR 3.0 largely outperforms our previous version and scores among state-of-the-art methods. BAR 3.0 is publicly available and accessible at http://bar.biocomp.unibo.it/bar3. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  10. Annotation of metabolites from gas chromatography/atmospheric pressure chemical ionization tandem mass spectrometry data using an in silico generated compound database and MetFrag.

    Science.gov (United States)

    Ruttkies, Christoph; Strehmel, Nadine; Scheel, Dierk; Neumann, Steffen

    2015-08-30

    Gas chromatography (GC) coupled to atmospheric pressure chemical ionization quadrupole time-of-flight mass spectrometry (APCI-QTOFMS) is an emerging technology in metabolomics. Reference spectra for GC/APCI-MS/MS barely exist; therefore, in silico fragmentation approaches and structure databases are prerequisites for annotation. To expand the limited coverage of derivatised structures in structure databases, in silico derivatisation procedures are required. A cheminformatics workflow has been developed for in silico derivatisation of compounds found in KEGG and PubChem, and validated on the Golm Metabolome Database (GMD). To demonstrate this workflow, these in silico generated databases were applied together with MetFrag to APCI-MS/MS spectra acquired from GC/APCI-MS/MS profiles of Arabidopsis thaliana and Solanum tuberosum. The Metabolite-Likeness of the original candidate structure was included as additional scoring term aiming at candidate structures of natural origin. The validation of our in silico derivatisation workflow on the GMD showed a true positive rate of 94%. MetFrag was applied to two datasets. In silico derivatisation of the KEGG and PubChem database served as a candidate source. For both datasets the Metabolite-Likeness score improved the identification performance. The derivatised data sources have been included into the MetFrag web application for the annotation of GC/APCI-MS/MS spectra. We demonstrated that MetFrag can support the identification of components from GC/APCI-MS/MS profiles, especially in the (common) case where reference spectra are not available. This workflow can be easily adapted to other types of derivatisation and is freely accessible together with the generated structure databases. Copyright © 2015 John Wiley & Sons, Ltd.

  11. Annotation Method (AM): SE7_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available base search. Peaks with no hit to these databases are then selected to secondary se...arch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are ma...SE7_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary data

  12. Annotation Method (AM): SE36_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE36_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  13. Annotation Method (AM): SE14_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE14_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  14. Annotation Method (AM): SE33_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE33_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  15. Annotation Method (AM): SE12_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE12_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  16. Annotation Method (AM): SE20_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE20_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  17. Annotation Method (AM): SE2_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available base search. Peaks with no hit to these databases are then selected to secondary se...arch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are ma...SE2_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary data

  18. Annotation Method (AM): SE28_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE28_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  19. Annotation Method (AM): SE11_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE11_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  20. Annotation Method (AM): SE17_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE17_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  1. Annotation Method (AM): SE10_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE10_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  2. Annotation Method (AM): SE4_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available base search. Peaks with no hit to these databases are then selected to secondary se...arch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are ma...SE4_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary data

  3. Annotation Method (AM): SE9_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available base search. Peaks with no hit to these databases are then selected to secondary se...arch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are ma...SE9_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary data

  4. Annotation Method (AM): SE3_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available base search. Peaks with no hit to these databases are then selected to secondary se...arch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are ma...SE3_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary data

  5. Annotation Method (AM): SE25_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE25_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  6. Annotation Method (AM): SE30_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE30_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  7. Annotation Method (AM): SE16_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE16_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  8. Annotation Method (AM): SE29_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE29_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  9. Annotation Method (AM): SE35_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE35_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  10. Annotation Method (AM): SE6_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available base search. Peaks with no hit to these databases are then selected to secondary se...arch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are ma...SE6_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary data

  11. Annotation Method (AM): SE1_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available base search. Peaks with no hit to these databases are then selected to secondary se...arch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are ma...SE1_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary data

  12. Annotation Method (AM): SE8_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available base search. Peaks with no hit to these databases are then selected to secondary se...arch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are ma...SE8_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary data

  13. Annotation Method (AM): SE13_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE13_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  14. Annotation Method (AM): SE26_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE26_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  15. Annotation Method (AM): SE27_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE27_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  16. Annotation Method (AM): SE34_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE34_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  17. Annotation Method (AM): SE5_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available base search. Peaks with no hit to these databases are then selected to secondary se...arch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are ma...SE5_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary data

  18. Annotation Method (AM): SE15_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE15_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  19. Annotation Method (AM): SE31_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE31_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  20. Annotation Method (AM): SE32_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available abase search. Peaks with no hit to these databases are then selected to secondary s...earch using exactMassDB and Pep1000 databases. After the database search processes, each database hits are m...SE32_AM1 PowerGet annotation A1 In annotation process, KEGG, KNApSAcK and LipidMAPS are used for primary dat

  1. Annotation-based feature extraction from sets of SBML models.

    Science.gov (United States)

    Alm, Rebekka; Waltemath, Dagmar; Wolfien, Markus; Wolkenhauer, Olaf; Henkel, Ron

    2015-01-01

    Model repositories such as BioModels Database provide computational models of biological systems for the scientific community. These models contain rich semantic annotations that link model entities to concepts in well-established bio-ontologies such as Gene Ontology. Consequently, thematically similar models are likely to share similar annotations. Based on this assumption, we argue that semantic annotations are a suitable tool to characterize sets of models. These characteristics improve model classification, allow to identify additional features for model retrieval tasks, and enable the comparison of sets of models. In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in SBML format which were composed from BioModels Database. To characterize each of these sets, we analyzed and extracted concepts from three frequently used ontologies, namely Gene Ontology, ChEBI and SBO. We find that three out of the methods are suitable to determine characteristic features for arbitrary sets of models: The selected features vary depending on the underlying model set, and they are also specific to the chosen model set. We show that the identified features map on concepts that are higher up in the hierarchy of the ontologies than the concepts used for model annotations. Our analysis also reveals that the information content of concepts in ontologies and their usage for model annotation do not correlate. Annotation-based feature extraction enables the comparison of model sets, as opposed to existing methods for model-to-keyword comparison, or model-to-model comparison.

  2. Chado controller: advanced annotation management with a community annotation system.

    Science.gov (United States)

    Guignon, Valentin; Droc, Gaëtan; Alaux, Michael; Baurens, Franc-Christophe; Garsmeur, Olivier; Poiron, Claire; Carver, Tim; Rouard, Mathieu; Bocs, Stéphanie

    2012-04-01

    We developed a controller that is compliant with the Chado database schema, GBrowse and genome annotation-editing tools such as Artemis and Apollo. It enables the management of public and private data, monitors manual annotation (with controlled vocabularies, structural and functional annotation controls) and stores versions of annotation for all modified features. The Chado controller uses PostgreSQL and Perl. The Chado Controller package is available for download at http://www.gnpannot.org/content/chado-controller and runs on any Unix-like operating system, and documentation is available at http://www.gnpannot.org/content/chado-controller-doc The system can be tested using the GNPAnnot Sandbox at http://www.gnpannot.org/content/gnpannot-sandbox-form valentin.guignon@cirad.fr; stephanie.sidibe-bocs@cirad.fr Supplementary data are available at Bioinformatics online.

  3. Retrieval-based Face Annotation by Weak Label Regularized Local Coordinate Coding.

    Science.gov (United States)

    Wang, Dayong; Hoi, Steven C H; He, Ying; Zhu, Jianke; Mei, Tao; Luo, Jiebo

    2013-08-02

    Retrieval-based face annotation is a promising paradigm of mining massive web facial images for automated face annotation. This paper addresses a critical problem of such paradigm, i.e., how to effectively perform annotation by exploiting the similar facial images and their weak labels which are often noisy and incomplete. In particular, we propose an effective Weak Label Regularized Local Coordinate Coding (WLRLCC) technique, which exploits the principle of local coordinate coding in learning sparse features, and employs the idea of graph-based weak label regularization to enhance the weak labels of the similar facial images. We present an efficient optimization algorithm to solve the WLRLCC task. We conduct extensive empirical studies on two large-scale web facial image databases: (i) a Western celebrity database with a total of $6,025$ persons and $714,454$ web facial images, and (ii)an Asian celebrity database with $1,200$ persons and $126,070$ web facial images. The encouraging results validate the efficacy of the proposed WLRLCC algorithm. To further improve the efficiency and scalability, we also propose a PCA-based approximation scheme and an offline approximation scheme (AWLRLCC), which generally maintains comparable results but significantly saves much time cost. Finally, we show that WLRLCC can also tackle two existing face annotation tasks with promising performance.

  4. Comparative high-throughput transcriptome sequencing and development of SiESTa, the Silene EST annotation database

    Directory of Open Access Journals (Sweden)

    Marais Gabriel AB

    2011-07-01

    Full Text Available Abstract Background The genus Silene is widely used as a model system for addressing ecological and evolutionary questions in plants, but advances in using the genus as a model system are impeded by the lack of available resources for studying its genome. Massively parallel sequencing cDNA has recently developed into an efficient method for characterizing the transcriptomes of non-model organisms, generating massive amounts of data that enable the study of multiple species in a comparative framework. The sequences generated provide an excellent resource for identifying expressed genes, characterizing functional variation and developing molecular markers, thereby laying the foundations for future studies on gene sequence and gene expression divergence. Here, we report the results of a comparative transcriptome sequencing study of eight individuals representing four Silene and one Dianthus species as outgroup. All sequences and annotations have been deposited in a newly developed and publicly available database called SiESTa, the Silene EST annotation database. Results A total of 1,041,122 EST reads were generated in two runs on a Roche GS-FLX 454 pyrosequencing platform. EST reads were analyzed separately for all eight individuals sequenced and were assembled into contigs using TGICL. These were annotated with results from BLASTX searches and Gene Ontology (GO terms, and thousands of single-nucleotide polymorphisms (SNPs were characterized. Unassembled reads were kept as singletons and together with the contigs contributed to the unigenes characterized in each individual. The high quality of unigenes is evidenced by the proportion (49% that have significant hits in similarity searches with the A. thaliana proteome. The SiESTa database is accessible at http://www.siesta.ethz.ch. Conclusion The sequence collections established in the present study provide an important genomic resource for four Silene and one Dianthus species and will help to

  5. Comparative high-throughput transcriptome sequencing and development of SiESTa, the Silene EST annotation database

    Science.gov (United States)

    2011-01-01

    Background The genus Silene is widely used as a model system for addressing ecological and evolutionary questions in plants, but advances in using the genus as a model system are impeded by the lack of available resources for studying its genome. Massively parallel sequencing cDNA has recently developed into an efficient method for characterizing the transcriptomes of non-model organisms, generating massive amounts of data that enable the study of multiple species in a comparative framework. The sequences generated provide an excellent resource for identifying expressed genes, characterizing functional variation and developing molecular markers, thereby laying the foundations for future studies on gene sequence and gene expression divergence. Here, we report the results of a comparative transcriptome sequencing study of eight individuals representing four Silene and one Dianthus species as outgroup. All sequences and annotations have been deposited in a newly developed and publicly available database called SiESTa, the Silene EST annotation database. Results A total of 1,041,122 EST reads were generated in two runs on a Roche GS-FLX 454 pyrosequencing platform. EST reads were analyzed separately for all eight individuals sequenced and were assembled into contigs using TGICL. These were annotated with results from BLASTX searches and Gene Ontology (GO) terms, and thousands of single-nucleotide polymorphisms (SNPs) were characterized. Unassembled reads were kept as singletons and together with the contigs contributed to the unigenes characterized in each individual. The high quality of unigenes is evidenced by the proportion (49%) that have significant hits in similarity searches with the A. thaliana proteome. The SiESTa database is accessible at http://www.siesta.ethz.ch. Conclusion The sequence collections established in the present study provide an important genomic resource for four Silene and one Dianthus species and will help to further develop Silene as a

  6. Characterizing and annotating the genome using RNA-seq data.

    Science.gov (United States)

    Chen, Geng; Shi, Tieliu; Shi, Leming

    2017-02-01

    Bioinformatics methods for various RNA-seq data analyses are in fast evolution with the improvement of sequencing technologies. However, many challenges still exist in how to efficiently process the RNA-seq data to obtain accurate and comprehensive results. Here we reviewed the strategies for improving diverse transcriptomic studies and the annotation of genetic variants based on RNA-seq data. Mapping RNA-seq reads to the genome and transcriptome represent two distinct methods for quantifying the expression of genes/transcripts. Besides the known genes annotated in current databases, many novel genes/transcripts (especially those long noncoding RNAs) still can be identified on the reference genome using RNA-seq. Moreover, owing to the incompleteness of current reference genomes, some novel genes are missing from them. Genome- guided and de novo transcriptome reconstruction are two effective and complementary strategies for identifying those novel genes/transcripts on or beyond the reference genome. In addition, integrating the genes of distinct databases to conduct transcriptomics and genetics studies can improve the results of corresponding analyses.

  7. Re-annotation and re-analysis of the Campylobacter jejuni NCTC11168 genome sequence

    Directory of Open Access Journals (Sweden)

    Dorrell Nick

    2007-06-01

    Full Text Available Abstract Background Campylobacter jejuni is the leading bacterial cause of human gastroenteritis in the developed world. To improve our understanding of this important human pathogen, the C. jejuni NCTC11168 genome was sequenced and published in 2000. The original annotation was a milestone in Campylobacter research, but is outdated. We now describe the complete re-annotation and re-analysis of the C. jejuni NCTC11168 genome using current database information, novel tools and annotation techniques not used during the original annotation. Results Re-annotation was carried out using sequence database searches such as FASTA, along with programs such as TMHMM for additional support. The re-annotation also utilises sequence data from additional Campylobacter strains and species not available during the original annotation. Re-annotation was accompanied by a full literature search that was incorporated into the updated EMBL file [EMBL: AL111168]. The C. jejuni NCTC11168 re-annotation reduced the total number of coding sequences from 1654 to 1643, of which 90.0% have additional information regarding the identification of new motifs and/or relevant literature. Re-annotation has led to 18.2% of coding sequence product functions being revised. Conclusions Major updates were made to genes involved in the biosynthesis of important surface structures such as lipooligosaccharide, capsule and both O- and N-linked glycosylation. This re-annotation will be a key resource for Campylobacter research and will also provide a prototype for the re-annotation and re-interpretation of other bacterial genomes.

  8. Supporting Keyword Search for Image Retrieval with Integration of Probabilistic Annotation

    Directory of Open Access Journals (Sweden)

    Tie Hua Zhou

    2015-05-01

    Full Text Available The ever-increasing quantities of digital photo resources are annotated with enriching vocabularies to form semantic annotations. Photo-sharing social networks have boosted the need for efficient and intuitive querying to respond to user requirements in large-scale image collections. In order to help users formulate efficient and effective image retrieval, we present a novel integration of a probabilistic model based on keyword query architecture that models the probability distribution of image annotations: allowing users to obtain satisfactory results from image retrieval via the integration of multiple annotations. We focus on the annotation integration step in order to specify the meaning of each image annotation, thus leading to the most representative annotations of the intent of a keyword search. For this demonstration, we show how a probabilistic model has been integrated to semantic annotations to allow users to intuitively define explicit and precise keyword queries in order to retrieve satisfactory image results distributed in heterogeneous large data sources. Our experiments on SBU (collected by Stony Brook University database show that (i our integrated annotation contains higher quality representatives and semantic matches; and (ii the results indicating annotation integration can indeed improve image search result quality.

  9. DFAST and DAGA: web-based integrated genome annotation tools and resources.

    Science.gov (United States)

    Tanizawa, Yasuhiro; Fujisawa, Takatomo; Kaminuma, Eli; Nakamura, Yasukazu; Arita, Masanori

    2016-01-01

    Quality assurance and correct taxonomic affiliation of data submitted to public sequence databases have been an everlasting problem. The DDBJ Fast Annotation and Submission Tool (DFAST) is a newly developed genome annotation pipeline with quality and taxonomy assessment tools. To enable annotation of ready-to-submit quality, we also constructed curated reference protein databases tailored for lactic acid bacteria. DFAST was developed so that all the procedures required for DDBJ submission could be done seamlessly online. The online workspace would be especially useful for users not familiar with bioinformatics skills. In addition, we have developed a genome repository, DFAST Archive of Genome Annotation (DAGA), which currently includes 1,421 genomes covering 179 species and 18 subspecies of two genera, Lactobacillus and Pediococcus , obtained from both DDBJ/ENA/GenBank and Sequence Read Archive (SRA). All the genomes deposited in DAGA were annotated consistently and assessed using DFAST. To assess the taxonomic position based on genomic sequence information, we used the average nucleotide identity (ANI), which showed high discriminative power to determine whether two given genomes belong to the same species. We corrected mislabeled or misidentified genomes in the public database and deposited the curated information in DAGA. The repository will improve the accessibility and reusability of genome resources for lactic acid bacteria. By exploiting the data deposited in DAGA, we found intraspecific subgroups in Lactobacillus gasseri and Lactobacillus jensenii , whose variation between subgroups is larger than the well-accepted ANI threshold of 95% to differentiate species. DFAST and DAGA are freely accessible at https://dfast.nig.ac.jp.

  10. MIPS: analysis and annotation of genome information in 2007.

    Science.gov (United States)

    Mewes, H W; Dietmann, S; Frishman, D; Gregory, R; Mannhaupt, G; Mayer, K F X; Münsterkötter, M; Ruepp, A; Spannagl, M; Stümpflen, V; Rattei, T

    2008-01-01

    The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) combines automatic processing of large amounts of sequences with manual annotation of selected model genomes. Due to the massive growth of the available data, the depth of annotation varies widely between independent databases. Also, the criteria for the transfer of information from known to orthologous sequences are diverse. To cope with the task of global in-depth genome annotation has become unfeasible. Therefore, our efforts are dedicated to three levels of annotation: (i) the curation of selected genomes, in particular from fungal and plant taxa (e.g. CYGD, MNCDB, MatDB), (ii) the comprehensive, consistent, automatic annotation employing exhaustive methods for the computation of sequence similarities and sequence-related attributes as well as the classification of individual sequences (SIMAP, PEDANT and FunCat) and (iii) the compilation of manually curated databases for protein interactions based on scrutinized information from the literature to serve as an accepted set of reliable annotated interaction data (MPACT, MPPI, CORUM). All databases and tools described as well as the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).

  11. Annotating the biomedical literature for the human variome.

    Science.gov (United States)

    Verspoor, Karin; Jimeno Yepes, Antonio; Cavedon, Lawrence; McIntosh, Tara; Herten-Crabb, Asha; Thomas, Zoë; Plazzer, John-Paul

    2013-01-01

    This article introduces the Variome Annotation Schema, a schema that aims to capture the core concepts and relations relevant to cataloguing and interpreting human genetic variation and its relationship to disease, as described in the published literature. The schema was inspired by the needs of the database curators of the International Society for Gastrointestinal Hereditary Tumours (InSiGHT) database, but is intended to have application to genetic variation information in a range of diseases. The schema has been applied to a small corpus of full text journal publications on the subject of inherited colorectal cancer. We show that the inter-annotator agreement on annotation of this corpus ranges from 0.78 to 0.95 F-score across different entity types when exact matching is measured, and improves to a minimum F-score of 0.87 when boundary matching is relaxed. Relations show more variability in agreement, but several are reliable, with the highest, cohort-has-size, reaching 0.90 F-score. We also explore the relevance of the schema to the InSiGHT database curation process. The schema and the corpus represent an important new resource for the development of text mining solutions that address relationships among patient cohorts, disease and genetic variation, and therefore, we also discuss the role text mining might play in the curation of information related to the human variome. The corpus is available at http://opennicta.com/home/health/variome.

  12. Annotating the human genome with Disease Ontology

    Science.gov (United States)

    Osborne, John D; Flatow, Jared; Holko, Michelle; Lin, Simon M; Kibbe, Warren A; Zhu, Lihua (Julie); Danila, Maria I; Feng, Gang; Chisholm, Rex L

    2009-01-01

    Background The human genome has been extensively annotated with Gene Ontology for biological functions, but minimally computationally annotated for diseases. Results We used the Unified Medical Language System (UMLS) MetaMap Transfer tool (MMTx) to discover gene-disease relationships from the GeneRIF database. We utilized a comprehensive subset of UMLS, which is disease-focused and structured as a directed acyclic graph (the Disease Ontology), to filter and interpret results from MMTx. The results were validated against the Homayouni gene collection using recall and precision measurements. We compared our results with the widely used Online Mendelian Inheritance in Man (OMIM) annotations. Conclusion The validation data set suggests a 91% recall rate and 97% precision rate of disease annotation using GeneRIF, in contrast with a 22% recall and 98% precision using OMIM. Our thesaurus-based approach allows for comparisons to be made between disease containing databases and allows for increased accuracy in disease identification through synonym matching. The much higher recall rate of our approach demonstrates that annotating human genome with Disease Ontology and GeneRIF for diseases dramatically increases the coverage of the disease annotation of human genome. PMID:19594883

  13. Facilitating functional annotation of chicken microarray data

    Directory of Open Access Journals (Sweden)

    Gresham Cathy R

    2009-10-01

    Full Text Available Abstract Background Modeling results from chicken microarray studies is challenging for researchers due to little functional annotation associated with these arrays. The Affymetrix GenChip chicken genome array, one of the biggest arrays that serve as a key research tool for the study of chicken functional genomics, is among the few arrays that link gene products to Gene Ontology (GO. However the GO annotation data presented by Affymetrix is incomplete, for example, they do not show references linked to manually annotated functions. In addition, there is no tool that facilitates microarray researchers to directly retrieve functional annotations for their datasets from the annotated arrays. This costs researchers amount of time in searching multiple GO databases for functional information. Results We have improved the breadth of functional annotations of the gene products associated with probesets on the Affymetrix chicken genome array by 45% and the quality of annotation by 14%. We have also identified the most significant diseases and disorders, different types of genes, and known drug targets represented on Affymetrix chicken genome array. To facilitate functional annotation of other arrays and microarray experimental datasets we developed an Array GO Mapper (AGOM tool to help researchers to quickly retrieve corresponding functional information for their dataset. Conclusion Results from this study will directly facilitate annotation of other chicken arrays and microarray experimental datasets. Researchers will be able to quickly model their microarray dataset into more reliable biological functional information by using AGOM tool. The disease, disorders, gene types and drug targets revealed in the study will allow researchers to learn more about how genes function in complex biological systems and may lead to new drug discovery and development of therapies. The GO annotation data generated will be available for public use via AgBase website and

  14. Semi-Automated Annotation of Biobank Data Using Standard Medical Terminologies in a Graph Database.

    Science.gov (United States)

    Hofer, Philipp; Neururer, Sabrina; Goebel, Georg

    2016-01-01

    Data describing biobank resources frequently contains unstructured free-text information or insufficient coding standards. (Bio-) medical ontologies like Orphanet Rare Diseases Ontology (ORDO) or the Human Disease Ontology (DOID) provide a high number of concepts, synonyms and entity relationship properties. Such standard terminologies increase quality and granularity of input data by adding comprehensive semantic background knowledge from validated entity relationships. Moreover, cross-references between terminology concepts facilitate data integration across databases using different coding standards. In order to encourage the use of standard terminologies, our aim is to identify and link relevant concepts with free-text diagnosis inputs within a biobank registry. Relevant concepts are selected automatically by lexical matching and SPARQL queries against a RDF triplestore. To ensure correctness of annotations, proposed concepts have to be confirmed by medical data administration experts before they are entered into the registry database. Relevant (bio-) medical terminologies describing diseases and phenotypes were identified and stored in a graph database which was tied to a local biobank registry. Concept recommendations during data input trigger a structured description of medical data and facilitate data linkage between heterogeneous systems.

  15. MicroScope: a platform for microbial genome annotation and comparative genomics.

    Science.gov (United States)

    Vallenet, D; Engelen, S; Mornico, D; Cruveiller, S; Fleury, L; Lajus, A; Rouy, Z; Roche, D; Salvignol, G; Scarpelli, C; Médigue, C

    2009-01-01

    The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope's rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of

  16. HIVBrainSeqDB: a database of annotated HIV envelope sequences from brain and other anatomical sites

    Directory of Open Access Journals (Sweden)

    O'Connor Niall

    2010-12-01

    Full Text Available Abstract Background The population of HIV replicating within a host consists of independently evolving and interacting sub-populations that can be genetically distinct within anatomical compartments. HIV replicating within the brain causes neurocognitive disorders in up to 20-30% of infected individuals and is a viral sanctuary site for the development of drug resistance. The primary determinant of HIV neurotropism is macrophage tropism, which is primarily determined by the viral envelope (env gene. However, studies of genetic aspects of HIV replicating in the brain are hindered because existing repositories of HIV sequences are not focused on neurotropic virus nor annotated with neurocognitive and neuropathological status. To address this need, we constructed the HIV Brain Sequence Database. Results The HIV Brain Sequence Database is a public database of HIV envelope sequences, directly sequenced from brain and other tissues from the same patients. Sequences are annotated with clinical data including viral load, CD4 count, antiretroviral status, neurocognitive impairment, and neuropathological diagnosis, all curated from the original publication. Tissue source is coded using an anatomical ontology, the Foundational Model of Anatomy, to capture the maximum level of detail available, while maintaining ontological relationships between tissues and their subparts. 44 tissue types are represented within the database, grouped into 4 categories: (i brain, brainstem, and spinal cord; (ii meninges, choroid plexus, and CSF; (iii blood and lymphoid; and (iv other (bone marrow, colon, lung, liver, etc. Patient coding is correlated across studies, allowing sequences from the same patient to be grouped to increase statistical power. Using Cytoscape, we visualized relationships between studies, patients and sequences, illustrating interconnections between studies and the varying depth of sequencing, patient number, and tissue representation across studies

  17. Ontology modularization to improve semantic medical image annotation.

    Science.gov (United States)

    Wennerberg, Pinar; Schulz, Klaus; Buitelaar, Paul

    2011-02-01

    Searching for medical images and patient reports is a significant challenge in a clinical setting. The contents of such documents are often not described in sufficient detail thus making it difficult to utilize the inherent wealth of information contained within them. Semantic image annotation addresses this problem by describing the contents of images and reports using medical ontologies. Medical images and patient reports are then linked to each other through common annotations. Subsequently, search algorithms can more effectively find related sets of documents on the basis of these semantic descriptions. A prerequisite to realizing such a semantic search engine is that the data contained within should have been previously annotated with concepts from medical ontologies. One major challenge in this regard is the size and complexity of medical ontologies as annotation sources. Manual annotation is particularly time consuming labor intensive in a clinical environment. In this article we propose an approach to reducing the size of clinical ontologies for more efficient manual image and text annotation. More precisely, our goal is to identify smaller fragments of a large anatomy ontology that are relevant for annotating medical images from patients suffering from lymphoma. Our work is in the area of ontology modularization, which is a recent and active field of research. We describe our approach, methods and data set in detail and we discuss our results. Copyright © 2010 Elsevier Inc. All rights reserved.

  18. A Linked Data-Based Collaborative Annotation System for Increasing Learning Achievements

    Science.gov (United States)

    Zarzour, Hafed; Sellami, Mokhtar

    2017-01-01

    With the emergence of the Web 2.0, collaborative annotation practices have become more mature in the field of learning. In this context, several recent studies have shown the powerful effects of the integration of annotation mechanism in learning process. However, most of these studies provide poor support for semantically structured resources,…

  19. ODG: Omics database generator - a tool for generating, querying, and analyzing multi-omics comparative databases to facilitate biological understanding.

    Science.gov (United States)

    Guhlin, Joseph; Silverstein, Kevin A T; Zhou, Peng; Tiffin, Peter; Young, Nevin D

    2017-08-10

    Rapid generation of omics data in recent years have resulted in vast amounts of disconnected datasets without systemic integration and knowledge building, while individual groups have made customized, annotated datasets available on the web with few ways to link them to in-lab datasets. With so many research groups generating their own data, the ability to relate it to the larger genomic and comparative genomic context is becoming increasingly crucial to make full use of the data. The Omics Database Generator (ODG) allows users to create customized databases that utilize published genomics data integrated with experimental data which can be queried using a flexible graph database. When provided with omics and experimental data, ODG will create a comparative, multi-dimensional graph database. ODG can import definitions and annotations from other sources such as InterProScan, the Gene Ontology, ENZYME, UniPathway, and others. This annotation data can be especially useful for studying new or understudied species for which transcripts have only been predicted, and rapidly give additional layers of annotation to predicted genes. In better studied species, ODG can perform syntenic annotation translations or rapidly identify characteristics of a set of genes or nucleotide locations, such as hits from an association study. ODG provides a web-based user-interface for configuring the data import and for querying the database. Queries can also be run from the command-line and the database can be queried directly through programming language hooks available for most languages. ODG supports most common genomic formats as well as generic, easy to use tab-separated value format for user-provided annotations. ODG is a user-friendly database generation and query tool that adapts to the supplied data to produce a comparative genomic database or multi-layered annotation database. ODG provides rapid comparative genomic annotation and is therefore particularly useful for non-model or

  20. AGORA : Organellar genome annotation from the amino acid and nucleotide references.

    Science.gov (United States)

    Jung, Jaehee; Kim, Jong Im; Jeong, Young-Sik; Yi, Gangman

    2018-03-29

    Next-generation sequencing (NGS) technologies have led to the accumulation of highthroughput sequence data from various organisms in biology. To apply gene annotation of organellar genomes for various organisms, more optimized tools for functional gene annotation are required. Almost all gene annotation tools are mainly focused on the chloroplast genome of land plants or the mitochondrial genome of animals.We have developed a web application AGORA for the fast, user-friendly, and improved annotations of organellar genomes. AGORA annotates genes based on a BLAST-based homology search and clustering with selected reference sequences from the NCBI database or user-defined uploaded data. AGORA can annotate the functional genes in almost all mitochondrion and plastid genomes of eukaryotes. The gene annotation of a genome with an exon-intron structure within a gene or inverted repeat region is also available. It provides information of start and end positions of each gene, BLAST results compared with the reference sequence, and visualization of gene map by OGDRAW. Users can freely use the software, and the accessible URL is https://bigdata.dongguk.edu/gene_project/AGORA/.The main module of the tool is implemented by the python and php, and the web page is built by the HTML and CSS to support all browsers. gangman@dongguk.edu.

  1. neXtA5: accelerating annotation of articles via automated approaches in neXtProt.

    Science.gov (United States)

    Mottin, Luc; Gobeill, Julien; Pasche, Emilie; Michel, Pierre-André; Cusin, Isabelle; Gaudet, Pascale; Ruch, Patrick

    2016-01-01

    The rapid increase in the number of published articles poses a challenge for curated databases to remain up-to-date. To help the scientific community and database curators deal with this issue, we have developed an application, neXtA5, which prioritizes the literature for specific curation requirements. Our system, neXtA5, is a curation service composed of three main elements. The first component is a named-entity recognition module, which annotates MEDLINE over some predefined axes. This report focuses on three axes: Diseases, the Molecular Function and Biological Process sub-ontologies of the Gene Ontology (GO). The automatic annotations are then stored in a local database, BioMed, for each annotation axis. Additional entities such as species and chemical compounds are also identified. The second component is an existing search engine, which retrieves the most relevant MEDLINE records for any given query. The third component uses the content of BioMed to generate an axis-specific ranking, which takes into account the density of named-entities as stored in the Biomed database. The two ranked lists are ultimately merged using a linear combination, which has been specifically tuned to support the annotation of each axis. The fine-tuning of the coefficients is formally reported for each axis-driven search. Compared with PubMed, which is the system used by most curators, the improvement is the following: +231% for Diseases, +236% for Molecular Functions and +3153% for Biological Process when measuring the precision of the top-returned PMID (P0 or mean reciprocal rank). The current search methods significantly improve the search effectiveness of curators for three important curation axes. Further experiments are being performed to extend the curation types, in particular protein-protein interactions, which require specific relationship extraction capabilities. In parallel, user-friendly interfaces powered with a set of JSON web services are currently being

  2. Assessment of Metabolome Annotation Quality: A Method for Evaluating the False Discovery Rate of Elemental Composition Searches

    Science.gov (United States)

    Matsuda, Fumio; Shinbo, Yoko; Oikawa, Akira; Hirai, Masami Yokota; Fiehn, Oliver; Kanaya, Shigehiko; Saito, Kazuki

    2009-01-01

    Background In metabolomics researches using mass spectrometry (MS), systematic searching of high-resolution mass data against compound databases is often the first step of metabolite annotation to determine elemental compositions possessing similar theoretical mass numbers. However, incorrect hits derived from errors in mass analyses will be included in the results of elemental composition searches. To assess the quality of peak annotation information, a novel methodology for false discovery rates (FDR) evaluation is presented in this study. Based on the FDR analyses, several aspects of an elemental composition search, including setting a threshold, estimating FDR, and the types of elemental composition databases most reliable for searching are discussed. Methodology/Principal Findings The FDR can be determined from one measured value (i.e., the hit rate for search queries) and four parameters determined by Monte Carlo simulation. The results indicate that relatively high FDR values (30–50%) were obtained when searching time-of-flight (TOF)/MS data using the KNApSAcK and KEGG databases. In addition, searches against large all-in-one databases (e.g., PubChem) always produced unacceptable results (FDR >70%). The estimated FDRs suggest that the quality of search results can be improved not only by performing more accurate mass analysis but also by modifying the properties of the compound database. A theoretical analysis indicates that FDR could be improved by using compound database with smaller but higher completeness entries. Conclusions/Significance High accuracy mass analysis, such as Fourier transform (FT)-MS, is needed for reliable annotation (FDR metabolome data. PMID:19847304

  3. Rfam: annotating families of non-coding RNA sequences.

    Science.gov (United States)

    Daub, Jennifer; Eberhardt, Ruth Y; Tate, John G; Burge, Sarah W

    2015-01-01

    The primary task of the Rfam database is to collate experimentally validated noncoding RNA (ncRNA) sequences from the published literature and facilitate the prediction and annotation of new homologues in novel nucleotide sequences. We group homologous ncRNA sequences into "families" and related families are further grouped into "clans." We collate and manually curate data cross-references for these families from other databases and external resources. Our Web site offers researchers a simple interface to Rfam and provides tools with which to annotate their own sequences using our covariance models (CMs), through our tools for searching, browsing, and downloading information on Rfam families. In this chapter, we will work through examples of annotating a query sequence, collating family information, and searching for data.

  4. Chemical annotation of small and peptide-like molecules at the Protein Data Bank

    Science.gov (United States)

    Young, Jasmine Y.; Feng, Zukang; Dimitropoulos, Dimitris; Sala, Raul; Westbrook, John; Zhuravleva, Marina; Shao, Chenghua; Quesada, Martha; Peisach, Ezra; Berman, Helen M.

    2013-01-01

    Over the past decade, the number of polymers and their complexes with small molecules in the Protein Data Bank archive (PDB) has continued to increase significantly. To support scientific advancements and ensure the best quality and completeness of the data files over the next 10 years and beyond, the Worldwide PDB partnership that manages the PDB archive is developing a new deposition and annotation system. This system focuses on efficient data capture across all supported experimental methods. The new deposition and annotation system is composed of four major modules that together support all of the processing requirements for a PDB entry. In this article, we describe one such module called the Chemical Component Annotation Tool. This tool uses information from both the Chemical Component Dictionary and Biologically Interesting molecule Reference Dictionary to aid in annotation. Benchmark studies have shown that the Chemical Component Annotation Tool provides significant improvements in processing efficiency and data quality. Database URL: http://wwpdb.org PMID:24291661

  5. Improved Genome Assembly and Annotation for the Rock Pigeon (Columba livia).

    Science.gov (United States)

    Holt, Carson; Campbell, Michael; Keays, David A; Edelman, Nathaniel; Kapusta, Aurélie; Maclary, Emily; T Domyan, Eric; Suh, Alexander; Warren, Wesley C; Yandell, Mark; Gilbert, M Thomas P; Shapiro, Michael D

    2018-05-04

    The domestic rock pigeon ( Columba livia ) is among the most widely distributed and phenotypically diverse avian species. C. livia is broadly studied in ecology, genetics, physiology, behavior, and evolutionary biology, and has recently emerged as a model for understanding the molecular basis of anatomical diversity, the magnetic sense, and other key aspects of avian biology. Here we report an update to the C. livia genome reference assembly and gene annotation dataset. Greatly increased scaffold lengths in the updated reference assembly, along with an updated annotation set, provide improved tools for evolutionary and functional genetic studies of the pigeon, and for comparative avian genomics in general. Copyright © 2018 Holt et al.

  6. Ontological interpretation of biomedical database content.

    Science.gov (United States)

    Santana da Silva, Filipe; Jansen, Ludger; Freitas, Fred; Schulz, Stefan

    2017-06-26

    Biological databases store data about laboratory experiments, together with semantic annotations, in order to support data aggregation and retrieval. The exact meaning of such annotations in the context of a database record is often ambiguous. We address this problem by grounding implicit and explicit database content in a formal-ontological framework. By using a typical extract from the databases UniProt and Ensembl, annotated with content from GO, PR, ChEBI and NCBI Taxonomy, we created four ontological models (in OWL), which generate explicit, distinct interpretations under the BioTopLite2 (BTL2) upper-level ontology. The first three models interpret database entries as individuals (IND), defined classes (SUBC), and classes with dispositions (DISP), respectively; the fourth model (HYBR) is a combination of SUBC and DISP. For the evaluation of these four models, we consider (i) database content retrieval, using ontologies as query vocabulary; (ii) information completeness; and, (iii) DL complexity and decidability. The models were tested under these criteria against four competency questions (CQs). IND does not raise any ontological claim, besides asserting the existence of sample individuals and relations among them. Modelling patterns have to be created for each type of annotation referent. SUBC is interpreted regarding maximally fine-grained defined subclasses under the classes referred to by the data. DISP attempts to extract truly ontological statements from the database records, claiming the existence of dispositions. HYBR is a hybrid of SUBC and DISP and is more parsimonious regarding expressiveness and query answering complexity. For each of the four models, the four CQs were submitted as DL queries. This shows the ability to retrieve individuals with IND, and classes in SUBC and HYBR. DISP does not retrieve anything because the axioms with disposition are embedded in General Class Inclusion (GCI) statements. Ambiguity of biological database content is

  7. WormBase: Annotating many nematode genomes.

    Science.gov (United States)

    Howe, Kevin; Davis, Paul; Paulini, Michael; Tuli, Mary Ann; Williams, Gary; Yook, Karen; Durbin, Richard; Kersey, Paul; Sternberg, Paul W

    2012-01-01

    WormBase (www.wormbase.org) has been serving the scientific community for over 11 years as the central repository for genomic and genetic information for the soil nematode Caenorhabditis elegans. The resource has evolved from its beginnings as a database housing the genomic sequence and genetic and physical maps of a single species, and now represents the breadth and diversity of nematode research, currently serving genome sequence and annotation for around 20 nematodes. In this article, we focus on WormBase's role of genome sequence annotation, describing how we annotate and integrate data from a growing collection of nematode species and strains. We also review our approaches to sequence curation, and discuss the impact on annotation quality of large functional genomics projects such as modENCODE.

  8. Improved methods and resources for paramecium genomics: transcription units, gene annotation and gene expression.

    Science.gov (United States)

    Arnaiz, Olivier; Van Dijk, Erwin; Bétermier, Mireille; Lhuillier-Akakpo, Maoussi; de Vanssay, Augustin; Duharcourt, Sandra; Sallet, Erika; Gouzy, Jérôme; Sperling, Linda

    2017-06-26

    The 15 sibling species of the Paramecium aurelia cryptic species complex emerged after a whole genome duplication that occurred tens of millions of years ago. Given extensive knowledge of the genetics and epigenetics of Paramecium acquired over the last century, this species complex offers a uniquely powerful system to investigate the consequences of whole genome duplication in a unicellular eukaryote as well as the genetic and epigenetic mechanisms that drive speciation. High quality Paramecium gene models are important for research using this system. The major aim of the work reported here was to build an improved gene annotation pipeline for the Paramecium lineage. We generated oriented RNA-Seq transcriptome data across the sexual process of autogamy for the model species Paramecium tetraurelia. We determined, for the first time in a ciliate, candidate P. tetraurelia transcription start sites using an adapted Cap-Seq protocol. We developed TrUC, multi-threaded Perl software that in conjunction with TopHat mapping of RNA-Seq data to a reference genome, predicts transcription units for the annotation pipeline. We used EuGene software to combine annotation evidence. The high quality gene structural annotations obtained for P. tetraurelia were used as evidence to improve published annotations for 3 other Paramecium species. The RNA-Seq data were also used for differential gene expression analysis, providing a gene expression atlas that is more sensitive than the previously established microarray resource. We have developed a gene annotation pipeline tailored for the compact genomes and tiny introns of Paramecium species. A novel component of this pipeline, TrUC, predicts transcription units using Cap-Seq and oriented RNA-Seq data. TrUC could prove useful beyond Paramecium, especially in the case of high gene density. Accurate predictions of 3' and 5' UTR will be particularly valuable for studies of gene expression (e.g. nucleosome positioning, identification of cis

  9. footprintDB: a database of transcription factors with annotated cis elements and binding interfaces.

    Science.gov (United States)

    Sebastian, Alvaro; Contreras-Moreira, Bruno

    2014-01-15

    Traditional and high-throughput techniques for determining transcription factor (TF) binding specificities are generating large volumes of data of uneven quality, which are scattered across individual databases. FootprintDB integrates some of the most comprehensive freely available libraries of curated DNA binding sites and systematically annotates the binding interfaces of the corresponding TFs. The first release contains 2422 unique TF sequences, 10 112 DNA binding sites and 3662 DNA motifs. A survey of the included data sources, organisms and TF families was performed together with proprietary database TRANSFAC, finding that footprintDB has a similar coverage of multicellular organisms, while also containing bacterial regulatory data. A search engine has been designed that drives the prediction of DNA motifs for input TFs, or conversely of TF sequences that might recognize input regulatory sequences, by comparison with database entries. Such predictions can also be extended to a single proteome chosen by the user, and results are ranked in terms of interface similarity. Benchmark experiments with bacterial, plant and human data were performed to measure the predictive power of footprintDB searches, which were able to correctly recover 10, 55 and 90% of the tested sequences, respectively. Correctly predicted TFs had a higher interface similarity than the average, confirming its diagnostic value. Web site implemented in PHP,Perl, MySQL and Apache. Freely available from http://floresta.eead.csic.es/footprintdb.

  10. Computer systems for annotation of single molecule fragments

    Science.gov (United States)

    Schwartz, David Charles; Severin, Jessica

    2016-07-19

    There are provided computer systems for visualizing and annotating single molecule images. Annotation systems in accordance with this disclosure allow a user to mark and annotate single molecules of interest and their restriction enzyme cut sites thereby determining the restriction fragments of single nucleic acid molecules. The markings and annotations may be automatically generated by the system in certain embodiments and they may be overlaid translucently onto the single molecule images. An image caching system may be implemented in the computer annotation systems to reduce image processing time. The annotation systems include one or more connectors connecting to one or more databases capable of storing single molecule data as well as other biomedical data. Such diverse array of data can be retrieved and used to validate the markings and annotations. The annotation systems may be implemented and deployed over a computer network. They may be ergonomically optimized to facilitate user interactions.

  11. An annotated corpus with nanomedicine and pharmacokinetic parameters.

    Science.gov (United States)

    Lewinski, Nastassja A; Jimenez, Ivan; McInnes, Bridget T

    2017-01-01

    A vast amount of data on nanomedicines is being generated and published, and natural language processing (NLP) approaches can automate the extraction of unstructured text-based data. Annotated corpora are a key resource for NLP and information extraction methods which employ machine learning. Although corpora are available for pharmaceuticals, resources for nanomedicines and nanotechnology are still limited. To foster nanotechnology text mining (NanoNLP) efforts, we have constructed a corpus of annotated drug product inserts taken from the US Food and Drug Administration's Drugs@FDA online database. In this work, we present the development of the Engineered Nanomedicine Database corpus to support the evaluation of nanomedicine entity extraction. The data were manually annotated for 21 entity mentions consisting of nanomedicine physicochemical characterization, exposure, and biologic response information of 41 Food and Drug Administration-approved nanomedicines. We evaluate the reliability of the manual annotations and demonstrate the use of the corpus by evaluating two state-of-the-art named entity extraction systems, OpenNLP and Stanford NER. The annotated corpus is available open source and, based on these results, guidelines and suggestions for future development of additional nanomedicine corpora are provided.

  12. Mycobacteriophage genome database.

    Science.gov (United States)

    Joseph, Jerrine; Rajendran, Vasanthi; Hassan, Sameer; Kumar, Vanaja

    2011-01-01

    Mycobacteriophage genome database (MGDB) is an exclusive repository of the 64 completely sequenced mycobacteriophages with annotated information. It is a comprehensive compilation of the various gene parameters captured from several databases pooled together to empower mycobacteriophage researchers. The MGDB (Version No.1.0) comprises of 6086 genes from 64 mycobacteriophages classified into 72 families based on ACLAME database. Manual curation was aided by information available from public databases which was enriched further by analysis. Its web interface allows browsing as well as querying the classification. The main objective is to collect and organize the complexity inherent to mycobacteriophage protein classification in a rational way. The other objective is to browse the existing and new genomes and describe their functional annotation. The database is available for free at http://mpgdb.ibioinformatics.org/mpgdb.php.

  13. Evaluating Functional Annotations of Enzymes Using the Gene Ontology.

    Science.gov (United States)

    Holliday, Gemma L; Davidson, Rebecca; Akiva, Eyal; Babbitt, Patricia C

    2017-01-01

    The Gene Ontology (GO) (Ashburner et al., Nat Genet 25(1):25-29, 2000) is a powerful tool in the informatics arsenal of methods for evaluating annotations in a protein dataset. From identifying the nearest well annotated homologue of a protein of interest to predicting where misannotation has occurred to knowing how confident you can be in the annotations assigned to those proteins is critical. In this chapter we explore what makes an enzyme unique and how we can use GO to infer aspects of protein function based on sequence similarity. These can range from identification of misannotation or other errors in a predicted function to accurate function prediction for an enzyme of entirely unknown function. Although GO annotation applies to any gene products, we focus here a describing our approach for hierarchical classification of enzymes in the Structure-Function Linkage Database (SFLD) (Akiva et al., Nucleic Acids Res 42(Database issue):D521-530, 2014) as a guide for informed utilisation of annotation transfer based on GO terms.

  14. WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research.

    Science.gov (United States)

    Slenter, Denise N; Kutmon, Martina; Hanspers, Kristina; Riutta, Anders; Windsor, Jacob; Nunes, Nuno; Mélius, Jonathan; Cirillo, Elisa; Coort, Susan L; Digles, Daniela; Ehrhart, Friederike; Giesbertz, Pieter; Kalafati, Marianthi; Martens, Marvin; Miller, Ryan; Nishida, Kozo; Rieswijk, Linda; Waagmeester, Andra; Eijssen, Lars M T; Evelo, Chris T; Pico, Alexander R; Willighagen, Egon L

    2018-01-04

    WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  15. EST-PAC a web package for EST annotation and protein sequence prediction

    Directory of Open Access Journals (Sweden)

    Strahm Yvan

    2006-10-01

    Full Text Available Abstract With the decreasing cost of DNA sequencing technology and the vast diversity of biological resources, researchers increasingly face the basic challenge of annotating a larger number of expressed sequences tags (EST from a variety of species. This typically consists of a series of repetitive tasks, which should be automated and easy to use. The results of these annotation tasks need to be stored and organized in a consistent way. All these operations should be self-installing, platform independent, easy to customize and amenable to using distributed bioinformatics resources available on the Internet. In order to address these issues, we present EST-PAC a web oriented multi-platform software package for expressed sequences tag (EST annotation. EST-PAC provides a solution for the administration of EST and protein sequence annotations accessible through a web interface. Three aspects of EST annotation are automated: 1 searching local or remote biological databases for sequence similarities using Blast services, 2 predicting protein coding sequence from EST data and, 3 annotating predicted protein sequences with functional domain predictions. In practice, EST-PAC integrates the BLASTALL suite, EST-Scan2 and HMMER in a relational database system accessible through a simple web interface. EST-PAC also takes advantage of the relational database to allow consistent storage, powerful queries of results and, management of the annotation process. The system allows users to customize annotation strategies and provides an open-source data-management environment for research and education in bioinformatics.

  16. Database Description - RMOS | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available base Description General information of database Database name RMOS Alternative nam...arch Unit Shoshi Kikuchi E-mail : Database classification Plant databases - Rice Microarray Data and other Gene Expression Database...s Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database description The Ric...19&lang=en Whole data download - Referenced database Rice Expression Database (RED) Rice full-length cDNA Database... (KOME) Rice Genome Integrated Map Database (INE) Rice Mutant Panel Database (Tos17) Rice Genome Annotation Database

  17. Transcriptome analysis of the desert locust central nervous system: production and annotation of a Schistocerca gregaria EST database.

    Science.gov (United States)

    Badisco, Liesbeth; Huybrechts, Jurgen; Simonet, Gert; Verlinden, Heleen; Marchal, Elisabeth; Huybrechts, Roger; Schoofs, Liliane; De Loof, Arnold; Vanden Broeck, Jozef

    2011-03-21

    The desert locust (Schistocerca gregaria) displays a fascinating type of phenotypic plasticity, designated as 'phase polyphenism'. Depending on environmental conditions, one genome can be translated into two highly divergent phenotypes, termed the solitarious and gregarious (swarming) phase. Although many of the underlying molecular events remain elusive, the central nervous system (CNS) is expected to play a crucial role in the phase transition process. Locusts have also proven to be interesting model organisms in a physiological and neurobiological research context. However, molecular studies in locusts are hampered by the fact that genome/transcriptome sequence information available for this branch of insects is still limited. We have generated 34,672 raw expressed sequence tags (EST) from the CNS of desert locusts in both phases. These ESTs were assembled in 12,709 unique transcript sequences and nearly 4,000 sequences were functionally annotated. Moreover, the obtained S. gregaria EST information is highly complementary to the existing orthopteran transcriptomic data. Since many novel transcripts encode neuronal signaling and signal transduction components, this paper includes an overview of these sequences. Furthermore, several transcripts being differentially represented in solitarious and gregarious locusts were retrieved from this EST database. The findings highlight the involvement of the CNS in the phase transition process and indicate that this novel annotated database may also add to the emerging knowledge of concomitant neuronal signaling and neuroplasticity events. In summary, we met the need for novel sequence data from desert locust CNS. To our knowledge, we hereby also present the first insect EST database that is derived from the complete CNS. The obtained S. gregaria EST data constitute an important new source of information that will be instrumental in further unraveling the molecular principles of phase polyphenism, in further establishing

  18. Transcriptome analysis of the desert locust central nervous system: production and annotation of a Schistocerca gregaria EST database.

    Directory of Open Access Journals (Sweden)

    Liesbeth Badisco

    Full Text Available BACKGROUND: The desert locust (Schistocerca gregaria displays a fascinating type of phenotypic plasticity, designated as 'phase polyphenism'. Depending on environmental conditions, one genome can be translated into two highly divergent phenotypes, termed the solitarious and gregarious (swarming phase. Although many of the underlying molecular events remain elusive, the central nervous system (CNS is expected to play a crucial role in the phase transition process. Locusts have also proven to be interesting model organisms in a physiological and neurobiological research context. However, molecular studies in locusts are hampered by the fact that genome/transcriptome sequence information available for this branch of insects is still limited. METHODOLOGY: We have generated 34,672 raw expressed sequence tags (EST from the CNS of desert locusts in both phases. These ESTs were assembled in 12,709 unique transcript sequences and nearly 4,000 sequences were functionally annotated. Moreover, the obtained S. gregaria EST information is highly complementary to the existing orthopteran transcriptomic data. Since many novel transcripts encode neuronal signaling and signal transduction components, this paper includes an overview of these sequences. Furthermore, several transcripts being differentially represented in solitarious and gregarious locusts were retrieved from this EST database. The findings highlight the involvement of the CNS in the phase transition process and indicate that this novel annotated database may also add to the emerging knowledge of concomitant neuronal signaling and neuroplasticity events. CONCLUSIONS: In summary, we met the need for novel sequence data from desert locust CNS. To our knowledge, we hereby also present the first insect EST database that is derived from the complete CNS. The obtained S. gregaria EST data constitute an important new source of information that will be instrumental in further unraveling the molecular

  19. Pipeline to upgrade the genome annotations

    Directory of Open Access Journals (Sweden)

    Lijin K. Gopi

    2017-12-01

    Full Text Available Current era of functional genomics is enriched with good quality draft genomes and annotations for many thousands of species and varieties with the support of the advancements in the next generation sequencing technologies (NGS. Around 25,250 genomes, of the organisms from various kingdoms, are submitted in the NCBI genome resource till date. Each of these genomes was annotated using various tools and knowledge-bases that were available during the period of the annotation. It is obvious that these annotations will be improved if the same genome is annotated using improved tools and knowledge-bases. Here we present a new genome annotation pipeline, strengthened with various tools and knowledge-bases that are capable of producing better quality annotations from the consensus of the predictions from different tools. This resource also perform various additional annotations, apart from the usual gene predictions and functional annotations, which involve SSRs, novel repeats, paralogs, proteins with transmembrane helices, signal peptides etc. This new annotation resource is trained to evaluate and integrate all the predictions together to resolve the overlaps and ambiguities of the boundaries. One of the important highlights of this resource is the capability of predicting the phylogenetic relations of the repeats using the evolutionary trace analysis and orthologous gene clusters. We also present a case study, of the pipeline, in which we upgrade the genome annotation of Nelumbo nucifera (sacred lotus. It is demonstrated that this resource is capable of producing an improved annotation for a better understanding of the biology of various organisms.

  20. Current and future trends in marine image annotation software

    Science.gov (United States)

    Gomes-Pereira, Jose Nuno; Auger, Vincent; Beisiegel, Kolja; Benjamin, Robert; Bergmann, Melanie; Bowden, David; Buhl-Mortensen, Pal; De Leo, Fabio C.; Dionísio, Gisela; Durden, Jennifer M.; Edwards, Luke; Friedman, Ariell; Greinert, Jens; Jacobsen-Stout, Nancy; Lerner, Steve; Leslie, Murray; Nattkemper, Tim W.; Sameoto, Jessica A.; Schoening, Timm; Schouten, Ronald; Seager, James; Singh, Hanumant; Soubigou, Olivier; Tojeira, Inês; van den Beld, Inge; Dias, Frederico; Tempera, Fernando; Santos, Ricardo S.

    2016-12-01

    Given the need to describe, analyze and index large quantities of marine imagery data for exploration and monitoring activities, a range of specialized image annotation tools have been developed worldwide. Image annotation - the process of transposing objects or events represented in a video or still image to the semantic level, may involve human interactions and computer-assisted solutions. Marine image annotation software (MIAS) have enabled over 500 publications to date. We review the functioning, application trends and developments, by comparing general and advanced features of 23 different tools utilized in underwater image analysis. MIAS requiring human input are basically a graphical user interface, with a video player or image browser that recognizes a specific time code or image code, allowing to log events in a time-stamped (and/or geo-referenced) manner. MIAS differ from similar software by the capability of integrating data associated to video collection, the most simple being the position coordinates of the video recording platform. MIAS have three main characteristics: annotating events in real time, posteriorly to annotation and interact with a database. These range from simple annotation interfaces, to full onboard data management systems, with a variety of toolboxes. Advanced packages allow to input and display data from multiple sensors or multiple annotators via intranet or internet. Posterior human-mediated annotation often include tools for data display and image analysis, e.g. length, area, image segmentation, point count; and in a few cases the possibility of browsing and editing previous dive logs or to analyze the annotations. The interaction with a database allows the automatic integration of annotations from different surveys, repeated annotation and collaborative annotation of shared datasets, browsing and querying of data. Progress in the field of automated annotation is mostly in post processing, for stable platforms or still images

  1. Annotation of novel neuropeptide precursors in the migratory locust based on transcript screening of a public EST database and mass spectrometry

    Directory of Open Access Journals (Sweden)

    De Loof Arnold

    2006-08-01

    Full Text Available Abstract Background For holometabolous insects there has been an explosion of proteomic and peptidomic information thanks to large genome sequencing projects. Heterometabolous insects, although comprising many important species, have been far less studied. The migratory locust Locusta migratoria, a heterometabolous insect, is one of the most infamous agricultural pests. They undergo a well-known and profound phase transition from the relatively harmless solitary form to a ferocious gregarious form. The underlying regulatory mechanisms of this phase transition are not fully understood, but it is undoubtedly that neuropeptides are involved. However, neuropeptide research in locusts is hampered by the absence of genomic information. Results Recently, EST (Expressed Sequence Tag databases from Locusta migratoria were constructed. Using bioinformatical tools, we searched these EST databases specifically for neuropeptide precursors. Based on known locust neuropeptide sequences, we confirmed the sequence of several previously identified neuropeptide precursors (i.e. pacifastin-related peptides, which consolidated our method. In addition, we found two novel neuroparsin precursors and annotated the hitherto unknown tachykinin precursor. Besides one of the known tachykinin peptides, this EST contained an additional tachykinin-like sequence. Using neuropeptide precursors from Drosophila melanogaster as a query, we succeeded in annotating the Locusta neuropeptide F, allatostatin-C and ecdysis-triggering hormone precursor, which until now had not been identified in locusts or in any other heterometabolous insect. For the tachykinin precursor, the ecdysis-triggering hormone precursor and the allatostatin-C precursor, translation of the predicted neuropeptides in neural tissues was confirmed with mass spectrometric techniques. Conclusion In this study we describe the annotation of 6 novel neuropeptide precursors and the neuropeptides they encode from the

  2. Gene annotation from scientific literature using mappings between keyword systems.

    Science.gov (United States)

    Pérez, Antonio J; Perez-Iratxeta, Carolina; Bork, Peer; Thode, Guillermo; Andrade, Miguel A

    2004-09-01

    The description of genes in databases by keywords helps the non-specialist to quickly grasp the properties of a gene and increases the efficiency of computational tools that are applied to gene data (e.g. searching a gene database for sequences related to a particular biological process). However, the association of keywords to genes or protein sequences is a difficult process that ultimately implies examination of the literature related to a gene. To support this task, we present a procedure to derive keywords from the set of scientific abstracts related to a gene. Our system is based on the automated extraction of mappings between related terms from different databases using a model of fuzzy associations that can be applied with all generality to any pair of linked databases. We tested the system by annotating genes of the SWISS-PROT database with keywords derived from the abstracts linked to their entries (stored in the MEDLINE database of scientific references). The performance of the annotation procedure was much better for SWISS-PROT keywords (recall of 47%, precision of 68%) than for Gene Ontology terms (recall of 8%, precision of 67%). The algorithm can be publicly accessed and used for the annotation of sequences through a web server at http://www.bork.embl.de/kat

  3. Database constraints applied to metabolic pathway reconstruction tools.

    Science.gov (United States)

    Vilaplana, Jordi; Solsona, Francesc; Teixido, Ivan; Usié, Anabel; Karathia, Hiren; Alves, Rui; Mateo, Jordi

    2014-01-01

    Our group developed two biological applications, Biblio-MetReS and Homol-MetReS, accessing the same database of organisms with annotated genes. Biblio-MetReS is a data-mining application that facilitates the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (re)annotation of proteomes, to properly identify both the individual proteins involved in the process(es) of interest and their function. It also enables the sets of proteins involved in the process(es) in different organisms to be compared directly. The efficiency of these biological applications is directly related to the design of the shared database. We classified and analyzed the different kinds of access to the database. Based on this study, we tried to adjust and tune the configurable parameters of the database server to reach the best performance of the communication data link to/from the database system. Different database technologies were analyzed. We started the study with a public relational SQL database, MySQL. Then, the same database was implemented by a MapReduce-based database named HBase. The results indicated that the standard configuration of MySQL gives an acceptable performance for low or medium size databases. Nevertheless, tuning database parameters can greatly improve the performance and lead to very competitive runtimes.

  4. CyanoBase: the cyanobacteria genome database update 2010

    OpenAIRE

    Nakao, Mitsuteru; Okamoto, Shinobu; Kohara, Mitsuyo; Fujishiro, Tsunakazu; Fujisawa, Takatomo; Sato, Shusei; Tabata, Satoshi; Kaneko, Takakazu; Nakamura, Yasukazu

    2009-01-01

    CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in var...

  5. AutoFACT: An Automatic Functional Annotation and Classification Tool

    Directory of Open Access Journals (Sweden)

    Lang B Franz

    2005-06-01

    Full Text Available Abstract Background Assignment of function to new molecular sequence data is an essential step in genomics projects. The usual process involves similarity searches of a given sequence against one or more databases, an arduous process for large datasets. Results We present AutoFACT, a fully automated and customizable annotation tool that assigns biologically informative functions to a sequence. Key features of this tool are that it (1 analyzes nucleotide and protein sequence data; (2 determines the most informative functional description by combining multiple BLAST reports from several user-selected databases; (3 assigns putative metabolic pathways, functional classes, enzyme classes, GeneOntology terms and locus names; and (4 generates output in HTML, text and GFF formats for the user's convenience. We have compared AutoFACT to four well-established annotation pipelines. The error rate of functional annotation is estimated to be only between 1–2%. Comparison of AutoFACT to the traditional top-BLAST-hit annotation method shows that our procedure increases the number of functionally informative annotations by approximately 50%. Conclusion AutoFACT will serve as a useful annotation tool for smaller sequencing groups lacking dedicated bioinformatics staff. It is implemented in PERL and runs on LINUX/UNIX platforms. AutoFACT is available at http://megasun.bch.umontreal.ca/Software/AutoFACT.htm.

  6. CGKB: an annotation knowledge base for cowpea (Vigna unguiculata L. methylation filtered genomic genespace sequences

    Directory of Open Access Journals (Sweden)

    Spraggins Thomas A

    2007-04-01

    Full Text Available Abstract Background Cowpea [Vigna unguiculata (L. Walp.] is one of the most important food and forage legumes in the semi-arid tropics because of its ability to tolerate drought and grow on poor soils. It is cultivated mostly by poor farmers in developing countries, with 80% of production taking place in the dry savannah of tropical West and Central Africa. Cowpea is largely an underexploited crop with relatively little genomic information available for use in applied plant breeding. The goal of the Cowpea Genomics Initiative (CGI, funded by the Kirkhouse Trust, a UK-based charitable organization, is to leverage modern molecular genetic tools for gene discovery and cowpea improvement. One aspect of the initiative is the sequencing of the gene-rich region of the cowpea genome (termed the genespace recovered using methylation filtration technology and providing annotation and analysis of the sequence data. Description CGKB, Cowpea Genespace/Genomics Knowledge Base, is an annotation knowledge base developed under the CGI. The database is based on information derived from 298,848 cowpea genespace sequences (GSS isolated by methylation filtering of genomic DNA. The CGKB consists of three knowledge bases: GSS annotation and comparative genomics knowledge base, GSS enzyme and metabolic pathway knowledge base, and GSS simple sequence repeats (SSRs knowledge base for molecular marker discovery. A homology-based approach was applied for annotations of the GSS, mainly using BLASTX against four public FASTA formatted protein databases (NCBI GenBank Proteins, UniProtKB-Swiss-Prot, UniprotKB-PIR (Protein Information Resource, and UniProtKB-TrEMBL. Comparative genome analysis was done by BLASTX searches of the cowpea GSS against four plant proteomes from Arabidopsis thaliana, Oryza sativa, Medicago truncatula, and Populus trichocarpa. The possible exons and introns on each cowpea GSS were predicted using the HMM-based Genscan gene predication program and the

  7. tagtog: interactive and text-mining-assisted annotation of gene mentions in PLOS full-text articles.

    Science.gov (United States)

    Cejuela, Juan Miguel; McQuilton, Peter; Ponting, Laura; Marygold, Steven J; Stefancsik, Raymund; Millburn, Gillian H; Rost, Burkhard

    2014-01-01

    The breadth and depth of biomedical literature are increasing year upon year. To keep abreast of these increases, FlyBase, a database for Drosophila genomic and genetic information, is constantly exploring new ways to mine the published literature to increase the efficiency and accuracy of manual curation and to automate some aspects, such as triaging and entity extraction. Toward this end, we present the 'tagtog' system, a web-based annotation framework that can be used to mark up biological entities (such as genes) and concepts (such as Gene Ontology terms) in full-text articles. tagtog leverages manual user annotation in combination with automatic machine-learned annotation to provide accurate identification of gene symbols and gene names. As part of the BioCreative IV Interactive Annotation Task, FlyBase has used tagtog to identify and extract mentions of Drosophila melanogaster gene symbols and names in full-text biomedical articles from the PLOS stable of journals. We show here the results of three experiments with different sized corpora and assess gene recognition performance and curation speed. We conclude that tagtog-named entity recognition improves with a larger corpus and that tagtog-assisted curation is quicker than manual curation. DATABASE URL: www.tagtog.net, www.flybase.org.

  8. MiMiR: a comprehensive solution for storage, annotation and exchange of microarray data

    Directory of Open Access Journals (Sweden)

    Rahman Fatimah

    2005-11-01

    Full Text Available Abstract Background The generation of large amounts of microarray data presents challenges for data collection, annotation, exchange and analysis. Although there are now widely accepted formats, minimum standards for data content and ontologies for microarray data, only a few groups are using them together to build and populate large-scale databases. Structured environments for data management are crucial for making full use of these data. Description The MiMiR database provides a comprehensive infrastructure for microarray data annotation, storage and exchange and is based on the MAGE format. MiMiR is MIAME-supportive, customised for use with data generated on the Affymetrix platform and includes a tool for data annotation using ontologies. Detailed information on the experiment, methods, reagents and signal intensity data can be captured in a systematic format. Reports screens permit the user to query the database, to view annotation on individual experiments and provide summary statistics. MiMiR has tools for automatic upload of the data from the microarray scanner and export to databases using MAGE-ML. Conclusion MiMiR facilitates microarray data management, annotation and exchange, in line with international guidelines. The database is valuable for underpinning research activities and promotes a systematic approach to data handling. Copies of MiMiR are freely available to academic groups under licence.

  9. A database of annotated promoters of genes associated with common respiratory and related diseases

    KAUST Repository

    Chowdhary, Rajesh

    2012-07-01

    Many genes have been implicated in the pathogenesis of common respiratory and related diseases (RRDs), yet the underlying mechanisms are largely unknown. Differential gene expression patterns in diseased and healthy individuals suggest that RRDs affect or are affected by modified transcription regulation programs. It is thus crucial to characterize implicated genes in terms of transcriptional regulation. For this purpose, we conducted a promoter analysis of genes associated with 11 common RRDs including allergic rhinitis, asthma, bronchiectasis, bronchiolitis, bronchitis, chronic obstructive pulmonary disease, cystic fibrosis, emphysema, eczema, psoriasis, and urticaria, many of which are thought to be genetically related. The objective of the present study was to obtain deeper insight into the transcriptional regulation of these disease-associated genes by annotating their promoter regions with transcription factors (TFs) and TF binding sites (TFBSs). We discovered many TFs that are significantly enriched in the target disease groups including associations that have been documented in the literature. We also identified a number of putative TFs/TFBSs that appear to be novel. The results of our analysis are provided in an online database that is freely accessible to researchers at http://www.respiratorygenomics.com. Promoter-associated TFBS information and related genomic features, such as histone modification sites, microsatellites, CpG islands, and SNPs, are graphically summarized in the database. Users can compare and contrast underlying mechanisms of specific RRDs relative to candidate genes, TFs, gene ontology terms, micro-RNAs, and biological pathways for the conduct of metaanalyses. This database represents a novel, useful resource for RRD researchers. Copyright © 2012 by the American Thoracic Society.

  10. A database of annotated promoters of genes associated with common respiratory and related diseases

    KAUST Repository

    Chowdhary, Rajesh; Tan, Sinlam; Pavesi, Giulio; Jin, Gg; Dong, Difeng; Mathur, Sameer K.; Burkart, Arthur; Narang, Vipin; Glurich, Ingrid E.; Raby, Benjamin A.; Weiss, Scott T.; Limsoon, Wong; Liu, Jun; Bajic, Vladimir B.

    2012-01-01

    Many genes have been implicated in the pathogenesis of common respiratory and related diseases (RRDs), yet the underlying mechanisms are largely unknown. Differential gene expression patterns in diseased and healthy individuals suggest that RRDs affect or are affected by modified transcription regulation programs. It is thus crucial to characterize implicated genes in terms of transcriptional regulation. For this purpose, we conducted a promoter analysis of genes associated with 11 common RRDs including allergic rhinitis, asthma, bronchiectasis, bronchiolitis, bronchitis, chronic obstructive pulmonary disease, cystic fibrosis, emphysema, eczema, psoriasis, and urticaria, many of which are thought to be genetically related. The objective of the present study was to obtain deeper insight into the transcriptional regulation of these disease-associated genes by annotating their promoter regions with transcription factors (TFs) and TF binding sites (TFBSs). We discovered many TFs that are significantly enriched in the target disease groups including associations that have been documented in the literature. We also identified a number of putative TFs/TFBSs that appear to be novel. The results of our analysis are provided in an online database that is freely accessible to researchers at http://www.respiratorygenomics.com. Promoter-associated TFBS information and related genomic features, such as histone modification sites, microsatellites, CpG islands, and SNPs, are graphically summarized in the database. Users can compare and contrast underlying mechanisms of specific RRDs relative to candidate genes, TFs, gene ontology terms, micro-RNAs, and biological pathways for the conduct of metaanalyses. This database represents a novel, useful resource for RRD researchers. Copyright © 2012 by the American Thoracic Society.

  11. PANNZER2: a rapid functional annotation web server.

    Science.gov (United States)

    Törönen, Petri; Medlar, Alan; Holm, Liisa

    2018-05-08

    The unprecedented growth of high-throughput sequencing has led to an ever-widening annotation gap in protein databases. While computational prediction methods are available to make up the shortfall, a majority of public web servers are hindered by practical limitations and poor performance. Here, we introduce PANNZER2 (Protein ANNotation with Z-scoRE), a fast functional annotation web server that provides both Gene Ontology (GO) annotations and free text description predictions. PANNZER2 uses SANSparallel to perform high-performance homology searches, making bulk annotation based on sequence similarity practical. PANNZER2 can output GO annotations from multiple scoring functions, enabling users to see which predictions are robust across predictors. Finally, PANNZER2 predictions scored within the top 10 methods for molecular function and biological process in the CAFA2 NK-full benchmark. The PANNZER2 web server is updated on a monthly schedule and is accessible at http://ekhidna2.biocenter.helsinki.fi/sanspanz/. The source code is available under the GNU Public Licence v3.

  12. A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases

    Directory of Open Access Journals (Sweden)

    Karp Peter D

    2004-06-01

    probability threshold of 0.9 during cross-validation using known reactions in computationally-predicted pathway databases. After applying our method to 513 pathway holes in 333 pathways from three Pathway/Genome databases, we increased the number of complete pathways by 42%. We made putative assignments to 46% of the holes, including annotation of 17 sequences of previously unknown function. Conclusions Our pathway hole filler can be used not only to increase the utility of Pathway/Genome databases to both experimental and computational researchers, but also to improve predictions of protein function.

  13. Reasoning with Annotations of Texts

    OpenAIRE

    Ma , Yue; Lévy , François; Ghimire , Sudeep

    2011-01-01

    International audience; Linguistic and semantic annotations are important features for text-based applications. However, achieving and maintaining a good quality of a set of annotations is known to be a complex task. Many ad hoc approaches have been developed to produce various types of annotations, while comparing those annotations to improve their quality is still rare. In this paper, we propose a framework in which both linguistic and domain information can cooperate to reason with annotat...

  14. CyanoBase: the cyanobacteria genome database update 2010.

    Science.gov (United States)

    Nakao, Mitsuteru; Okamoto, Shinobu; Kohara, Mitsuyo; Fujishiro, Tsunakazu; Fujisawa, Takatomo; Sato, Shusei; Tabata, Satoshi; Kaneko, Takakazu; Nakamura, Yasukazu

    2010-01-01

    CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in various formats with other tools, seamlessly.

  15. HBVRegDB: Annotation, comparison, detection and visualization of regulatory elements in hepatitis B virus sequences

    Directory of Open Access Journals (Sweden)

    Firth Andrew E

    2007-12-01

    Full Text Available Abstract Background The many Hepadnaviridae sequences available have widely varied functional annotation. The genomes are very compact (~3.2 kb but contain multiple layers of functional regulatory elements in addition to coding regions. Key regions are subject to purifying selection, as mutations in these regions will produce non-functional viruses. Results These genomic sequences have been organized into a structured database to facilitate research at the molecular level. HBVRegDB is a comparative genomic analysis tool with an integrated underlying sequence database. The database contains genomic sequence data from representative viruses. In addition to INSDC and RefSeq annotation, HBVRegDB also contains expert and systematically calculated annotations (e.g. promoters and comparative genome analysis results (e.g. blastn, tblastx. It also contains analyses based on curated HBV alignments. Information about conserved regions – including primary conservation (e.g. CDS-Plotcon and RNA secondary structure predictions (e.g. Alidot – is integrated into the database. A large amount of data is graphically presented using the GBrowse (Generic Genome Browser adapted for analysis of viral genomes. Flexible query access is provided based on any annotated genomic feature. Novel regulatory motifs can be found by analysing the annotated sequences. Conclusion HBVRegDB serves as a knowledge database and as a comparative genomic analysis tool for molecular biologists investigating HBV. It is publicly available and complementary to other viral and HBV focused datasets and tools http://hbvregdb.otago.ac.nz. The availability of multiple and highly annotated sequences of viral genomes in one database combined with comparative analysis tools facilitates detection of novel genomic elements.

  16. MIPS: analysis and annotation of proteins from whole genomes.

    Science.gov (United States)

    Mewes, H W; Amid, C; Arnold, R; Frishman, D; Güldener, U; Mannhaupt, G; Münsterkötter, M; Pagel, P; Strack, N; Stümpflen, V; Warfsmann, J; Ruepp, A

    2004-01-01

    The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein-protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).

  17. The surplus value of semantic annotations

    NARCIS (Netherlands)

    Marx, M.

    2010-01-01

    We compare the costs of semantic annotation of textual documents to its benefits for information processing tasks. Semantic annotation can improve the performance of retrieval tasks and facilitates an improved search experience through faceted search, focused retrieval, better document summaries,

  18. DSSTOX STRUCTURE-SEARCHABLE PUBLIC TOXICITY DATABASE NETWORK: CURRENT PROGRESS AND NEW INITIATIVES TO IMPROVE CHEMO-BIOINFORMATICS CAPABILITIES

    Science.gov (United States)

    The EPA DSSTox website (http://www/epa.gov/nheerl/dsstox) publishes standardized, structure-annotated toxicity databases, covering a broad range of toxicity disciplines. Each DSSTox database features documentation written in collaboration with the source authors and toxicity expe...

  19. Expressed Peptide Tags: An additional layer of data for genome annotation

    Energy Technology Data Exchange (ETDEWEB)

    Savidor, Alon [ORNL; Donahoo, Ryan S [ORNL; Hurtado-Gonzales, Oscar [University of Tennessee, Knoxville (UTK); Verberkmoes, Nathan C [ORNL; Shah, Manesh B [ORNL; Lamour, Kurt H [ORNL; McDonald, W Hayes [ORNL

    2006-01-01

    While genome sequencing is becoming ever more routine, genome annotation remains a challenging process. Identification of the coding sequences within the genomic milieu presents a tremendous challenge, especially for eukaryotes with their complex gene architectures. Here we present a method to assist the annotation process through the use of proteomic data and bioinformatics. Mass spectra of digested protein preparations of the organism of interest were acquired and searched against a protein database created by a six frame translation of the genome. The identified peptides were mapped back to the genome, compared to the current annotation, and then categorized as supporting or extending the current genome annotation. We named the classified peptides Expressed Peptide Tags (EPTs). The well annotated bacterium Rhodopseudomonas palustris was used as a control for the method and showed high degree of correlation between EPT mapping and the current annotation, with 86% of the EPTs confirming existing gene calls and less than 1% of the EPTs expanding on the current annotation. The eukaryotic plant pathogens Phytophthora ramorum and Phytophthora sojae, whose genomes have been recently sequenced and are much less well annotated, were also subjected to this method. A series of algorithmic steps were taken to increase the confidence of EPT identification for these organisms, including generation of smaller sub-databases to be searched against, and definition of EPT criteria that accommodates the more complex eukaryotic gene architecture. As expected, the analysis of the Phytophthora species showed less correlation between EPT mapping and their current annotation. While ~77% of Phytophthora EPTs supported the current annotation, a portion of them (7.2% and 12.6% for P. ramorum and P. sojae, respectively) suggested modification to current gene calls or identified novel genes that were missed by the current genome annotation of these organisms.

  20. An annotated corpus with nanomedicine and pharmacokinetic parameters

    Directory of Open Access Journals (Sweden)

    Lewinski NA

    2017-10-01

    Full Text Available Nastassja A Lewinski,1 Ivan Jimenez,1 Bridget T McInnes2 1Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, 2Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA Abstract: A vast amount of data on nanomedicines is being generated and published, and natural language processing (NLP approaches can automate the extraction of unstructured text-based data. Annotated corpora are a key resource for NLP and information extraction methods which employ machine learning. Although corpora are available for pharmaceuticals, resources for nanomedicines and nanotechnology are still limited. To foster nanotechnology text mining (NanoNLP efforts, we have constructed a corpus of annotated drug product inserts taken from the US Food and Drug Administration’s Drugs@FDA online database. In this work, we present the development of the Engineered Nanomedicine Database corpus to support the evaluation of nanomedicine entity extraction. The data were manually annotated for 21 entity mentions consisting of nanomedicine physicochemical characterization, exposure, and biologic response information of 41 Food and Drug Administration-approved nanomedicines. We evaluate the reliability of the manual annotations and demonstrate the use of the corpus by evaluating two state-of-the-art named entity extraction systems, OpenNLP and Stanford NER. The annotated corpus is available open source and, based on these results, guidelines and suggestions for future development of additional nanomedicine corpora are provided. Keywords: nanotechnology, informatics, natural language processing, text mining, corpora

  1. Managing and Querying Image Annotation and Markup in XML.

    Science.gov (United States)

    Wang, Fusheng; Pan, Tony; Sharma, Ashish; Saltz, Joel

    2010-01-01

    Proprietary approaches for representing annotations and image markup are serious barriers for researchers to share image data and knowledge. The Annotation and Image Markup (AIM) project is developing a standard based information model for image annotation and markup in health care and clinical trial environments. The complex hierarchical structures of AIM data model pose new challenges for managing such data in terms of performance and support of complex queries. In this paper, we present our work on managing AIM data through a native XML approach, and supporting complex image and annotation queries through native extension of XQuery language. Through integration with xService, AIM databases can now be conveniently shared through caGrid.

  2. Managing and Querying Image Annotation and Markup in XML

    Science.gov (United States)

    Wang, Fusheng; Pan, Tony; Sharma, Ashish; Saltz, Joel

    2010-01-01

    Proprietary approaches for representing annotations and image markup are serious barriers for researchers to share image data and knowledge. The Annotation and Image Markup (AIM) project is developing a standard based information model for image annotation and markup in health care and clinical trial environments. The complex hierarchical structures of AIM data model pose new challenges for managing such data in terms of performance and support of complex queries. In this paper, we present our work on managing AIM data through a native XML approach, and supporting complex image and annotation queries through native extension of XQuery language. Through integration with xService, AIM databases can now be conveniently shared through caGrid. PMID:21218167

  3. Concept annotation in the CRAFT corpus.

    Science.gov (United States)

    Bada, Michael; Eckert, Miriam; Evans, Donald; Garcia, Kristin; Shipley, Krista; Sitnikov, Dmitry; Baumgartner, William A; Cohen, K Bretonnel; Verspoor, Karin; Blake, Judith A; Hunter, Lawrence E

    2012-07-09

    Manually annotated corpora are critical for the training and evaluation of automated methods to identify concepts in biomedical text. This paper presents the concept annotations of the Colorado Richly Annotated Full-Text (CRAFT) Corpus, a collection of 97 full-length, open-access biomedical journal articles that have been annotated both semantically and syntactically to serve as a research resource for the biomedical natural-language-processing (NLP) community. CRAFT identifies all mentions of nearly all concepts from nine prominent biomedical ontologies and terminologies: the Cell Type Ontology, the Chemical Entities of Biological Interest ontology, the NCBI Taxonomy, the Protein Ontology, the Sequence Ontology, the entries of the Entrez Gene database, and the three subontologies of the Gene Ontology. The first public release includes the annotations for 67 of the 97 articles, reserving two sets of 15 articles for future text-mining competitions (after which these too will be released). Concept annotations were created based on a single set of guidelines, which has enabled us to achieve consistently high interannotator agreement. As the initial 67-article release contains more than 560,000 tokens (and the full set more than 790,000 tokens), our corpus is among the largest gold-standard annotated biomedical corpora. Unlike most others, the journal articles that comprise the corpus are drawn from diverse biomedical disciplines and are marked up in their entirety. Additionally, with a concept-annotation count of nearly 100,000 in the 67-article subset (and more than 140,000 in the full collection), the scale of conceptual markup is also among the largest of comparable corpora. The concept annotations of the CRAFT Corpus have the potential to significantly advance biomedical text mining by providing a high-quality gold standard for NLP systems. The corpus, annotation guidelines, and other associated resources are freely available at http://bionlp-corpora.sourceforge.net/CRAFT/index.shtml.

  4. Evaluation of Three Automated Genome Annotations for Halorhabdus utahensis

    DEFF Research Database (Denmark)

    Bakke, Peter; Carney, Nick; DeLoache, Will

    2009-01-01

    in databases such as NCBI and used to validate subsequent annotation errors. We submitted the genome sequence of halophilic archaeon Halorhabdus utahensis to be analyzed by three genome annotation services. We have examined the output from each service in a variety of ways in order to compare the methodology...

  5. The GATO gene annotation tool for research laboratories

    Directory of Open Access Journals (Sweden)

    A. Fujita

    2005-11-01

    Full Text Available Large-scale genome projects have generated a rapidly increasing number of DNA sequences. Therefore, development of computational methods to rapidly analyze these sequences is essential for progress in genomic research. Here we present an automatic annotation system for preliminary analysis of DNA sequences. The gene annotation tool (GATO is a Bioinformatics pipeline designed to facilitate routine functional annotation and easy access to annotated genes. It was designed in view of the frequent need of genomic researchers to access data pertaining to a common set of genes. In the GATO system, annotation is generated by querying some of the Web-accessible resources and the information is stored in a local database, which keeps a record of all previous annotation results. GATO may be accessed from everywhere through the internet or may be run locally if a large number of sequences are going to be annotated. It is implemented in PHP and Perl and may be run on any suitable Web server. Usually, installation and application of annotation systems require experience and are time consuming, but GATO is simple and practical, allowing anyone with basic skills in informatics to access it without any special training. GATO can be downloaded at [http://mariwork.iq.usp.br/gato/]. Minimum computer free space required is 2 MB.

  6. A framework for annotating human genome in disease context.

    Science.gov (United States)

    Xu, Wei; Wang, Huisong; Cheng, Wenqing; Fu, Dong; Xia, Tian; Kibbe, Warren A; Lin, Simon M

    2012-01-01

    Identification of gene-disease association is crucial to understanding disease mechanism. A rapid increase in biomedical literatures, led by advances of genome-scale technologies, poses challenge for manually-curated-based annotation databases to characterize gene-disease associations effectively and timely. We propose an automatic method-The Disease Ontology Annotation Framework (DOAF) to provide a comprehensive annotation of the human genome using the computable Disease Ontology (DO), the NCBO Annotator service and NCBI Gene Reference Into Function (GeneRIF). DOAF can keep the resulting knowledgebase current by periodically executing automatic pipeline to re-annotate the human genome using the latest DO and GeneRIF releases at any frequency such as daily or monthly. Further, DOAF provides a computable and programmable environment which enables large-scale and integrative analysis by working with external analytic software or online service platforms. A user-friendly web interface (doa.nubic.northwestern.edu) is implemented to allow users to efficiently query, download, and view disease annotations and the underlying evidences.

  7. Improving decoy databases for protein folding algorithms

    KAUST Repository

    Lindsey, Aaron

    2014-01-01

    Copyright © 2014 ACM. Predicting protein structures and simulating protein folding are two of the most important problems in computational biology today. Simulation methods rely on a scoring function to distinguish the native structure (the most energetically stable) from non-native structures. Decoy databases are collections of non-native structures used to test and verify these functions. We present a method to evaluate and improve the quality of decoy databases by adding novel structures and removing redundant structures. We test our approach on 17 different decoy databases of varying size and type and show significant improvement across a variety of metrics. We also test our improved databases on a popular modern scoring function and show that they contain a greater number of native-like structures than the original databases, thereby producing a more rigorous database for testing scoring functions.

  8. A database of immunoglobulins with integrated tools: DIGIT.

    KAUST Repository

    Chailyan, Anna; Tramontano, Anna; Marcatili, Paolo

    2011-01-01

    The DIGIT (Database of ImmunoGlobulins with Integrated Tools) database (http://biocomputing.it/digit) is an integrated resource storing sequences of annotated immunoglobulin variable domains and enriched with tools for searching and analyzing them. The annotations in the database include information on the type of antigen, the respective germline sequences and on pairing information between light and heavy chains. Other annotations, such as the identification of the complementarity determining regions, assignment of their structural class and identification of mutations with respect to the germline, are computed on the fly and can also be obtained for user-submitted sequences. The system allows customized BLAST searches and automatic building of 3D models of the domains to be performed.

  9. A database of immunoglobulins with integrated tools: DIGIT.

    KAUST Repository

    Chailyan, Anna

    2011-11-10

    The DIGIT (Database of ImmunoGlobulins with Integrated Tools) database (http://biocomputing.it/digit) is an integrated resource storing sequences of annotated immunoglobulin variable domains and enriched with tools for searching and analyzing them. The annotations in the database include information on the type of antigen, the respective germline sequences and on pairing information between light and heavy chains. Other annotations, such as the identification of the complementarity determining regions, assignment of their structural class and identification of mutations with respect to the germline, are computed on the fly and can also be obtained for user-submitted sequences. The system allows customized BLAST searches and automatic building of 3D models of the domains to be performed.

  10. Improving HIV proteome annotation: new features of BioAfrica HIV Proteomics Resource.

    Science.gov (United States)

    Druce, Megan; Hulo, Chantal; Masson, Patrick; Sommer, Paula; Xenarios, Ioannis; Le Mercier, Philippe; De Oliveira, Tulio

    2016-01-01

    The Human Immunodeficiency Virus (HIV) is one of the pathogens that cause the greatest global concern, with approximately 35 million people currently infected with HIV. Extensive HIV research has been performed, generating a large amount of HIV and host genomic data. However, no effective vaccine that protects the host from HIV infection is available and HIV is still spreading at an alarming rate, despite effective antiretroviral (ARV) treatment. In order to develop effective therapies, we need to expand our knowledge of the interaction between HIV and host proteins. In contrast to virus proteins, which often rapidly evolve drug resistance mutations, the host proteins are essentially invariant within all humans. Thus, if we can identify the host proteins needed for virus replication, such as those involved in transporting viral proteins to the cell surface, we have a chance of interrupting viral replication. There is no proteome resource that summarizes this interaction, making research on this subject a difficult enterprise. In order to fill this gap in knowledge, we curated a resource presents detailed annotation on the interaction between the HIV proteome and host proteins. Our resource was produced in collaboration with ViralZone and used manual curation techniques developed by UniProtKB/Swiss-Prot. Our new website also used previous annotations of the BioAfrica HIV-1 Proteome Resource, which has been accessed by approximately 10 000 unique users a year since its inception in 2005. The novel features include a dedicated new page for each HIV protein, a graphic display of its function and a section on its interaction with host proteins. Our new webpages also add information on the genomic location of each HIV protein and the position of ARV drug resistance mutations. Our improved BioAfrica HIV-1 Proteome Resource fills a gap in the current knowledge of biocuration.Database URL:http://www.bioafrica.net/proteomics/HIVproteome.html. © The Author(s) 2016. Published

  11. Brassica ASTRA: an integrated database for Brassica genomic research.

    Science.gov (United States)

    Love, Christopher G; Robinson, Andrew J; Lim, Geraldine A C; Hopkins, Clare J; Batley, Jacqueline; Barker, Gary; Spangenberg, German C; Edwards, David

    2005-01-01

    Brassica ASTRA is a public database for genomic information on Brassica species. The database incorporates expressed sequences with Swiss-Prot and GenBank comparative sequence annotation as well as secondary Gene Ontology (GO) annotation derived from the comparison with Arabidopsis TAIR GO annotations. Simple sequence repeat molecular markers are identified within resident sequences and mapped onto the closely related Arabidopsis genome sequence. Bacterial artificial chromosome (BAC) end sequences derived from the Multinational Brassica Genome Project are also mapped onto the Arabidopsis genome sequence enabling users to identify candidate Brassica BACs corresponding to syntenic regions of Arabidopsis. This information is maintained in a MySQL database with a web interface providing the primary means of interrogation. The database is accessible at http://hornbill.cspp.latrobe.edu.au.

  12. A post-assembly genome-improvement toolkit (PAGIT) to obtain annotated genomes from contigs.

    Science.gov (United States)

    Swain, Martin T; Tsai, Isheng J; Assefa, Samual A; Newbold, Chris; Berriman, Matthew; Otto, Thomas D

    2012-06-07

    Genome projects now produce draft assemblies within weeks owing to advanced high-throughput sequencing technologies. For milestone projects such as Escherichia coli or Homo sapiens, teams of scientists were employed to manually curate and finish these genomes to a high standard. Nowadays, this is not feasible for most projects, and the quality of genomes is generally of a much lower standard. This protocol describes software (PAGIT) that is used to improve the quality of draft genomes. It offers flexible functionality to close gaps in scaffolds, correct base errors in the consensus sequence and exploit reference genomes (if available) in order to improve scaffolding and generating annotations. The protocol is most accessible for bacterial and small eukaryotic genomes (up to 300 Mb), such as pathogenic bacteria, malaria and parasitic worms. Applying PAGIT to an E. coli assembly takes ∼24 h: it doubles the average contig size and annotates over 4,300 gene models.

  13. A kingdom-specific protein domain HMM library for improved annotation of fungal genomes

    Directory of Open Access Journals (Sweden)

    Oliver Stephen G

    2007-04-01

    Full Text Available Abstract Background Pfam is a general-purpose database of protein domain alignments and profile Hidden Markov Models (HMMs, which is very popular for the annotation of sequence data produced by genome sequencing projects. Pfam provides models that are often very general in terms of the taxa that they cover and it has previously been suggested that such general models may lack some of the specificity or selectivity that would be provided by kingdom-specific models. Results Here we present a general approach to create domain libraries of HMMs for sub-taxa of a kingdom. Taking fungal species as an example, we construct a domain library of HMMs (called Fungal Pfam or FPfam using sequences from 30 genomes, consisting of 24 species from the ascomycetes group and two basidiomycetes, Ustilago maydis, a fungal pathogen of maize, and the white rot fungus Phanerochaete chrysosporium. In addition, we include the Microsporidion Encephalitozoon cuniculi, an obligate intracellular parasite, and two non-fungal species, the oomycetes Phytophthora sojae and Phytophthora ramorum, both plant pathogens. We evaluate the performance in terms of coverage against the original 30 genomes used in training FPfam and against five more recently sequenced fungal genomes that can be considered as an independent test set. We show that kingdom-specific models such as FPfam can find instances of both novel and well characterized domains, increases overall coverage and detects more domains per sequence with typically higher bitscores than Pfam for the same domain families. An evaluation of the effect of changing E-values on the coverage shows that the performance of FPfam is consistent over the range of E-values applied. Conclusion Kingdom-specific models are shown to provide improved coverage. However, as the models become more specific, some sequences found by Pfam may be missed by the models in FPfam and some of the families represented in the test set are not present in FPfam

  14. Improvement of database on glass dissolution

    International Nuclear Information System (INIS)

    Hayashi, Maki; Sasamoto, Hiroshi; Yoshikawa, Hideki

    2008-03-01

    In geological disposal system, high-level radioactive waste (HLW) glass is expected to retain radionuclide for the long term as the first barrier to prevent radionuclide release. The advancement of its performance assessment technology leads to the reliability improvement of the safety assessment of entire geological disposal system. For this purpose, phenomenological studies for improvement of scientific understanding of dissolution/alteration mechanisms, and development of robust dissolution/alteration model based on the study outcomes are indispensable. The database on glass dissolution has been developed for supporting these studies. This report describes improvement of the prototype glass database. Also, this report gives an example of the application of the database for reliability assessment of glass dissolution model. (author)

  15. Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes.

    Science.gov (United States)

    Feuermann, Marc; Gaudet, Pascale; Mi, Huaiyu; Lewis, Suzanna E; Thomas, Paul D

    2016-01-01

    We previously reported a paradigm for large-scale phylogenomic analysis of gene families that takes advantage of the large corpus of experimentally supported Gene Ontology (GO) annotations. This 'GO Phylogenetic Annotation' approach integrates GO annotations from evolutionarily related genes across ∼100 different organisms in the context of a gene family tree, in which curators build an explicit model of the evolution of gene functions. GO Phylogenetic Annotation models the gain and loss of functions in a gene family tree, which is used to infer the functions of uncharacterized (or incompletely characterized) gene products, even for human proteins that are relatively well studied. Here, we report our results from applying this paradigm to two well-characterized cellular processes, apoptosis and autophagy. This revealed several important observations with respect to GO annotations and how they can be used for function inference. Notably, we applied only a small fraction of the experimentally supported GO annotations to infer function in other family members. The majority of other annotations describe indirect effects, phenotypes or results from high throughput experiments. In addition, we show here how feedback from phylogenetic annotation leads to significant improvements in the PANTHER trees, the GO annotations and GO itself. Thus GO phylogenetic annotation both increases the quantity and improves the accuracy of the GO annotations provided to the research community. We expect these phylogenetically based annotations to be of broad use in gene enrichment analysis as well as other applications of GO annotations.Database URL: http://amigo.geneontology.org/amigo. © The Author(s) 2016. Published by Oxford University Press.

  16. MIPS: a database for genomes and protein sequences.

    Science.gov (United States)

    Mewes, H W; Frishman, D; Güldener, U; Mannhaupt, G; Mayer, K; Mokrejs, M; Morgenstern, B; Münsterkötter, M; Rudd, S; Weil, B

    2002-01-01

    The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz-Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91-93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155-158; Barker et al. (2001) Nucleic Acids Res., 29, 29-32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de).

  17. EnzDP: improved enzyme annotation for metabolic network reconstruction based on domain composition profiles.

    Science.gov (United States)

    Nguyen, Nam-Ninh; Srihari, Sriganesh; Leong, Hon Wai; Chong, Ket-Fah

    2015-10-01

    Determining the entire complement of enzymes and their enzymatic functions is a fundamental step for reconstructing the metabolic network of cells. High quality enzyme annotation helps in enhancing metabolic networks reconstructed from the genome, especially by reducing gaps and increasing the enzyme coverage. Currently, structure-based and network-based approaches can only cover a limited number of enzyme families, and the accuracy of homology-based approaches can be further improved. Bottom-up homology-based approach improves the coverage by rebuilding Hidden Markov Model (HMM) profiles for all known enzymes. However, its clustering procedure relies firmly on BLAST similarity score, ignoring protein domains/patterns, and is sensitive to changes in cut-off thresholds. Here, we use functional domain architecture to score the association between domain families and enzyme families (Domain-Enzyme Association Scoring, DEAS). The DEAS score is used to calculate the similarity between proteins, which is then used in clustering procedure, instead of using sequence similarity score. We improve the enzyme annotation protocol using a stringent classification procedure, and by choosing optimal threshold settings and checking for active sites. Our analysis shows that our stringent protocol EnzDP can cover up to 90% of enzyme families available in Swiss-Prot. It achieves a high accuracy of 94.5% based on five-fold cross-validation. EnzDP outperforms existing methods across several testing scenarios. Thus, EnzDP serves as a reliable automated tool for enzyme annotation and metabolic network reconstruction. Available at: www.comp.nus.edu.sg/~nguyennn/EnzDP .

  18. The volatile compound BinBase mass spectral database.

    Science.gov (United States)

    Skogerson, Kirsten; Wohlgemuth, Gert; Barupal, Dinesh K; Fiehn, Oliver

    2011-08-04

    Volatile compounds comprise diverse chemical groups with wide-ranging sources and functions. These compounds originate from major pathways of secondary metabolism in many organisms and play essential roles in chemical ecology in both plant and animal kingdoms. In past decades, sampling methods and instrumentation for the analysis of complex volatile mixtures have improved; however, design and implementation of database tools to process and store the complex datasets have lagged behind. The volatile compound BinBase (vocBinBase) is an automated peak annotation and database system developed for the analysis of GC-TOF-MS data derived from complex volatile mixtures. The vocBinBase DB is an extension of the previously reported metabolite BinBase software developed to track and identify derivatized metabolites. The BinBase algorithm uses deconvoluted spectra and peak metadata (retention index, unique ion, spectral similarity, peak signal-to-noise ratio, and peak purity) from the Leco ChromaTOF software, and annotates peaks using a multi-tiered filtering system with stringent thresholds. The vocBinBase algorithm assigns the identity of compounds existing in the database. Volatile compound assignments are supported by the Adams mass spectral-retention index library, which contains over 2,000 plant-derived volatile compounds. Novel molecules that are not found within vocBinBase are automatically added using strict mass spectral and experimental criteria. Users obtain fully annotated data sheets with quantitative information for all volatile compounds for studies that may consist of thousands of chromatograms. The vocBinBase database may also be queried across different studies, comprising currently 1,537 unique mass spectra generated from 1.7 million deconvoluted mass spectra of 3,435 samples (18 species). Mass spectra with retention indices and volatile profiles are available as free download under the CC-BY agreement (http://vocbinbase.fiehnlab.ucdavis.edu). The Bin

  19. The volatile compound BinBase mass spectral database

    Directory of Open Access Journals (Sweden)

    Barupal Dinesh K

    2011-08-01

    Full Text Available Abstract Background Volatile compounds comprise diverse chemical groups with wide-ranging sources and functions. These compounds originate from major pathways of secondary metabolism in many organisms and play essential roles in chemical ecology in both plant and animal kingdoms. In past decades, sampling methods and instrumentation for the analysis of complex volatile mixtures have improved; however, design and implementation of database tools to process and store the complex datasets have lagged behind. Description The volatile compound BinBase (vocBinBase is an automated peak annotation and database system developed for the analysis of GC-TOF-MS data derived from complex volatile mixtures. The vocBinBase DB is an extension of the previously reported metabolite BinBase software developed to track and identify derivatized metabolites. The BinBase algorithm uses deconvoluted spectra and peak metadata (retention index, unique ion, spectral similarity, peak signal-to-noise ratio, and peak purity from the Leco ChromaTOF software, and annotates peaks using a multi-tiered filtering system with stringent thresholds. The vocBinBase algorithm assigns the identity of compounds existing in the database. Volatile compound assignments are supported by the Adams mass spectral-retention index library, which contains over 2,000 plant-derived volatile compounds. Novel molecules that are not found within vocBinBase are automatically added using strict mass spectral and experimental criteria. Users obtain fully annotated data sheets with quantitative information for all volatile compounds for studies that may consist of thousands of chromatograms. The vocBinBase database may also be queried across different studies, comprising currently 1,537 unique mass spectra generated from 1.7 million deconvoluted mass spectra of 3,435 samples (18 species. Mass spectra with retention indices and volatile profiles are available as free download under the CC-BY agreement (http

  20. ExpTreeDB: web-based query and visualization of manually annotated gene expression profiling experiments of human and mouse from GEO.

    Science.gov (United States)

    Ni, Ming; Ye, Fuqiang; Zhu, Juanjuan; Li, Zongwei; Yang, Shuai; Yang, Bite; Han, Lu; Wu, Yongge; Chen, Ying; Li, Fei; Wang, Shengqi; Bo, Xiaochen

    2014-12-01

    Numerous public microarray datasets are valuable resources for the scientific communities. Several online tools have made great steps to use these data by querying related datasets with users' own gene signatures or expression profiles. However, dataset annotation and result exhibition still need to be improved. ExpTreeDB is a database that allows for queries on human and mouse microarray experiments from Gene Expression Omnibus with gene signatures or profiles. Compared with similar applications, ExpTreeDB pays more attention to dataset annotations and result visualization. We introduced a multiple-level annotation system to depict and organize original experiments. For example, a tamoxifen-treated cell line experiment is hierarchically annotated as 'agent→drug→estrogen receptor antagonist→tamoxifen'. Consequently, retrieved results are exhibited by an interactive tree-structured graphics, which provide an overview for related experiments and might enlighten users on key items of interest. The database is freely available at http://biotech.bmi.ac.cn/ExpTreeDB. Web site is implemented in Perl, PHP, R, MySQL and Apache. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. The UCSC Genome Browser Database: update 2006

    DEFF Research Database (Denmark)

    Hinrichs, A S; Karolchik, D; Baertsch, R

    2006-01-01

    The University of California Santa Cruz Genome Browser Database (GBD) contains sequence and annotation data for the genomes of about a dozen vertebrate species and several major model organisms. Genome annotations typically include assembly data, sequence composition, genes and gene predictions, ...

  2. SNAD: sequence name annotation-based designer

    Directory of Open Access Journals (Sweden)

    Gorbalenya Alexander E

    2009-08-01

    Full Text Available Abstract Background A growing diversity of biological data is tagged with unique identifiers (UIDs associated with polynucleotides and proteins to ensure efficient computer-mediated data storage, maintenance, and processing. These identifiers, which are not informative for most people, are often substituted by biologically meaningful names in various presentations to facilitate utilization and dissemination of sequence-based knowledge. This substitution is commonly done manually that may be a tedious exercise prone to mistakes and omissions. Results Here we introduce SNAD (Sequence Name Annotation-based Designer that mediates automatic conversion of sequence UIDs (associated with multiple alignment or phylogenetic tree, or supplied as plain text list into biologically meaningful names and acronyms. This conversion is directed by precompiled or user-defined templates that exploit wealth of annotation available in cognate entries of external databases. Using examples, we demonstrate how this tool can be used to generate names for practical purposes, particularly in virology. Conclusion A tool for controllable annotation-based conversion of sequence UIDs into biologically meaningful names and acronyms has been developed and placed into service, fostering links between quality of sequence annotation, and efficiency of communication and knowledge dissemination among researchers.

  3. The MAR databases: development and implementation of databases specific for marine metagenomics.

    Science.gov (United States)

    Klemetsen, Terje; Raknes, Inge A; Fu, Juan; Agafonov, Alexander; Balasundaram, Sudhagar V; Tartari, Giacomo; Robertsen, Espen; Willassen, Nils P

    2018-01-04

    We introduce the marine databases; MarRef, MarDB and MarCat (https://mmp.sfb.uit.no/databases/), which are publicly available resources that promote marine research and innovation. These data resources, which have been implemented in the Marine Metagenomics Portal (MMP) (https://mmp.sfb.uit.no/), are collections of richly annotated and manually curated contextual (metadata) and sequence databases representing three tiers of accuracy. While MarRef is a database for completely sequenced marine prokaryotic genomes, which represent a marine prokaryote reference genome database, MarDB includes all incomplete sequenced prokaryotic genomes regardless level of completeness. The last database, MarCat, represents a gene (protein) catalog of uncultivable (and cultivable) marine genes and proteins derived from marine metagenomics samples. The first versions of MarRef and MarDB contain 612 and 3726 records, respectively. Each record is built up of 106 metadata fields including attributes for sampling, sequencing, assembly and annotation in addition to the organism and taxonomic information. Currently, MarCat contains 1227 records with 55 metadata fields. Ontologies and controlled vocabularies are used in the contextual databases to enhance consistency. The user-friendly web interface lets the visitors browse, filter and search in the contextual databases and perform BLAST searches against the corresponding sequence databases. All contextual and sequence databases are freely accessible and downloadable from https://s1.sfb.uit.no/public/mar/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  4. Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists.

    Science.gov (United States)

    Wiley, Laura K; Sivley, R Michael; Bush, William S

    2013-01-01

    Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist.

  5. A database for coconut crop improvement.

    Science.gov (United States)

    Rajagopal, Velamoor; Manimekalai, Ramaswamy; Devakumar, Krishnamurthy; Rajesh; Karun, Anitha; Niral, Vittal; Gopal, Murali; Aziz, Shamina; Gunasekaran, Marimuthu; Kumar, Mundappurathe Ramesh; Chandrasekar, Arumugam

    2005-12-08

    Coconut crop improvement requires a number of biotechnology and bioinformatics tools. A database containing information on CG (coconut germplasm), CCI (coconut cultivar identification), CD (coconut disease), MIFSPC (microbial information systems in plantation crops) and VO (vegetable oils) is described. The database was developed using MySQL and PostgreSQL running in Linux operating system. The database interface is developed in PHP, HTML and JAVA. http://www.bioinfcpcri.org.

  6. MetaStorm: A Public Resource for Customizable Metagenomics Annotation.

    Directory of Open Access Journals (Sweden)

    Gustavo Arango-Argoty

    Full Text Available Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. The need to store, retrieve, analyze, share, and visualize such data challenges current online computational systems. Interpretation and annotation of specific information is especially a challenge for metagenomic data sets derived from environmental samples, because current annotation systems only offer broad classification of microbial diversity and function. Moreover, existing resources are not configured to readily address common questions relevant to environmental systems. Here we developed a new online user-friendly metagenomic analysis server called MetaStorm (http://bench.cs.vt.edu/MetaStorm/, which facilitates customization of computational analysis for metagenomic data sets. Users can upload their own reference databases to tailor the metagenomics annotation to focus on various taxonomic and functional gene markers of interest. MetaStorm offers two major analysis pipelines: an assembly-based annotation pipeline and the standard read annotation pipeline used by existing web servers. These pipelines can be selected individually or together. Overall, MetaStorm provides enhanced interactive visualization to allow researchers to explore and manipulate taxonomy and functional annotation at various levels of resolution.

  7. MetaStorm: A Public Resource for Customizable Metagenomics Annotation.

    Science.gov (United States)

    Arango-Argoty, Gustavo; Singh, Gargi; Heath, Lenwood S; Pruden, Amy; Xiao, Weidong; Zhang, Liqing

    2016-01-01

    Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. The need to store, retrieve, analyze, share, and visualize such data challenges current online computational systems. Interpretation and annotation of specific information is especially a challenge for metagenomic data sets derived from environmental samples, because current annotation systems only offer broad classification of microbial diversity and function. Moreover, existing resources are not configured to readily address common questions relevant to environmental systems. Here we developed a new online user-friendly metagenomic analysis server called MetaStorm (http://bench.cs.vt.edu/MetaStorm/), which facilitates customization of computational analysis for metagenomic data sets. Users can upload their own reference databases to tailor the metagenomics annotation to focus on various taxonomic and functional gene markers of interest. MetaStorm offers two major analysis pipelines: an assembly-based annotation pipeline and the standard read annotation pipeline used by existing web servers. These pipelines can be selected individually or together. Overall, MetaStorm provides enhanced interactive visualization to allow researchers to explore and manipulate taxonomy and functional annotation at various levels of resolution.

  8. MetaStorm: A Public Resource for Customizable Metagenomics Annotation

    Science.gov (United States)

    Arango-Argoty, Gustavo; Singh, Gargi; Heath, Lenwood S.; Pruden, Amy; Xiao, Weidong; Zhang, Liqing

    2016-01-01

    Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. The need to store, retrieve, analyze, share, and visualize such data challenges current online computational systems. Interpretation and annotation of specific information is especially a challenge for metagenomic data sets derived from environmental samples, because current annotation systems only offer broad classification of microbial diversity and function. Moreover, existing resources are not configured to readily address common questions relevant to environmental systems. Here we developed a new online user-friendly metagenomic analysis server called MetaStorm (http://bench.cs.vt.edu/MetaStorm/), which facilitates customization of computational analysis for metagenomic data sets. Users can upload their own reference databases to tailor the metagenomics annotation to focus on various taxonomic and functional gene markers of interest. MetaStorm offers two major analysis pipelines: an assembly-based annotation pipeline and the standard read annotation pipeline used by existing web servers. These pipelines can be selected individually or together. Overall, MetaStorm provides enhanced interactive visualization to allow researchers to explore and manipulate taxonomy and functional annotation at various levels of resolution. PMID:27632579

  9. The effectiveness of annotated (vs. non-annotated) digital pathology slides as a teaching tool during dermatology and pathology residencies.

    Science.gov (United States)

    Marsch, Amanda F; Espiritu, Baltazar; Groth, John; Hutchens, Kelli A

    2014-06-01

    With today's technology, paraffin-embedded, hematoxylin & eosin-stained pathology slides can be scanned to generate high quality virtual slides. Using proprietary software, digital images can also be annotated with arrows, circles and boxes to highlight certain diagnostic features. Previous studies assessing digital microscopy as a teaching tool did not involve the annotation of digital images. The objective of this study was to compare the effectiveness of annotated digital pathology slides versus non-annotated digital pathology slides as a teaching tool during dermatology and pathology residencies. A study group composed of 31 dermatology and pathology residents was asked to complete an online pre-quiz consisting of 20 multiple choice style questions, each associated with a static digital pathology image. After completion, participants were given access to an online tutorial composed of digitally annotated pathology slides and subsequently asked to complete a post-quiz. A control group of 12 residents completed a non-annotated version of the tutorial. Nearly all participants in the study group improved their quiz score, with an average improvement of 17%, versus only 3% (P = 0.005) in the control group. These results support the notion that annotated digital pathology slides are superior to non-annotated slides for the purpose of resident education. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  10. The UCSC genome browser database: update 2007

    DEFF Research Database (Denmark)

    Kuhn, R M; Karolchik, D; Zweig, A S

    2006-01-01

    The University of California, Santa Cruz Genome Browser Database contains, as of September 2006, sequence and annotation data for the genomes of 13 vertebrate and 19 invertebrate species. The Genome Browser displays a wide variety of annotations at all scales from the single nucleotide level up t...

  11. Annotation-Based Whole Genomic Prediction and Selection

    DEFF Research Database (Denmark)

    Kadarmideen, Haja; Do, Duy Ngoc; Janss, Luc

    Genomic selection is widely used in both animal and plant species, however, it is performed with no input from known genomic or biological role of genetic variants and therefore is a black box approach in a genomic era. This study investigated the role of different genomic regions and detected QTLs...... in their contribution to estimated genomic variances and in prediction of genomic breeding values by applying SNP annotation approaches to feed efficiency. Ensembl Variant Predictor (EVP) and Pig QTL database were used as the source of genomic annotation for 60K chip. Genomic prediction was performed using the Bayes...... classes. Predictive accuracy was 0.531, 0.532, 0.302, and 0.344 for DFI, RFI, ADG and BF, respectively. The contribution per SNP to total genomic variance was similar among annotated classes across different traits. Predictive performance of SNP classes did not significantly differ from randomized SNP...

  12. Potential impacts of OCS oil and gas activities on fisheries. Volume 1. Annotated bibliography and database descriptions for target-species distribution and abundance studies. Section 1, Part 2. Final report

    International Nuclear Information System (INIS)

    Tear, L.M.

    1989-10-01

    The purpose of the volume is to present an annotated bibliography of unpublished and grey literature related to the distribution and abundance of select species of finfish and shellfish along the coasts of the United States. The volume also includes descriptions of databases that contain information related to target species' distribution and abundance. An index is provided at the end of each section to help the reader locate studies or databases related to a particular species

  13. Potential impacts of OCS oil and gas activities on fisheries. Volume 1. Annotated bibliography and database descriptions for target species distribution and abundance studies. Section 1, Part 1. Final report

    International Nuclear Information System (INIS)

    Tear, L.M.

    1989-10-01

    The purpose of the volume is to present an annotated bibliography of unpublished and grey literature related to the distribution and abundance of select species of finfish and shellfish along the coasts of the United States. The volume also includes descriptions of databases that contain information related to target species' distribution and abundance. An index is provided at the end of each section to help the reader locate studies or databases related to a particular species

  14. Can Global Visual Features Improve Tag Recommendation for Image Annotation?

    Directory of Open Access Journals (Sweden)

    Oge Marques

    2010-08-01

    Full Text Available Recent advances in the fields of digital photography, networking and computing, have made it easier than ever for users to store and share photographs. However without sufficient metadata, e.g., in the form of tags, photos are difficult to find and organize. In this paper, we describe a system that recommends tags for image annotation. We postulate that the use of low-level global visual features can improve the quality of the tag recommendation process when compared to a baseline statistical method based on tag co-occurrence. We present results from experiments conducted using photos and metadata sourced from the Flickr photo website that suggest that the use of visual features improves the mean average precision (MAP of the system and increases the system's ability to suggest different tags, therefore justifying the associated increase in complexity.

  15. Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae

    DEFF Research Database (Denmark)

    Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim

    2008-01-01

    Background: Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number...... to a genome scale metabolic model of A. oryzae. Results: Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted...... model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources. Conclusion: A much enhanced annotation of the A. oryzae genome was performed and a genomescale metabolic model of A. oryzae was reconstructed. The model accurately predicted...

  16. CEBS: a comprehensive annotated database of toxicological data

    Science.gov (United States)

    Lea, Isabel A.; Gong, Hui; Paleja, Anand; Rashid, Asif; Fostel, Jennifer

    2017-01-01

    The Chemical Effects in Biological Systems database (CEBS) is a comprehensive and unique toxicology resource that compiles individual and summary animal data from the National Toxicology Program (NTP) testing program and other depositors into a single electronic repository. CEBS has undergone significant updates in recent years and currently contains over 11 000 test articles (exposure agents) and over 8000 studies including all available NTP carcinogenicity, short-term toxicity and genetic toxicity studies. Study data provided to CEBS are manually curated, accessioned and subject to quality assurance review prior to release to ensure high quality. The CEBS database has two main components: data collection and data delivery. To accommodate the breadth of data produced by NTP, the CEBS data collection component is an integrated relational design that allows the flexibility to capture any type of electronic data (to date). The data delivery component of the database comprises a series of dedicated user interface tables containing pre-processed data that support each component of the user interface. The user interface has been updated to include a series of nine Guided Search tools that allow access to NTP summary and conclusion data and larger non-NTP datasets. The CEBS database can be accessed online at http://www.niehs.nih.gov/research/resources/databases/cebs/. PMID:27899660

  17. Cadastral Database Positional Accuracy Improvement

    Science.gov (United States)

    Hashim, N. M.; Omar, A. H.; Ramli, S. N. M.; Omar, K. M.; Din, N.

    2017-10-01

    Positional Accuracy Improvement (PAI) is the refining process of the geometry feature in a geospatial dataset to improve its actual position. This actual position relates to the absolute position in specific coordinate system and the relation to the neighborhood features. With the growth of spatial based technology especially Geographical Information System (GIS) and Global Navigation Satellite System (GNSS), the PAI campaign is inevitable especially to the legacy cadastral database. Integration of legacy dataset and higher accuracy dataset like GNSS observation is a potential solution for improving the legacy dataset. However, by merely integrating both datasets will lead to a distortion of the relative geometry. The improved dataset should be further treated to minimize inherent errors and fitting to the new accurate dataset. The main focus of this study is to describe a method of angular based Least Square Adjustment (LSA) for PAI process of legacy dataset. The existing high accuracy dataset known as National Digital Cadastral Database (NDCDB) is then used as bench mark to validate the results. It was found that the propose technique is highly possible for positional accuracy improvement of legacy spatial datasets.

  18. A database of annotated tentative orthologs from crop abiotic stress transcripts.

    Science.gov (United States)

    Balaji, Jayashree; Crouch, Jonathan H; Petite, Prasad V N S; Hoisington, David A

    2006-10-07

    A minimal requirement to initiate a comparative genomics study on plant responses to abiotic stresses is a dataset of orthologous sequences. The availability of a large amount of sequence information, including those derived from stress cDNA libraries allow for the identification of stress related genes and orthologs associated with the stress response. Orthologous sequences serve as tools to explore genes and their relationships across species. For this purpose, ESTs from stress cDNA libraries across 16 crop species including 6 important cereal crops and 10 dicots were systematically collated and subjected to bioinformatics analysis such as clustering, grouping of tentative orthologous sets, identification of protein motifs/patterns in the predicted protein sequence, and annotation with stress conditions, tissue/library source and putative function. All data are available to the scientific community at http://intranet.icrisat.org/gt1/tog/homepage.htm. We believe that the availability of annotated plant abiotic stress ortholog sets will be a valuable resource for researchers studying the biology of environmental stresses in plant systems, molecular evolution and genomics.

  19. Enhanced oil recovery using improved aqueous fluid-injection methods: an annotated bibliography. [328 citations

    Energy Technology Data Exchange (ETDEWEB)

    Meister, M.J.; Kettenbrink, G.K.; Collins, A.G.

    1976-10-01

    This annotated bibliography contains abstracts, prepared by the authors, of articles published between 1968 and early 1976 on tests of improved aqueous fluid injection methods (i.e., polymer and surfactant floods). The abstracts have been written and organized to facilitate studies of the oil recovery potential of polymer and surfactant floods under known reservoir conditions. 328 citations.

  20. Fuzzy Emotional Semantic Analysis and Automated Annotation of Scene Images

    Directory of Open Access Journals (Sweden)

    Jianfang Cao

    2015-01-01

    Full Text Available With the advances in electronic and imaging techniques, the production of digital images has rapidly increased, and the extraction and automated annotation of emotional semantics implied by images have become issues that must be urgently addressed. To better simulate human subjectivity and ambiguity for understanding scene images, the current study proposes an emotional semantic annotation method for scene images based on fuzzy set theory. A fuzzy membership degree was calculated to describe the emotional degree of a scene image and was implemented using the Adaboost algorithm and a back-propagation (BP neural network. The automated annotation method was trained and tested using scene images from the SUN Database. The annotation results were then compared with those based on artificial annotation. Our method showed an annotation accuracy rate of 91.2% for basic emotional values and 82.4% after extended emotional values were added, which correspond to increases of 5.5% and 8.9%, respectively, compared with the results from using a single BP neural network algorithm. Furthermore, the retrieval accuracy rate based on our method reached approximately 89%. This study attempts to lay a solid foundation for the automated emotional semantic annotation of more types of images and therefore is of practical significance.

  1. Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob; Hohimer, Ryan E.; White, Amanda M.

    2006-06-06

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  2. Plant protein annotation in the UniProt Knowledgebase.

    Science.gov (United States)

    Schneider, Michel; Bairoch, Amos; Wu, Cathy H; Apweiler, Rolf

    2005-05-01

    The Swiss-Prot, TrEMBL, Protein Information Resource (PIR), and DNA Data Bank of Japan (DDBJ) protein database activities have united to form the Universal Protein Resource (UniProt) Consortium. UniProt presents three database layers: the UniProt Archive, the UniProt Knowledgebase (UniProtKB), and the UniProt Reference Clusters. The UniProtKB consists of two sections: UniProtKB/Swiss-Prot (fully manually curated entries) and UniProtKB/TrEMBL (automated annotation, classification and extensive cross-references). New releases are published fortnightly. A specific Plant Proteome Annotation Program (http://www.expasy.org/sprot/ppap/) was initiated to cope with the increasing amount of data produced by the complete sequencing of plant genomes. Through UniProt, our aim is to provide the scientific community with a single, centralized, authoritative resource for protein sequences and functional information that will allow the plant community to fully explore and utilize the wealth of information available for both plant and non-plant model organisms.

  3. Lynx web services for annotations and systems analysis of multi-gene disorders.

    Science.gov (United States)

    Sulakhe, Dinanath; Taylor, Andrew; Balasubramanian, Sandhya; Feng, Bo; Xie, Bingqing; Börnigen, Daniela; Dave, Utpal J; Foster, Ian T; Gilliam, T Conrad; Maltsev, Natalia

    2014-07-01

    Lynx is a web-based integrated systems biology platform that supports annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Lynx has integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual and others) from various public databases as well as manually curated data from our group and collaborators (LynxKB). Lynx provides tools for gene list enrichment analysis using multiple functional annotations and network-based gene prioritization. Lynx provides access to the integrated database and the analytical tools via REST based Web Services (http://lynx.ci.uchicago.edu/webservices.html). This comprises data retrieval services for specific functional annotations, services to search across the complete LynxKB (powered by Lucene), and services to access the analytical tools built within the Lynx platform. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  4. Medicago truncatula transporter database: a comprehensive database resource for M. truncatula transporters

    Directory of Open Access Journals (Sweden)

    Miao Zhenyan

    2012-02-01

    Full Text Available Abstract Background Medicago truncatula has been chosen as a model species for genomic studies. It is closely related to an important legume, alfalfa. Transporters are a large group of membrane-spanning proteins. They deliver essential nutrients, eject waste products, and assist the cell in sensing environmental conditions by forming a complex system of pumps and channels. Although studies have effectively characterized individual M. truncatula transporters in several databases, until now there has been no available systematic database that includes all transporters in M. truncatula. Description The M. truncatula transporter database (MTDB contains comprehensive information on the transporters in M. truncatula. Based on the TransportTP method, we have presented a novel prediction pipeline. A total of 3,665 putative transporters have been annotated based on International Medicago Genome Annotated Group (IMGAG V3.5 V3 and the M. truncatula Gene Index (MTGI V10.0 releases and assigned to 162 families according to the transporter classification system. These families were further classified into seven types according to their transport mode and energy coupling mechanism. Extensive annotations referring to each protein were generated, including basic protein function, expressed sequence tag (EST mapping, genome locus, three-dimensional template prediction, transmembrane segment, and domain annotation. A chromosome distribution map and text-based Basic Local Alignment Search Tools were also created. In addition, we have provided a way to explore the expression of putative M. truncatula transporter genes under stress treatments. Conclusions In summary, the MTDB enables the exploration and comparative analysis of putative transporters in M. truncatula. A user-friendly web interface and regular updates make MTDB valuable to researchers in related fields. The MTDB is freely available now to all users at http://bioinformatics.cau.edu.cn/MtTransporter/.

  5. Evaluation of web-based annotation of ophthalmic images for multicentric clinical trials.

    Science.gov (United States)

    Chalam, K V; Jain, P; Shah, V A; Shah, Gaurav Y

    2006-06-01

    An Internet browser-based annotation system can be used to identify and describe features in digitalized retinal images, in multicentric clinical trials, in real time. In this web-based annotation system, the user employs a mouse to draw and create annotations on a transparent layer, that encapsulates the observations and interpretations of a specific image. Multiple annotation layers may be overlaid on a single image. These layers may correspond to annotations by different users on the same image or annotations of a temporal sequence of images of a disease process, over a period of time. In addition, geometrical properties of annotated figures may be computed and measured. The annotations are stored in a central repository database on a server, which can be retrieved by multiple users in real time. This system facilitates objective evaluation of digital images and comparison of double-blind readings of digital photographs, with an identifiable audit trail. Annotation of ophthalmic images allowed clinically feasible and useful interpretation to track properties of an area of fundus pathology. This provided an objective method to monitor properties of pathologies over time, an essential component of multicentric clinical trials. The annotation system also allowed users to view stereoscopic images that are stereo pairs. This web-based annotation system is useful and valuable in monitoring patient care, in multicentric clinical trials, telemedicine, teaching and routine clinical settings.

  6. TabSQL: a MySQL tool to facilitate mapping user data to public databases.

    Science.gov (United States)

    Xia, Xiao-Qin; McClelland, Michael; Wang, Yipeng

    2010-06-23

    With advances in high-throughput genomics and proteomics, it is challenging for biologists to deal with large data files and to map their data to annotations in public databases. We developed TabSQL, a MySQL-based application tool, for viewing, filtering and querying data files with large numbers of rows. TabSQL provides functions for downloading and installing table files from public databases including the Gene Ontology database (GO), the Ensembl databases, and genome databases from the UCSC genome bioinformatics site. Any other database that provides tab-delimited flat files can also be imported. The downloaded gene annotation tables can be queried together with users' data in TabSQL using either a graphic interface or command line. TabSQL allows queries across the user's data and public databases without programming. It is a convenient tool for biologists to annotate and enrich their data.

  7. Workflow and web application for annotating NCBI BioProject transcriptome data.

    Science.gov (United States)

    Vera Alvarez, Roberto; Medeiros Vidal, Newton; Garzón-Martínez, Gina A; Barrero, Luz S; Landsman, David; Mariño-Ramírez, Leonardo

    2017-01-01

    The volume of transcriptome data is growing exponentially due to rapid improvement of experimental technologies. In response, large central resources such as those of the National Center for Biotechnology Information (NCBI) are continually adapting their computational infrastructure to accommodate this large influx of data. New and specialized databases, such as Transcriptome Shotgun Assembly Sequence Database (TSA) and Sequence Read Archive (SRA), have been created to aid the development and expansion of centralized repositories. Although the central resource databases are under continual development, they do not include automatic pipelines to increase annotation of newly deposited data. Therefore, third-party applications are required to achieve that aim. Here, we present an automatic workflow and web application for the annotation of transcriptome data. The workflow creates secondary data such as sequencing reads and BLAST alignments, which are available through the web application. They are based on freely available bioinformatics tools and scripts developed in-house. The interactive web application provides a search engine and several browser utilities. Graphical views of transcript alignments are available through SeqViewer, an embedded tool developed by NCBI for viewing biological sequence data. The web application is tightly integrated with other NCBI web applications and tools to extend the functionality of data processing and interconnectivity. We present a case study for the species Physalis peruviana with data generated from BioProject ID 67621. URL: http://www.ncbi.nlm.nih.gov/projects/physalis/. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

  8. BGD: a database of bat genomes.

    Science.gov (United States)

    Fang, Jianfei; Wang, Xuan; Mu, Shuo; Zhang, Shuyi; Dong, Dong

    2015-01-01

    Bats account for ~20% of mammalian species, and are the only mammals with true powered flight. For the sake of their specialized phenotypic traits, many researches have been devoted to examine the evolution of bats. Until now, some whole genome sequences of bats have been assembled and annotated, however, a uniform resource for the annotated bat genomes is still unavailable. To make the extensive data associated with the bat genomes accessible to the general biological communities, we established a Bat Genome Database (BGD). BGD is an open-access, web-available portal that integrates available data of bat genomes and genes. It hosts data from six bat species, including two megabats and four microbats. Users can query the gene annotations using efficient searching engine, and it offers browsable tracks of bat genomes. Furthermore, an easy-to-use phylogenetic analysis tool was also provided to facilitate online phylogeny study of genes. To the best of our knowledge, BGD is the first database of bat genomes. It will extend our understanding of the bat evolution and be advantageous to the bat sequences analysis. BGD is freely available at: http://donglab.ecnu.edu.cn/databases/BatGenome/.

  9. BGD: a database of bat genomes.

    Directory of Open Access Journals (Sweden)

    Jianfei Fang

    Full Text Available Bats account for ~20% of mammalian species, and are the only mammals with true powered flight. For the sake of their specialized phenotypic traits, many researches have been devoted to examine the evolution of bats. Until now, some whole genome sequences of bats have been assembled and annotated, however, a uniform resource for the annotated bat genomes is still unavailable. To make the extensive data associated with the bat genomes accessible to the general biological communities, we established a Bat Genome Database (BGD. BGD is an open-access, web-available portal that integrates available data of bat genomes and genes. It hosts data from six bat species, including two megabats and four microbats. Users can query the gene annotations using efficient searching engine, and it offers browsable tracks of bat genomes. Furthermore, an easy-to-use phylogenetic analysis tool was also provided to facilitate online phylogeny study of genes. To the best of our knowledge, BGD is the first database of bat genomes. It will extend our understanding of the bat evolution and be advantageous to the bat sequences analysis. BGD is freely available at: http://donglab.ecnu.edu.cn/databases/BatGenome/.

  10. dbCAN2: a meta server for automated carbohydrate-active enzyme annotation

    DEFF Research Database (Denmark)

    Zhang, Han; Yohe, Tanner; Huang, Le

    2018-01-01

    of plant and plant-associated microbial genomes and metagenomes being sequenced, there is an urgent need of automatic tools for genomic data mining of CAZymes. We developed the dbCAN web server in 2012 to provide a public service for automated CAZyme annotation for newly sequenced genomes. Here, dbCAN2...... (http://cys.bios.niu.edu/dbCAN2) is presented as an updated meta server, which integrates three state-of-the-art tools for CAZome (all CAZymes of a genome) annotation: (i) HMMER search against the dbCAN HMM (hidden Markov model) database; (ii) DIAMOND search against the CAZy pre-annotated CAZyme...

  11. ECMDB: The E. coli Metabolome Database

    OpenAIRE

    Guo, An Chi; Jewison, Timothy; Wilson, Michael; Liu, Yifeng; Knox, Craig; Djoumbou, Yannick; Lo, Patrick; Mandal, Rupasri; Krishnamurthy, Ram; Wishart, David S.

    2012-01-01

    The Escherichia coli Metabolome Database (ECMDB, http://www.ecmdb.ca) is a comprehensively annotated metabolomic database containing detailed information about the metabolome of E. coli (K-12). Modelled closely on the Human and Yeast Metabolome Databases, the ECMDB contains >2600 metabolites with links to ?1500 different genes and proteins, including enzymes and transporters. The information in the ECMDB has been collected from dozens of textbooks, journal articles and electronic databases. E...

  12. Accessing the SEED genome databases via Web services API: tools for programmers.

    Science.gov (United States)

    Disz, Terry; Akhter, Sajia; Cuevas, Daniel; Olson, Robert; Overbeek, Ross; Vonstein, Veronika; Stevens, Rick; Edwards, Robert A

    2010-06-14

    The SEED integrates many publicly available genome sequences into a single resource. The database contains accurate and up-to-date annotations based on the subsystems concept that leverages clustering between genomes and other clues to accurately and efficiently annotate microbial genomes. The backend is used as the foundation for many genome annotation tools, such as the Rapid Annotation using Subsystems Technology (RAST) server for whole genome annotation, the metagenomics RAST server for random community genome annotations, and the annotation clearinghouse for exchanging annotations from different resources. In addition to a web user interface, the SEED also provides Web services based API for programmatic access to the data in the SEED, allowing the development of third-party tools and mash-ups. The currently exposed Web services encompass over forty different methods for accessing data related to microbial genome annotations. The Web services provide comprehensive access to the database back end, allowing any programmer access to the most consistent and accurate genome annotations available. The Web services are deployed using a platform independent service-oriented approach that allows the user to choose the most suitable programming platform for their application. Example code demonstrate that Web services can be used to access the SEED using common bioinformatics programming languages such as Perl, Python, and Java. We present a novel approach to access the SEED database. Using Web services, a robust API for access to genomics data is provided, without requiring large volume downloads all at once. The API ensures timely access to the most current datasets available, including the new genomes as soon as they come online.

  13. Gene coexpression network analysis as a source of functional annotation for rice genes.

    Directory of Open Access Journals (Sweden)

    Kevin L Childs

    Full Text Available With the existence of large publicly available plant gene expression data sets, many groups have undertaken data analyses to construct gene coexpression networks and functionally annotate genes. Often, a large compendium of unrelated or condition-independent expression data is used to construct gene networks. Condition-dependent expression experiments consisting of well-defined conditions/treatments have also been used to create coexpression networks to help examine particular biological processes. Gene networks derived from either condition-dependent or condition-independent data can be difficult to interpret if a large number of genes and connections are present. However, algorithms exist to identify modules of highly connected and biologically relevant genes within coexpression networks. In this study, we have used publicly available rice (Oryza sativa gene expression data to create gene coexpression networks using both condition-dependent and condition-independent data and have identified gene modules within these networks using the Weighted Gene Coexpression Network Analysis method. We compared the number of genes assigned to modules and the biological interpretability of gene coexpression modules to assess the utility of condition-dependent and condition-independent gene coexpression networks. For the purpose of providing functional annotation to rice genes, we found that gene modules identified by coexpression analysis of condition-dependent gene expression experiments to be more useful than gene modules identified by analysis of a condition-independent data set. We have incorporated our results into the MSU Rice Genome Annotation Project database as additional expression-based annotation for 13,537 genes, 2,980 of which lack a functional annotation description. These results provide two new types of functional annotation for our database. Genes in modules are now associated with groups of genes that constitute a collective functional

  14. Improving decoy databases for protein folding algorithms

    KAUST Repository

    Lindsey, Aaron; Yeh, Hsin-Yi (Cindy); Wu, Chih-Peng; Thomas, Shawna; Amato, Nancy M.

    2014-01-01

    energetically stable) from non-native structures. Decoy databases are collections of non-native structures used to test and verify these functions. We present a method to evaluate and improve the quality of decoy databases by adding novel structures and removing

  15. Harnessing Collaborative Annotations on Online Formative Assessments

    Science.gov (United States)

    Lin, Jian-Wei; Lai, Yuan-Cheng

    2013-01-01

    This paper harnesses collaborative annotations by students as learning feedback on online formative assessments to improve the learning achievements of students. Through the developed Web platform, students can conduct formative assessments, collaboratively annotate, and review historical records in a convenient way, while teachers can generate…

  16. Orchid: a novel management, annotation and machine learning framework for analyzing cancer mutations.

    Science.gov (United States)

    Cario, Clinton L; Witte, John S

    2018-03-15

    As whole-genome tumor sequence and biological annotation datasets grow in size, number and content, there is an increasing basic science and clinical need for efficient and accurate data management and analysis software. With the emergence of increasingly sophisticated data stores, execution environments and machine learning algorithms, there is also a need for the integration of functionality across frameworks. We present orchid, a python based software package for the management, annotation and machine learning of cancer mutations. Building on technologies of parallel workflow execution, in-memory database storage and machine learning analytics, orchid efficiently handles millions of mutations and hundreds of features in an easy-to-use manner. We describe the implementation of orchid and demonstrate its ability to distinguish tissue of origin in 12 tumor types based on 339 features using a random forest classifier. Orchid and our annotated tumor mutation database are freely available at https://github.com/wittelab/orchid. Software is implemented in python 2.7, and makes use of MySQL or MemSQL databases. Groovy 2.4.5 is optionally required for parallel workflow execution. JWitte@ucsf.edu. Supplementary data are available at Bioinformatics online.

  17. MIPS: analysis and annotation of proteins from whole genomes in 2005.

    Science.gov (United States)

    Mewes, H W; Frishman, D; Mayer, K F X; Münsterkötter, M; Noubibou, O; Pagel, P; Rattei, T; Oesterheld, M; Ruepp, A; Stümpflen, V

    2006-01-01

    The Munich Information Center for Protein Sequences (MIPS at the GSF), Neuherberg, Germany, provides resources related to genome information. Manually curated databases for several reference organisms are maintained. Several of these databases are described elsewhere in this and other recent NAR database issues. In a complementary effort, a comprehensive set of >400 genomes automatically annotated with the PEDANT system are maintained. The main goal of our current work on creating and maintaining genome databases is to extend gene centered information to information on interactions within a generic comprehensive framework. We have concentrated our efforts along three lines (i) the development of suitable comprehensive data structures and database technology, communication and query tools to include a wide range of different types of information enabling the representation of complex information such as functional modules or networks Genome Research Environment System, (ii) the development of databases covering computable information such as the basic evolutionary relations among all genes, namely SIMAP, the sequence similarity matrix and the CABiNet network analysis framework and (iii) the compilation and manual annotation of information related to interactions such as protein-protein interactions or other types of relations (e.g. MPCDB, MPPI, CYGD). All databases described and the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.gsf.de).

  18. Molecular signatures database (MSigDB) 3.0.

    Science.gov (United States)

    Liberzon, Arthur; Subramanian, Aravind; Pinchback, Reid; Thorvaldsdóttir, Helga; Tamayo, Pablo; Mesirov, Jill P

    2011-06-15

    Well-annotated gene sets representing the universe of the biological processes are critical for meaningful and insightful interpretation of large-scale genomic data. The Molecular Signatures Database (MSigDB) is one of the most widely used repositories of such sets. We report the availability of a new version of the database, MSigDB 3.0, with over 6700 gene sets, a complete revision of the collection of canonical pathways and experimental signatures from publications, enhanced annotations and upgrades to the web site. MSigDB is freely available for non-commercial use at http://www.broadinstitute.org/msigdb.

  19. Propagating annotations of molecular networks using in silico fragmentation.

    Science.gov (United States)

    da Silva, Ricardo R; Wang, Mingxun; Nothias, Louis-Félix; van der Hooft, Justin J J; Caraballo-Rodríguez, Andrés Mauricio; Fox, Evan; Balunas, Marcy J; Klassen, Jonathan L; Lopes, Norberto Peporine; Dorrestein, Pieter C

    2018-04-18

    The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp.

  20. Metab2MeSH: annotating compounds with medical subject headings.

    Science.gov (United States)

    Sartor, Maureen A; Ade, Alex; Wright, Zach; States, David; Omenn, Gilbert S; Athey, Brian; Karnovsky, Alla

    2012-05-15

    Progress in high-throughput genomic technologies has led to the development of a variety of resources that link genes to functional information contained in the biomedical literature. However, tools attempting to link small molecules to normal and diseased physiology and published data relevant to biologists and clinical investigators, are still lacking. With metabolomics rapidly emerging as a new omics field, the task of annotating small molecule metabolites becomes highly relevant. Our tool Metab2MeSH uses a statistical approach to reliably and automatically annotate compounds with concepts defined in Medical Subject Headings, and the National Library of Medicine's controlled vocabulary for biomedical concepts. These annotations provide links from compounds to biomedical literature and complement existing resources such as PubChem and the Human Metabolome Database.

  1. Citrus sinensis annotation project (CAP): a comprehensive database for sweet orange genome.

    Science.gov (United States)

    Wang, Jia; Chen, Dijun; Lei, Yang; Chang, Ji-Wei; Hao, Bao-Hai; Xing, Feng; Li, Sen; Xu, Qiang; Deng, Xiu-Xin; Chen, Ling-Ling

    2014-01-01

    Citrus is one of the most important and widely grown fruit crop with global production ranking firstly among all the fruit crops in the world. Sweet orange accounts for more than half of the Citrus production both in fresh fruit and processed juice. We have sequenced the draft genome of a double-haploid sweet orange (C. sinensis cv. Valencia), and constructed the Citrus sinensis annotation project (CAP) to store and visualize the sequenced genomic and transcriptome data. CAP provides GBrowse-based organization of sweet orange genomic data, which integrates ab initio gene prediction, EST, RNA-seq and RNA-paired end tag (RNA-PET) evidence-based gene annotation. Furthermore, we provide a user-friendly web interface to show the predicted protein-protein interactions (PPIs) and metabolic pathways in sweet orange. CAP provides comprehensive information beneficial to the researchers of sweet orange and other woody plants, which is freely available at http://citrus.hzau.edu.cn/.

  2. Semantic annotation in biomedicine: the current landscape.

    Science.gov (United States)

    Jovanović, Jelena; Bagheri, Ebrahim

    2017-09-22

    The abundance and unstructured nature of biomedical texts, be it clinical or research content, impose significant challenges for the effective and efficient use of information and knowledge stored in such texts. Annotation of biomedical documents with machine intelligible semantics facilitates advanced, semantics-based text management, curation, indexing, and search. This paper focuses on annotation of biomedical entity mentions with concepts from relevant biomedical knowledge bases such as UMLS. As a result, the meaning of those mentions is unambiguously and explicitly defined, and thus made readily available for automated processing. This process is widely known as semantic annotation, and the tools that perform it are known as semantic annotators.Over the last dozen years, the biomedical research community has invested significant efforts in the development of biomedical semantic annotation technology. Aiming to establish grounds for further developments in this area, we review a selected set of state of the art biomedical semantic annotators, focusing particularly on general purpose annotators, that is, semantic annotation tools that can be customized to work with texts from any area of biomedicine. We also examine potential directions for further improvements of today's annotators which could make them even more capable of meeting the needs of real-world applications. To motivate and encourage further developments in this area, along the suggested and/or related directions, we review existing and potential practical applications and benefits of semantic annotators.

  3. RICD: A rice indica cDNA database resource for rice functional genomics

    Directory of Open Access Journals (Sweden)

    Zhang Qifa

    2008-11-01

    Full Text Available Abstract Background The Oryza sativa L. indica subspecies is the most widely cultivated rice. During the last few years, we have collected over 20,000 putative full-length cDNAs and over 40,000 ESTs isolated from various cDNA libraries of two indica varieties Guangluai 4 and Minghui 63. A database of the rice indica cDNAs was therefore built to provide a comprehensive web data source for searching and retrieving the indica cDNA clones. Results Rice Indica cDNA Database (RICD is an online MySQL-PHP driven database with a user-friendly web interface. It allows investigators to query the cDNA clones by keyword, genome position, nucleotide or protein sequence, and putative function. It also provides a series of information, including sequences, protein domain annotations, similarity search results, SNPs and InDels information, and hyperlinks to gene annotation in both The Rice Annotation Project Database (RAP-DB and The TIGR Rice Genome Annotation Resource, expression atlas in RiceGE and variation report in Gramene of each cDNA. Conclusion The online rice indica cDNA database provides cDNA resource with comprehensive information to researchers for functional analysis of indica subspecies and for comparative genomics. The RICD database is available through our website http://www.ncgr.ac.cn/ricd.

  4. Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data

    Directory of Open Access Journals (Sweden)

    Tu Kang

    2007-06-01

    Full Text Available Abstract Background The wide use of Affymetrix microarray in broadened fields of biological research has made the probeset annotation an important issue. Standard Affymetrix probeset annotation is at gene level, i.e. a probeset is precisely linked to a gene, and probeset intensity is interpreted as gene expression. The increased knowledge that one gene may have multiple transcript variants clearly brings up the necessity of updating this gene-level annotation to a refined transcript-level. Results Through performing rigorous alignments of the Affymetrix probe sequences against a comprehensive pool of currently available transcript sequences, and further linking the probesets to the International Protein Index, we generated transcript-level or protein-level annotation tables for two popular Affymetrix expression arrays, Mouse Genome 430A 2.0 Array and Human Genome U133A Array. Application of our new annotations in re-examining existing expression data sets shows increased expression consistency among synonymous probesets and strengthened expression correlation between interacting proteins. Conclusion By refining the standard Affymetrix annotation of microarray probesets from the gene level to the transcript level and protein level, one can achieve a more reliable interpretation of their experimental data, which may lead to discovery of more profound regulatory mechanism.

  5. EXTRACT: interactive extraction of environment metadata and term suggestion for metagenomic sample annotation.

    Science.gov (United States)

    Pafilis, Evangelos; Buttigieg, Pier Luigi; Ferrell, Barbra; Pereira, Emiliano; Schnetzer, Julia; Arvanitidis, Christos; Jensen, Lars Juhl

    2016-01-01

    The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have therefore developed an interactive annotation tool, EXTRACT, which helps curators identify and extract standard-compliant terms for annotation of metagenomic records and other samples. Behind its web-based user interface, the system combines published methods for named entity recognition of environment, organism, tissue and disease terms. The evaluators in the BioCreative V Interactive Annotation Task found the system to be intuitive, useful, well documented and sufficiently accurate to be helpful in spotting relevant text passages and extracting organism and environment terms. Comparison of fully manual and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed. Database URL: https://extract.hcmr.gr/. © The Author(s) 2016. Published by Oxford University Press.

  6. LeishCyc: a biochemical pathways database for Leishmania major

    Directory of Open Access Journals (Sweden)

    Doyle Maria A

    2009-06-01

    Full Text Available Abstract Background Leishmania spp. are sandfly transmitted protozoan parasites that cause a spectrum of diseases in more than 12 million people worldwide. Much research is now focusing on how these parasites adapt to the distinct nutrient environments they encounter in the digestive tract of the sandfly vector and the phagolysosome compartment of mammalian macrophages. While data mining and annotation of the genomes of three Leishmania species has provided an initial inventory of predicted metabolic components and associated pathways, resources for integrating this information into metabolic networks and incorporating data from transcript, protein, and metabolite profiling studies is currently lacking. The development of a reliable, expertly curated, and widely available model of Leishmania metabolic networks is required to facilitate systems analysis, as well as discovery and prioritization of new drug targets for this important human pathogen. Description The LeishCyc database was initially built from the genome sequence of Leishmania major (v5.2, based on the annotation published by the Wellcome Trust Sanger Institute. LeishCyc was manually curated to remove errors, correct automated predictions, and add information from the literature. The ongoing curation is based on public sources, literature searches, and our own experimental and bioinformatics studies. In a number of instances we have improved on the original genome annotation, and, in some ambiguous cases, collected relevant information from the literature in order to help clarify gene or protein annotation in the future. All genes in LeishCyc are linked to the corresponding entry in GeneDB (Wellcome Trust Sanger Institute. Conclusion The LeishCyc database describes Leishmania major genes, gene products, metabolites, their relationships and biochemical organization into metabolic pathways. LeishCyc provides a systematic approach to organizing the evolving information about Leishmania

  7. Bridging the Gap: Enriching YouTube Videos with Jazz Music Annotations

    Directory of Open Access Journals (Sweden)

    Stefan Balke

    2018-02-01

    Full Text Available Web services allow permanent access to music from all over the world. Especially in the case of web services with user-supplied content, e.g., YouTube™, the available metadata is often incomplete or erroneous. On the other hand, a vast amount of high-quality and musically relevant metadata has been annotated in research areas such as Music Information Retrieval (MIR. Although they have great potential, these musical annotations are often inaccessible to users outside the academic world. With our contribution, we want to bridge this gap by enriching publicly available multimedia content with musical annotations available in research corpora, while maintaining easy access to the underlying data. Our web-based tools offer researchers and music lovers novel possibilities to interact with and navigate through the content. In this paper, we consider a research corpus called the Weimar Jazz Database (WJD as an illustrating example scenario. The WJD contains various annotations related to famous jazz solos. First, we establish a link between the WJD annotations and corresponding YouTube videos employing existing retrieval techniques. With these techniques, we were able to identify 988 corresponding YouTube videos for 329 solos out of 456 solos contained in the WJD. We then embed the retrieved videos in a recently developed web-based platform and enrich the videos with solo transcriptions that are part of the WJD. Furthermore, we integrate publicly available data resources from the Semantic Web in order to extend the presented information, for example, with a detailed discography or artists-related information. Our contribution illustrates the potential of modern web-based technologies for the digital humanities, and novel ways for improving access and interaction with digitized multimedia content.

  8. A robust data-driven approach for gene ontology annotation.

    Science.gov (United States)

    Li, Yanpeng; Yu, Hong

    2014-01-01

    Gene ontology (GO) and GO annotation are important resources for biological information management and knowledge discovery, but the speed of manual annotation became a major bottleneck of database curation. BioCreative IV GO annotation task aims to evaluate the performance of system that automatically assigns GO terms to genes based on the narrative sentences in biomedical literature. This article presents our work in this task as well as the experimental results after the competition. For the evidence sentence extraction subtask, we built a binary classifier to identify evidence sentences using reference distance estimator (RDE), a recently proposed semi-supervised learning method that learns new features from around 10 million unlabeled sentences, achieving an F1 of 19.3% in exact match and 32.5% in relaxed match. In the post-submission experiment, we obtained 22.1% and 35.7% F1 performance by incorporating bigram features in RDE learning. In both development and test sets, RDE-based method achieved over 20% relative improvement on F1 and AUC performance against classical supervised learning methods, e.g. support vector machine and logistic regression. For the GO term prediction subtask, we developed an information retrieval-based method to retrieve the GO term most relevant to each evidence sentence using a ranking function that combined cosine similarity and the frequency of GO terms in documents, and a filtering method based on high-level GO classes. The best performance of our submitted runs was 7.8% F1 and 22.2% hierarchy F1. We found that the incorporation of frequency information and hierarchy filtering substantially improved the performance. In the post-submission evaluation, we obtained a 10.6% F1 using a simpler setting. Overall, the experimental analysis showed our approaches were robust in both the two tasks. © The Author(s) 2014. Published by Oxford University Press.

  9. MetReS, an Efficient Database for Genomic Applications.

    Science.gov (United States)

    Vilaplana, Jordi; Alves, Rui; Solsona, Francesc; Mateo, Jordi; Teixidó, Ivan; Pifarré, Marc

    2018-02-01

    MetReS (Metabolic Reconstruction Server) is a genomic database that is shared between two software applications that address important biological problems. Biblio-MetReS is a data-mining tool that enables the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (re)annotation of proteomes, to properly identify both the individual proteins involved in the processes of interest and their function. The main goal of this work was to identify the areas where the performance of the MetReS database performance could be improved and to test whether this improvement would scale to larger datasets and more complex types of analysis. The study was started with a relational database, MySQL, which is the current database server used by the applications. We also tested the performance of an alternative data-handling framework, Apache Hadoop. Hadoop is currently used for large-scale data processing. We found that this data handling framework is likely to greatly improve the efficiency of the MetReS applications as the dataset and the processing needs increase by several orders of magnitude, as expected to happen in the near future.

  10. Plant Protein Annotation in the UniProt Knowledgebase1

    Science.gov (United States)

    Schneider, Michel; Bairoch, Amos; Wu, Cathy H.; Apweiler, Rolf

    2005-01-01

    The Swiss-Prot, TrEMBL, Protein Information Resource (PIR), and DNA Data Bank of Japan (DDBJ) protein database activities have united to form the Universal Protein Resource (UniProt) Consortium. UniProt presents three database layers: the UniProt Archive, the UniProt Knowledgebase (UniProtKB), and the UniProt Reference Clusters. The UniProtKB consists of two sections: UniProtKB/Swiss-Prot (fully manually curated entries) and UniProtKB/TrEMBL (automated annotation, classification and extensive cross-references). New releases are published fortnightly. A specific Plant Proteome Annotation Program (http://www.expasy.org/sprot/ppap/) was initiated to cope with the increasing amount of data produced by the complete sequencing of plant genomes. Through UniProt, our aim is to provide the scientific community with a single, centralized, authoritative resource for protein sequences and functional information that will allow the plant community to fully explore and utilize the wealth of information available for both plant and nonplant model organisms. PMID:15888679

  11. Database citation in full text biomedical articles.

    Science.gov (United States)

    Kafkas, Şenay; Kim, Jee-Hyub; McEntyre, Johanna R

    2013-01-01

    Molecular biology and literature databases represent essential infrastructure for life science research. Effective integration of these data resources requires that there are structured cross-references at the level of individual articles and biological records. Here, we describe the current patterns of how database entries are cited in research articles, based on analysis of the full text Open Access articles available from Europe PMC. Focusing on citation of entries in the European Nucleotide Archive (ENA), UniProt and Protein Data Bank, Europe (PDBe), we demonstrate that text mining doubles the number of structured annotations of database record citations supplied in journal articles by publishers. Many thousands of new literature-database relationships are found by text mining, since these relationships are also not present in the set of articles cited by database records. We recommend that structured annotation of database records in articles is extended to other databases, such as ArrayExpress and Pfam, entries from which are also cited widely in the literature. The very high precision and high-throughput of this text-mining pipeline makes this activity possible both accurately and at low cost, which will allow the development of new integrated data services.

  12. Expression profiling of hypothetical genes in Desulfovibrio vulgaris leads to improved functional annotation

    Energy Technology Data Exchange (ETDEWEB)

    Elias, Dwayne A.; Mukhopadhyay, Aindrila; Joachimiak, Marcin P.; Drury, Elliott C.; Redding, Alyssa M.; Yen, Huei-Che B.; Fields, Matthew W.; Hazen, Terry C.; Arkin, Adam P.; Keasling, Jay D.; Wall, Judy D.

    2008-10-27

    Hypothetical and conserved hypothetical genes account for>30percent of sequenced bacterial genomes. For the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, 347 of the 3634 genes were annotated as conserved hypothetical (9.5percent) along with 887 hypothetical genes (24.4percent). Given the large fraction of the genome, it is plausible that some of these genes serve critical cellular roles. The study goals were to determine which genes were expressed and provide a more functionally based annotation. To accomplish this, expression profiles of 1234 hypothetical and conserved genes were used from transcriptomic datasets of 11 environmental stresses, complemented with shotgun LC-MS/MS and AMT tag proteomic data. Genes were divided into putatively polycistronic operons and those predicted to be monocistronic, then classified by basal expression levels and grouped according to changes in expression for one or multiple stresses. 1212 of these genes were transcribed with 786 producing detectable proteins. There was no evidence for expression of 17 predicted genes. Except for the latter, monocistronic gene annotation was expanded using the above criteria along with matching Clusters of Orthologous Groups. Polycistronic genes were annotated in the same manner with inferences from their proximity to more confidently annotated genes. Two targeted deletion mutants were used as test cases to determine the relevance of the inferred functional annotations.

  13. A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

    Science.gov (United States)

    Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L

    2018-01-01

    The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.

  14. Studying Oogenesis in a Non-model Organism Using Transcriptomics: Assembling, Annotating, and Analyzing Your Data.

    Science.gov (United States)

    Carter, Jean-Michel; Gibbs, Melanie; Breuker, Casper J

    2016-01-01

    This chapter provides a guide to processing and analyzing RNA-Seq data in a non-model organism. This approach was implemented for studying oogenesis in the Speckled Wood Butterfly Pararge aegeria. We focus in particular on how to perform a more informative primary annotation of your non-model organism by implementing our multi-BLAST annotation strategy. We also provide a general guide to other essential steps in the next-generation sequencing analysis workflow. Before undertaking these methods, we recommend you familiarize yourself with command line usage and fundamental concepts of database handling. Most of the operations in the primary annotation pipeline can be performed in Galaxy (or equivalent standalone versions of the tools) and through the use of common database operations (e.g. to remove duplicates) but other equivalent programs and/or custom scripts can be implemented for further automation.

  15. Automating Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob L.; Hohimer, Ryan E.; White, Amanda M.

    2006-01-22

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  16. The UCSC Genome Browser Database: 2008 update

    DEFF Research Database (Denmark)

    Karolchik, D; Kuhn, R M; Baertsch, R

    2007-01-01

    The University of California, Santa Cruz, Genome Browser Database (GBD) provides integrated sequence and annotation data for a large collection of vertebrate and model organism genomes. Seventeen new assemblies have been added to the database in the past year, for a total coverage of 19 vertebrat...

  17. GarlicESTdb: an online database and mining tool for garlic EST sequences

    Directory of Open Access Journals (Sweden)

    Choi Sang-Haeng

    2009-05-01

    Full Text Available Abstract Background Allium sativum., commonly known as garlic, is a species in the onion genus (Allium, which is a large and diverse one containing over 1,250 species. Its close relatives include chives, onion, leek and shallot. Garlic has been used throughout recorded history for culinary, medicinal use and health benefits. Currently, the interest in garlic is highly increasing due to nutritional and pharmaceutical value including high blood pressure and cholesterol, atherosclerosis and cancer. For all that, there are no comprehensive databases available for Expressed Sequence Tags(EST of garlic for gene discovery and future efforts of genome annotation. That is why we developed a new garlic database and applications to enable comprehensive analysis of garlic gene expression. Description GarlicESTdb is an integrated database and mining tool for large-scale garlic (Allium sativum EST sequencing. A total of 21,595 ESTs collected from an in-house cDNA library were used to construct the database. The analysis pipeline is an automated system written in JAVA and consists of the following components: automatic preprocessing of EST reads, assembly of raw sequences, annotation of the assembled sequences, storage of the analyzed information into MySQL databases, and graphic display of all processed data. A web application was implemented with the latest J2EE (Java 2 Platform Enterprise Edition software technology (JSP/EJB/JavaServlet for browsing and querying the database, for creation of dynamic web pages on the client side, and for mapping annotated enzymes to KEGG pathways, the AJAX framework was also used partially. The online resources, such as putative annotation, single nucleotide polymorphisms (SNP and tandem repeat data sets, can be searched by text, explored on the website, searched using BLAST, and downloaded. To archive more significant BLAST results, a curation system was introduced with which biologists can easily edit best-hit annotation

  18. GarlicESTdb: an online database and mining tool for garlic EST sequences.

    Science.gov (United States)

    Kim, Dae-Won; Jung, Tae-Sung; Nam, Seong-Hyeuk; Kwon, Hyuk-Ryul; Kim, Aeri; Chae, Sung-Hwa; Choi, Sang-Haeng; Kim, Dong-Wook; Kim, Ryong Nam; Park, Hong-Seog

    2009-05-18

    Allium sativum., commonly known as garlic, is a species in the onion genus (Allium), which is a large and diverse one containing over 1,250 species. Its close relatives include chives, onion, leek and shallot. Garlic has been used throughout recorded history for culinary, medicinal use and health benefits. Currently, the interest in garlic is highly increasing due to nutritional and pharmaceutical value including high blood pressure and cholesterol, atherosclerosis and cancer. For all that, there are no comprehensive databases available for Expressed Sequence Tags(EST) of garlic for gene discovery and future efforts of genome annotation. That is why we developed a new garlic database and applications to enable comprehensive analysis of garlic gene expression. GarlicESTdb is an integrated database and mining tool for large-scale garlic (Allium sativum) EST sequencing. A total of 21,595 ESTs collected from an in-house cDNA library were used to construct the database. The analysis pipeline is an automated system written in JAVA and consists of the following components: automatic preprocessing of EST reads, assembly of raw sequences, annotation of the assembled sequences, storage of the analyzed information into MySQL databases, and graphic display of all processed data. A web application was implemented with the latest J2EE (Java 2 Platform Enterprise Edition) software technology (JSP/EJB/JavaServlet) for browsing and querying the database, for creation of dynamic web pages on the client side, and for mapping annotated enzymes to KEGG pathways, the AJAX framework was also used partially. The online resources, such as putative annotation, single nucleotide polymorphisms (SNP) and tandem repeat data sets, can be searched by text, explored on the website, searched using BLAST, and downloaded. To archive more significant BLAST results, a curation system was introduced with which biologists can easily edit best-hit annotation information for others to view. The Garlic

  19. SoyDB: a knowledge database of soybean transcription factors

    Directory of Open Access Journals (Sweden)

    Valliyodan Babu

    2010-01-01

    Full Text Available Abstract Background Transcription factors play the crucial rule of regulating gene expression and influence almost all biological processes. Systematically identifying and annotating transcription factors can greatly aid further understanding their functions and mechanisms. In this article, we present SoyDB, a user friendly database containing comprehensive knowledge of soybean transcription factors. Description The soybean genome was recently sequenced by the Department of Energy-Joint Genome Institute (DOE-JGI and is publicly available. Mining of this sequence identified 5,671 soybean genes as putative transcription factors. These genes were comprehensively annotated as an aid to the soybean research community. We developed SoyDB - a knowledge database for all the transcription factors in the soybean genome. The database contains protein sequences, predicted tertiary structures, putative DNA binding sites, domains, homologous templates in the Protein Data Bank (PDB, protein family classifications, multiple sequence alignments, consensus protein sequence motifs, web logo of each family, and web links to the soybean transcription factor database PlantTFDB, known EST sequences, and other general protein databases including Swiss-Prot, Gene Ontology, KEGG, EMBL, TAIR, InterPro, SMART, PROSITE, NCBI, and Pfam. The database can be accessed via an interactive and convenient web server, which supports full-text search, PSI-BLAST sequence search, database browsing by protein family, and automatic classification of a new protein sequence into one of 64 annotated transcription factor families by hidden Markov models. Conclusions A comprehensive soybean transcription factor database was constructed and made publicly accessible at http://casp.rnet.missouri.edu/soydb/.

  20. ToxGen: an improved reference database for the identification of type B-trichothecene genotypes in Fusarium

    Directory of Open Access Journals (Sweden)

    Tomasz Kulik

    2017-02-01

    Full Text Available Type B trichothecenes, which pose a serious hazard to consumer health, occur worldwide in grains. These mycotoxins are produced mainly by three different trichothecene genotypes/chemotypes: 3ADON (3-acetyldeoxynivalenol, 15ADON (15-acetyldeoxynivalenol and NIV (nivalenol, named after these three major mycotoxin compounds. Correct identification of these genotypes is elementary for all studies relating to population surveys, fungal ecology and mycotoxicology. Trichothecene producers exhibit enormous strain-dependent chemical diversity, which may result in variation in levels of the genotype’s determining toxin and in the production of low to high amounts of atypical compounds. New high-throughput DNA-sequencing technologies promise to boost the diagnostics of mycotoxin genotypes. However, this requires a reference database containing a satisfactory taxonomic sampling of sequences showing high correlation to actually produced chemotypes. We believe that one of the most pressing current challenges of such a database is the linking of molecular identification with chemical diversity of the strains, as well as other metadata. In this study, we use the Tri12 gene involved in mycotoxin biosynthesis for identification of Tri genotypes through sequence comparison. Tri12 sequences from a range of geographically diverse fungal strains comprising 22 Fusarium species were stored in the ToxGen database, which covers descriptive and up-to-date annotations such as indication on Tri genotype and chemotype of the strains, chemical diversity, information on trichothecene-inducing host, substrate or media, geographical locality, and most recent taxonomic affiliations. The present initiative bridges the gap between the demands of comprehensive studies on trichothecene producers and the existing nucleotide sequence databases, which lack toxicological and other auxiliary data. We invite researchers working in the fields of fungal taxonomy, epidemiology and

  1. ToxGen: an improved reference database for the identification of type B-trichothecene genotypes in Fusarium.

    Science.gov (United States)

    Kulik, Tomasz; Abarenkov, Kessy; Buśko, Maciej; Bilska, Katarzyna; van Diepeningen, Anne D; Ostrowska-Kołodziejczak, Anna; Krawczyk, Katarzyna; Brankovics, Balázs; Stenglein, Sebastian; Sawicki, Jakub; Perkowski, Juliusz

    2017-01-01

    Type B trichothecenes, which pose a serious hazard to consumer health, occur worldwide in grains. These mycotoxins are produced mainly by three different trichothecene genotypes/chemotypes: 3ADON (3-acetyldeoxynivalenol), 15ADON (15-acetyldeoxynivalenol) and NIV (nivalenol), named after these three major mycotoxin compounds. Correct identification of these genotypes is elementary for all studies relating to population surveys, fungal ecology and mycotoxicology. Trichothecene producers exhibit enormous strain-dependent chemical diversity, which may result in variation in levels of the genotype's determining toxin and in the production of low to high amounts of atypical compounds. New high-throughput DNA-sequencing technologies promise to boost the diagnostics of mycotoxin genotypes. However, this requires a reference database containing a satisfactory taxonomic sampling of sequences showing high correlation to actually produced chemotypes. We believe that one of the most pressing current challenges of such a database is the linking of molecular identification with chemical diversity of the strains, as well as other metadata. In this study, we use the Tri12 gene involved in mycotoxin biosynthesis for identification of Tri genotypes through sequence comparison. Tri12 sequences from a range of geographically diverse fungal strains comprising 22 Fusarium species were stored in the ToxGen database, which covers descriptive and up-to-date annotations such as indication on Tri genotype and chemotype of the strains, chemical diversity, information on trichothecene-inducing host, substrate or media, geographical locality, and most recent taxonomic affiliations. The present initiative bridges the gap between the demands of comprehensive studies on trichothecene producers and the existing nucleotide sequence databases, which lack toxicological and other auxiliary data. We invite researchers working in the fields of fungal taxonomy, epidemiology and mycotoxicology to join the

  2. Benchmarking database performance for genomic data.

    Science.gov (United States)

    Khushi, Matloob

    2015-06-01

    Genomic regions represent features such as gene annotations, transcription factor binding sites and epigenetic modifications. Performing various genomic operations such as identifying overlapping/non-overlapping regions or nearest gene annotations are common research needs. The data can be saved in a database system for easy management, however, there is no comprehensive database built-in algorithm at present to identify overlapping regions. Therefore I have developed a novel region-mapping (RegMap) SQL-based algorithm to perform genomic operations and have benchmarked the performance of different databases. Benchmarking identified that PostgreSQL extracts overlapping regions much faster than MySQL. Insertion and data uploads in PostgreSQL were also better, although general searching capability of both databases was almost equivalent. In addition, using the algorithm pair-wise, overlaps of >1000 datasets of transcription factor binding sites and histone marks, collected from previous publications, were reported and it was found that HNF4G significantly co-locates with cohesin subunit STAG1 (SA1).Inc. © 2015 Wiley Periodicals, Inc.

  3. Fast T Wave Detection Calibrated by Clinical Knowledge with Annotation of P and T Waves

    Directory of Open Access Journals (Sweden)

    Mohamed Elgendi

    2015-07-01

    Full Text Available Background: There are limited studies on the automatic detection of T waves in arrhythmic electrocardiogram (ECG signals. This is perhaps because there is no available arrhythmia dataset with annotated T waves. There is a growing need to develop numerically-efficient algorithms that can accommodate the new trend of battery-driven ECG devices. Moreover, there is also a need to analyze long-term recorded signals in a reliable and time-efficient manner, therefore improving the diagnostic ability of mobile devices and point-of-care technologies. Methods: Here, the T wave annotation of the well-known MIT-BIH arrhythmia database is discussed and provided. Moreover, a simple fast method for detecting T waves is introduced. A typical T wave detection method has been reduced to a basic approach consisting of two moving averages and dynamic thresholds. The dynamic thresholds were calibrated using four clinically known types of sinus node response to atrial premature depolarization (compensation, reset, interpolation, and reentry. Results: The determination of T wave peaks is performed and the proposed algorithm is evaluated on two well-known databases, the QT and MIT-BIH Arrhythmia databases. The detector obtained a sensitivity of 97.14% and a positive predictivity of 99.29% over the first lead of the validation databases (total of 221,186 beats. Conclusions: We present a simple yet very reliable T wave detection algorithm that can be potentially implemented on mobile battery-driven devices. In contrast to complex methods, it can be easily implemented in a digital filter design.

  4. Functional annotation of hierarchical modularity.

    Directory of Open Access Journals (Sweden)

    Kanchana Padmanabhan

    method using Saccharomyces cerevisiae data from KEGG and MIPS databases and several other computationally derived and curated datasets. The code and additional supplemental files can be obtained from http://code.google.com/p/functional-annotation-of-hierarchical-modularity/ (Accessed 2012 March 13.

  5. An automated system designed for large scale NMR data deposition and annotation: application to over 600 assigned chemical shift data entries to the BioMagResBank from the Riken Structural Genomics/Proteomics Initiative internal database

    International Nuclear Information System (INIS)

    Kobayashi, Naohiro; Harano, Yoko; Tochio, Naoya; Nakatani, Eiichi; Kigawa, Takanori; Yokoyama, Shigeyuki; Mading, Steve; Ulrich, Eldon L.; Markley, John L.; Akutsu, Hideo; Fujiwara, Toshimichi

    2012-01-01

    Biomolecular NMR chemical shift data are key information for the functional analysis of biomolecules and the development of new techniques for NMR studies utilizing chemical shift statistical information. Structural genomics projects are major contributors to the accumulation of protein chemical shift information. The management of the large quantities of NMR data generated by each project in a local database and the transfer of the data to the public databases are still formidable tasks because of the complicated nature of NMR data. Here we report an automated and efficient system developed for the deposition and annotation of a large number of data sets including 1 H, 13 C and 15 N resonance assignments used for the structure determination of proteins. We have demonstrated the feasibility of our system by applying it to over 600 entries from the internal database generated by the RIKEN Structural Genomics/Proteomics Initiative (RSGI) to the public database, BioMagResBank (BMRB). We have assessed the quality of the deposited chemical shifts by comparing them with those predicted from the PDB coordinate entry for the corresponding protein. The same comparison for other matched BMRB/PDB entries deposited from 2001–2011 has been carried out and the results suggest that the RSGI entries greatly improved the quality of the BMRB database. Since the entries include chemical shifts acquired under strikingly similar experimental conditions, these NMR data can be expected to be a promising resource to improve current technologies as well as to develop new NMR methods for protein studies.

  6. CTDB: An Integrated Chickpea Transcriptome Database for Functional and Applied Genomics.

    Directory of Open Access Journals (Sweden)

    Mohit Verma

    Full Text Available Chickpea is an important grain legume used as a rich source of protein in human diet. The narrow genetic diversity and limited availability of genomic resources are the major constraints in implementing breeding strategies and biotechnological interventions for genetic enhancement of chickpea. We developed an integrated Chickpea Transcriptome Database (CTDB, which provides the comprehensive web interface for visualization and easy retrieval of transcriptome data in chickpea. The database features many tools for similarity search, functional annotation (putative function, PFAM domain and gene ontology search and comparative gene expression analysis. The current release of CTDB (v2.0 hosts transcriptome datasets with high quality functional annotation from cultivated (desi and kabuli types and wild chickpea. A catalog of transcription factor families and their expression profiles in chickpea are available in the database. The gene expression data have been integrated to study the expression profiles of chickpea transcripts in major tissues/organs and various stages of flower development. The utilities, such as similarity search, ortholog identification and comparative gene expression have also been implemented in the database to facilitate comparative genomic studies among different legumes and Arabidopsis. Furthermore, the CTDB represents a resource for the discovery of functional molecular markers (microsatellites and single nucleotide polymorphisms between different chickpea types. We anticipate that integrated information content of this database will accelerate the functional and applied genomic research for improvement of chickpea. The CTDB web service is freely available at http://nipgr.res.in/ctdb.html.

  7. Linking human diseases to animal models using ontology-based phenotype annotation.

    Directory of Open Access Journals (Sweden)

    Nicole L Washington

    2009-11-01

    Full Text Available Scientists and clinicians who study genetic alterations and disease have traditionally described phenotypes in natural language. The considerable variation in these free-text descriptions has posed a hindrance to the important task of identifying candidate genes and models for human diseases and indicates the need for a computationally tractable method to mine data resources for mutant phenotypes. In this study, we tested the hypothesis that ontological annotation of disease phenotypes will facilitate the discovery of new genotype-phenotype relationships within and across species. To describe phenotypes using ontologies, we used an Entity-Quality (EQ methodology, wherein the affected entity (E and how it is affected (Q are recorded using terms from a variety of ontologies. Using this EQ method, we annotated the phenotypes of 11 gene-linked human diseases described in Online Mendelian Inheritance in Man (OMIM. These human annotations were loaded into our Ontology-Based Database (OBD along with other ontology-based phenotype descriptions of mutants from various model organism databases. Phenotypes recorded with this EQ method can be computationally compared based on the hierarchy of terms in the ontologies and the frequency of annotation. We utilized four similarity metrics to compare phenotypes and developed an ontology of homologous and analogous anatomical structures to compare phenotypes between species. Using these tools, we demonstrate that we can identify, through the similarity of the recorded phenotypes, other alleles of the same gene, other members of a signaling pathway, and orthologous genes and pathway members across species. We conclude that EQ-based annotation of phenotypes, in conjunction with a cross-species ontology, and a variety of similarity metrics can identify biologically meaningful similarities between genes by comparing phenotypes alone. This annotation and search method provides a novel and efficient means to identify

  8. Processing sequence annotation data using the Lua programming language.

    Science.gov (United States)

    Ueno, Yutaka; Arita, Masanori; Kumagai, Toshitaka; Asai, Kiyoshi

    2003-01-01

    The data processing language in a graphical software tool that manages sequence annotation data from genome databases should provide flexible functions for the tasks in molecular biology research. Among currently available languages we adopted the Lua programming language. It fulfills our requirements to perform computational tasks for sequence map layouts, i.e. the handling of data containers, symbolic reference to data, and a simple programming syntax. Upon importing a foreign file, the original data are first decomposed in the Lua language while maintaining the original data schema. The converted data are parsed by the Lua interpreter and the contents are stored in our data warehouse. Then, portions of annotations are selected and arranged into our catalog format to be depicted on the sequence map. Our sequence visualization program was successfully implemented, embedding the Lua language for processing of annotation data and layout script. The program is available at http://staff.aist.go.jp/yutaka.ueno/guppy/.

  9. DaMold: A data-mining platform for variant annotation and visualization in molecular diagnostics research.

    Science.gov (United States)

    Pandey, Ram Vinay; Pabinger, Stephan; Kriegner, Albert; Weinhäusel, Andreas

    2017-07-01

    Next-generation sequencing (NGS) has become a powerful and efficient tool for routine mutation screening in clinical research. As each NGS test yields hundreds of variants, the current challenge is to meaningfully interpret the data and select potential candidates. Analyzing each variant while manually investigating several relevant databases to collect specific information is a cumbersome and time-consuming process, and it requires expertise and familiarity with these databases. Thus, a tool that can seamlessly annotate variants with clinically relevant databases under one common interface would be of great help for variant annotation, cross-referencing, and visualization. This tool would allow variants to be processed in an automated and high-throughput manner and facilitate the investigation of variants in several genome browsers. Several analysis tools are available for raw sequencing-read processing and variant identification, but an automated variant filtering, annotation, cross-referencing, and visualization tool is still lacking. To fulfill these requirements, we developed DaMold, a Web-based, user-friendly tool that can filter and annotate variants and can access and compile information from 37 resources. It is easy to use, provides flexible input options, and accepts variants from NGS and Sanger sequencing as well as hotspots in VCF and BED formats. DaMold is available as an online application at http://damold.platomics.com/index.html, and as a Docker container and virtual machine at https://sourceforge.net/projects/damold/. © 2017 Wiley Periodicals, Inc.

  10. DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication.

    Science.gov (United States)

    Tanizawa, Yasuhiro; Fujisawa, Takatomo; Nakamura, Yasukazu

    2018-03-15

    We developed a prokaryotic genome annotation pipeline, DFAST, that also supports genome submission to public sequence databases. DFAST was originally started as an on-line annotation server, and to date, over 7000 jobs have been processed since its first launch in 2016. Here, we present a newly implemented background annotation engine for DFAST, which is also available as a standalone command-line program. The new engine can annotate a typical-sized bacterial genome within 10 min, with rich information such as pseudogenes, translation exceptions and orthologous gene assignment between given reference genomes. In addition, the modular framework of DFAST allows users to customize the annotation workflow easily and will also facilitate extensions for new functions and incorporation of new tools in the future. The software is implemented in Python 3 and runs in both Python 2.7 and 3.4-on Macintosh and Linux systems. It is freely available at https://github.com/nigyta/dfast_core/under the GPLv3 license with external binaries bundled in the software distribution. An on-line version is also available at https://dfast.nig.ac.jp/. yn@nig.ac.jp. Supplementary data are available at Bioinformatics online.

  11. Improving integrative searching of systems chemical biology data using semantic annotation.

    Science.gov (United States)

    Chen, Bin; Ding, Ying; Wild, David J

    2012-03-08

    Systems chemical biology and chemogenomics are considered critical, integrative disciplines in modern biomedical research, but require data mining of large, integrated, heterogeneous datasets from chemistry and biology. We previously developed an RDF-based resource called Chem2Bio2RDF that enabled querying of such data using the SPARQL query language. Whilst this work has proved useful in its own right as one of the first major resources in these disciplines, its utility could be greatly improved by the application of an ontology for annotation of the nodes and edges in the RDF graph, enabling a much richer range of semantic queries to be issued. We developed a generalized chemogenomics and systems chemical biology OWL ontology called Chem2Bio2OWL that describes the semantics of chemical compounds, drugs, protein targets, pathways, genes, diseases and side-effects, and the relationships between them. The ontology also includes data provenance. We used it to annotate our Chem2Bio2RDF dataset, making it a rich semantic resource. Through a series of scientific case studies we demonstrate how this (i) simplifies the process of building SPARQL queries, (ii) enables useful new kinds of queries on the data and (iii) makes possible intelligent reasoning and semantic graph mining in chemogenomics and systems chemical biology. Chem2Bio2OWL is available at http://chem2bio2rdf.org/owl. The document is available at http://chem2bio2owl.wikispaces.com.

  12. Gene Ontology annotation of the rice blast fungus, Magnaporthe oryzae

    Directory of Open Access Journals (Sweden)

    Deng Jixin

    2009-02-01

    were assigned to the 3 root terms. The Version 5 GO annotation is publically queryable via the GO site http://amigo.geneontology.org/cgi-bin/amigo/go.cgi. Additionally, the genome of M. oryzae is constantly being refined and updated as new information is incorporated. For the latest GO annotation of Version 6 genome, please visit our website http://scotland.fgl.ncsu.edu/smeng/GoAnnotationMagnaporthegrisea.html. The preliminary GO annotation of Version 6 genome is placed at a local MySql database that is publically queryable via a user-friendly interface Adhoc Query System. Conclusion Our analysis provides comprehensive and robust GO annotations of the M. oryzae genome assemblies that will be solid foundations for further functional interrogation of M. oryzae.

  13. Updating and improving the National Population Database to National Population Database 2

    OpenAIRE

    SMITH, Graham; FAIRBURN, Jonathan

    2008-01-01

    In 2004 Staffordshire University delivered the National Population Database for use in estimating populations at risk under the Control of Major Accident Hazards Regulations (COMAH). In 2006 an assessment of the updating and potential improvements to NPD was delivered to HSE. Between Autumn 2007 and Summer 2008 an implementation of the feasibility report led to the creation of National Population Database 2 which both updated and expanded the datasets contained in the original NPD. This repor...

  14. GDR (Genome Database for Rosaceae): integrated web-database for Rosaceae genomics and genetics data.

    Science.gov (United States)

    Jung, Sook; Staton, Margaret; Lee, Taein; Blenda, Anna; Svancara, Randall; Abbott, Albert; Main, Dorrie

    2008-01-01

    The Genome Database for Rosaceae (GDR) is a central repository of curated and integrated genetics and genomics data of Rosaceae, an economically important family which includes apple, cherry, peach, pear, raspberry, rose and strawberry. GDR contains annotated databases of all publicly available Rosaceae ESTs, the genetically anchored peach physical map, Rosaceae genetic maps and comprehensively annotated markers and traits. The ESTs are assembled to produce unigene sets of each genus and the entire Rosaceae. Other annotations include putative function, microsatellites, open reading frames, single nucleotide polymorphisms, gene ontology terms and anchored map position where applicable. Most of the published Rosaceae genetic maps can be viewed and compared through CMap, the comparative map viewer. The peach physical map can be viewed using WebFPC/WebChrom, and also through our integrated GDR map viewer, which serves as a portal to the combined genetic, transcriptome and physical mapping information. ESTs, BACs, markers and traits can be queried by various categories and the search result sites are linked to the mapping visualization tools. GDR also provides online analysis tools such as a batch BLAST/FASTA server for the GDR datasets, a sequence assembly server and microsatellite and primer detection tools. GDR is available at http://www.rosaceae.org.

  15. NABIC marker database: A molecular markers information network of agricultural crops.

    Science.gov (United States)

    Kim, Chang-Kug; Seol, Young-Joo; Lee, Dong-Jun; Jeong, In-Seon; Yoon, Ung-Han; Lee, Gang-Seob; Hahn, Jang-Ho; Park, Dong-Suk

    2013-01-01

    In 2013, National Agricultural Biotechnology Information Center (NABIC) reconstructs a molecular marker database for useful genetic resources. The web-based marker database consists of three major functional categories: map viewer, RSN marker and gene annotation. It provides 7250 marker locations, 3301 RSN marker property, 3280 molecular marker annotation information in agricultural plants. The individual molecular marker provides information such as marker name, expressed sequence tag number, gene definition and general marker information. This updated marker-based database provides useful information through a user-friendly web interface that assisted in tracing any new structures of the chromosomes and gene positional functions using specific molecular markers. The database is available for free at http://nabic.rda.go.kr/gere/rice/molecularMarkers/

  16. Annotating functional RNAs in genomes using Infernal.

    Science.gov (United States)

    Nawrocki, Eric P

    2014-01-01

    Many different types of functional non-coding RNAs participate in a wide range of important cellular functions but the large majority of these RNAs are not routinely annotated in published genomes. Several programs have been developed for identifying RNAs, including specific tools tailored to a particular RNA family as well as more general ones designed to work for any family. Many of these tools utilize covariance models (CMs), statistical models of the conserved sequence, and structure of an RNA family. In this chapter, as an illustrative example, the Infernal software package and CMs from the Rfam database are used to identify RNAs in the genome of the archaeon Methanobrevibacter ruminantium, uncovering some additional RNAs not present in the genome's initial annotation. Analysis of the results and comparison with family-specific methods demonstrate some important strengths and weaknesses of this general approach.

  17. ArthropodaCyc: a CycADS powered collection of BioCyc databases to analyse and compare metabolism of arthropods.

    Science.gov (United States)

    Baa-Puyoulet, Patrice; Parisot, Nicolas; Febvay, Gérard; Huerta-Cepas, Jaime; Vellozo, Augusto F; Gabaldón, Toni; Calevro, Federica; Charles, Hubert; Colella, Stefano

    2016-01-01

    Arthropods interact with humans at different levels with highly beneficial roles (e.g. as pollinators), as well as with a negative impact for example as vectors of human or animal diseases, or as agricultural pests. Several arthropod genomes are available at present and many others will be sequenced in the near future in the context of the i5K initiative, offering opportunities for reconstructing, modelling and comparing their metabolic networks. In-depth analysis of these genomic data through metabolism reconstruction is expected to contribute to a better understanding of the biology of arthropods, thereby allowing the development of new strategies to control harmful species. In this context, we present here ArthropodaCyc, a dedicated BioCyc collection of databases using the Cyc annotation database system (CycADS), allowing researchers to perform reliable metabolism comparisons of fully sequenced arthropods genomes. Since the annotation quality is a key factor when performing such global genome comparisons, all proteins from the genomes included in the ArthropodaCyc database were re-annotated using several annotation tools and orthology information. All functional/domain annotation results and their sources were integrated in the databases for user access. Currently, ArthropodaCyc offers a centralized repository of metabolic pathways, protein sequence domains, Gene Ontology annotations as well as evolutionary information for 28 arthropod species. Such database collection allows metabolism analysis both with integrated tools and through extraction of data in formats suitable for systems biology studies.Database URL: http://arthropodacyc.cycadsys.org/. © The Author(s) 2016. Published by Oxford University Press.

  18. A high-performance spatial database based approach for pathology imaging algorithm evaluation.

    Science.gov (United States)

    Wang, Fusheng; Kong, Jun; Gao, Jingjing; Cooper, Lee A D; Kurc, Tahsin; Zhou, Zhengwen; Adler, David; Vergara-Niedermayr, Cristobal; Katigbak, Bryan; Brat, Daniel J; Saltz, Joel H

    2013-01-01

    Algorithm evaluation provides a means to characterize variability across image analysis algorithms, validate algorithms by comparison with human annotations, combine results from multiple algorithms for performance improvement, and facilitate algorithm sensitivity studies. The sizes of images and image analysis results in pathology image analysis pose significant challenges in algorithm evaluation. We present an efficient parallel spatial database approach to model, normalize, manage, and query large volumes of analytical image result data. This provides an efficient platform for algorithm evaluation. Our experiments with a set of brain tumor images demonstrate the application, scalability, and effectiveness of the platform. The paper describes an approach and platform for evaluation of pathology image analysis algorithms. The platform facilitates algorithm evaluation through a high-performance database built on the Pathology Analytic Imaging Standards (PAIS) data model. (1) Develop a framework to support algorithm evaluation by modeling and managing analytical results and human annotations from pathology images; (2) Create a robust data normalization tool for converting, validating, and fixing spatial data from algorithm or human annotations; (3) Develop a set of queries to support data sampling and result comparisons; (4) Achieve high performance computation capacity via a parallel data management infrastructure, parallel data loading and spatial indexing optimizations in this infrastructure. WE HAVE CONSIDERED TWO SCENARIOS FOR ALGORITHM EVALUATION: (1) algorithm comparison where multiple result sets from different methods are compared and consolidated; and (2) algorithm validation where algorithm results are compared with human annotations. We have developed a spatial normalization toolkit to validate and normalize spatial boundaries produced by image analysis algorithms or human annotations. The validated data were formatted based on the PAIS data model and

  19. Plann: A command-line application for annotating plastome sequences.

    Science.gov (United States)

    Huang, Daisie I; Cronk, Quentin C B

    2015-08-01

    Plann automates the process of annotating a plastome sequence in GenBank format for either downstream processing or for GenBank submission by annotating a new plastome based on a similar, well-annotated plastome. Plann is a Perl script to be executed on the command line. Plann compares a new plastome sequence to the features annotated in a reference plastome and then shifts the intervals of any matching features to the locations in the new plastome. Plann's output can be used in the National Center for Biotechnology Information's tbl2asn to create a Sequin file for GenBank submission. Unlike Web-based annotation packages, Plann is a locally executable script that will accurately annotate a plastome sequence to a locally specified reference plastome. Because it executes from the command line, it is ready to use in other software pipelines and can be easily rerun as a draft plastome is improved.

  20. The Drosophila melanogaster PeptideAtlas facilitates the use of peptide data for improved fly proteomics and genome annotation

    Directory of Open Access Journals (Sweden)

    King Nichole L

    2009-02-01

    Full Text Available Abstract Background Crucial foundations of any quantitative systems biology experiment are correct genome and proteome annotations. Protein databases compiled from high quality empirical protein identifications that are in turn based on correct gene models increase the correctness, sensitivity, and quantitative accuracy of systems biology genome-scale experiments. Results In this manuscript, we present the Drosophila melanogaster PeptideAtlas, a fly proteomics and genomics resource of unsurpassed depth. Based on peptide mass spectrometry data collected in our laboratory the portal http://www.drosophila-peptideatlas.org allows querying fly protein data observed with respect to gene model confirmation and splice site verification as well as for the identification of proteotypic peptides suited for targeted proteomics studies. Additionally, the database provides consensus mass spectra for observed peptides along with qualitative and quantitative information about the number of observations of a particular peptide and the sample(s in which it was observed. Conclusion PeptideAtlas is an open access database for the Drosophila community that has several features and applications that support (1 reduction of the complexity inherently associated with performing targeted proteomic studies, (2 designing and accelerating shotgun proteomics experiments, (3 confirming or questioning gene models, and (4 adjusting gene models such that they are in line with observed Drosophila peptides. While the database consists of proteomic data it is not required that the user is a proteomics expert.

  1. Ubiquitous Annotation Systems

    DEFF Research Database (Denmark)

    Hansen, Frank Allan

    2006-01-01

    Ubiquitous annotation systems allow users to annotate physical places, objects, and persons with digital information. Especially in the field of location based information systems much work has been done to implement adaptive and context-aware systems, but few efforts have focused on the general...... requirements for linking information to objects in both physical and digital space. This paper surveys annotation techniques from open hypermedia systems, Web based annotation systems, and mobile and augmented reality systems to illustrate different approaches to four central challenges ubiquitous annotation...... systems have to deal with: anchoring, structuring, presentation, and authoring. Through a number of examples each challenge is discussed and HyCon, a context-aware hypermedia framework developed at the University of Aarhus, Denmark, is used to illustrate an integrated approach to ubiquitous annotations...

  2. Database Constraints Applied to Metabolic Pathway Reconstruction Tools

    Directory of Open Access Journals (Sweden)

    Jordi Vilaplana

    2014-01-01

    Full Text Available Our group developed two biological applications, Biblio-MetReS and Homol-MetReS, accessing the same database of organisms with annotated genes. Biblio-MetReS is a data-mining application that facilitates the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (reannotation of proteomes, to properly identify both the individual proteins involved in the process(es of interest and their function. It also enables the sets of proteins involved in the process(es in different organisms to be compared directly. The efficiency of these biological applications is directly related to the design of the shared database. We classified and analyzed the different kinds of access to the database. Based on this study, we tried to adjust and tune the configurable parameters of the database server to reach the best performance of the communication data link to/from the database system. Different database technologies were analyzed. We started the study with a public relational SQL database, MySQL. Then, the same database was implemented by a MapReduce-based database named HBase. The results indicated that the standard configuration of MySQL gives an acceptable performance for low or medium size databases. Nevertheless, tuning database parameters can greatly improve the performance and lead to very competitive runtimes.

  3. Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics.

    Science.gov (United States)

    Chepelev, Leonid L; Riazanov, Alexandre; Kouznetsov, Alexandre; Low, Hong Sang; Dumontier, Michel; Baker, Christopher J O

    2011-07-26

    The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality. As part of an exploratory study, we have investigated the utility of semantic web technologies in automated chemical classification and annotation of lipids. Our prototype framework consists of two components: an ontology and a set of federated web services that operate upon it. The formal lipid ontology we use here extends a part of the LiPrO ontology and draws on the lipid hierarchy in the LIPID MAPS database, as well as literature-derived knowledge. The federated semantic web services that operate upon this ontology are deployed within the Semantic Annotation, Discovery, and Integration (SADI) framework. Structure-based lipid classification is enacted by two core services. Firstly, a structural annotation service detects and enumerates relevant functional groups for a specified chemical structure. A second service reasons over lipid ontology class descriptions using the attributes obtained from the annotation service and identifies the appropriate lipid classification. We extend the utility of these core services by combining them with additional SADI services that retrieve associations between lipids and proteins and identify publications related to specified lipid types. We analyze the performance of SADI-enabled eicosanoid classification relative to the LIPID MAPS classification and reflect on the contribution of our integrative methodology in the context of

  4. Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics

    Directory of Open Access Journals (Sweden)

    Dumontier Michel

    2011-07-01

    Full Text Available Abstract Background The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality. Results As part of an exploratory study, we have investigated the utility of semantic web technologies in automated chemical classification and annotation of lipids. Our prototype framework consists of two components: an ontology and a set of federated web services that operate upon it. The formal lipid ontology we use here extends a part of the LiPrO ontology and draws on the lipid hierarchy in the LIPID MAPS database, as well as literature-derived knowledge. The federated semantic web services that operate upon this ontology are deployed within the Semantic Annotation, Discovery, and Integration (SADI framework. Structure-based lipid classification is enacted by two core services. Firstly, a structural annotation service detects and enumerates relevant functional groups for a specified chemical structure. A second service reasons over lipid ontology class descriptions using the attributes obtained from the annotation service and identifies the appropriate lipid classification. We extend the utility of these core services by combining them with additional SADI services that retrieve associations between lipids and proteins and identify publications related to specified lipid types. We analyze the performance of SADI-enabled eicosanoid classification relative to the LIPID MAPS classification and reflect on the contribution of

  5. Improving integrative searching of systems chemical biology data using semantic annotation

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    Chen Bin

    2012-03-01

    Full Text Available Abstract Background Systems chemical biology and chemogenomics are considered critical, integrative disciplines in modern biomedical research, but require data mining of large, integrated, heterogeneous datasets from chemistry and biology. We previously developed an RDF-based resource called Chem2Bio2RDF that enabled querying of such data using the SPARQL query language. Whilst this work has proved useful in its own right as one of the first major resources in these disciplines, its utility could be greatly improved by the application of an ontology for annotation of the nodes and edges in the RDF graph, enabling a much richer range of semantic queries to be issued. Results We developed a generalized chemogenomics and systems chemical biology OWL ontology called Chem2Bio2OWL that describes the semantics of chemical compounds, drugs, protein targets, pathways, genes, diseases and side-effects, and the relationships between them. The ontology also includes data provenance. We used it to annotate our Chem2Bio2RDF dataset, making it a rich semantic resource. Through a series of scientific case studies we demonstrate how this (i simplifies the process of building SPARQL queries, (ii enables useful new kinds of queries on the data and (iii makes possible intelligent reasoning and semantic graph mining in chemogenomics and systems chemical biology. Availability Chem2Bio2OWL is available at http://chem2bio2rdf.org/owl. The document is available at http://chem2bio2owl.wikispaces.com.

  6. Data Cleaning and Semantic Improvement in Biological Databases

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    Apiletti Daniele

    2006-12-01

    Full Text Available Public genomic and proteomic databases can be affected by a variety of errors. These errors may involve either the description or the meaning of data (namely, syntactic or semantic errors. We focus our analysis on the detection of semantic errors, in order to verify the accuracy of the stored information. In particular, we address the issue of data constraints and functional dependencies among attributes in a given relational database. Constraints and dependencies show semantics among attributes in a database schema and their knowledge may be exploited to improve data quality and integration in database design, and to perform query optimization and dimensional reduction.

  7. MIPS: curated databases and comprehensive secondary data resources in 2010.

    Science.gov (United States)

    Mewes, H Werner; Ruepp, Andreas; Theis, Fabian; Rattei, Thomas; Walter, Mathias; Frishman, Dmitrij; Suhre, Karsten; Spannagl, Manuel; Mayer, Klaus F X; Stümpflen, Volker; Antonov, Alexey

    2011-01-01

    The Munich Information Center for Protein Sequences (MIPS at the Helmholtz Center for Environmental Health, Neuherberg, Germany) has many years of experience in providing annotated collections of biological data. Selected data sets of high relevance, such as model genomes, are subjected to careful manual curation, while the bulk of high-throughput data is annotated by automatic means. High-quality reference resources developed in the past and still actively maintained include Saccharomyces cerevisiae, Neurospora crassa and Arabidopsis thaliana genome databases as well as several protein interaction data sets (MPACT, MPPI and CORUM). More recent projects are PhenomiR, the database on microRNA-related phenotypes, and MIPS PlantsDB for integrative and comparative plant genome research. The interlinked resources SIMAP and PEDANT provide homology relationships as well as up-to-date and consistent annotation for 38,000,000 protein sequences. PPLIPS and CCancer are versatile tools for proteomics and functional genomics interfacing to a database of compilations from gene lists extracted from literature. A novel literature-mining tool, EXCERBT, gives access to structured information on classified relations between genes, proteins, phenotypes and diseases extracted from Medline abstracts by semantic analysis. All databases described here, as well as the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.helmholtz-muenchen.de).

  8. Experimental-confirmation and functional-annotation of predicted proteins in the chicken genome

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    McCarthy Fiona M

    2007-11-01

    Full Text Available Abstract Background The chicken genome was sequenced because of its phylogenetic position as a non-mammalian vertebrate, its use as a biomedical model especially to study embryology and development, its role as a source of human disease organisms and its importance as the major source of animal derived food protein. However, genomic sequence data is, in itself, of limited value; generally it is not equivalent to understanding biological function. The benefit of having a genome sequence is that it provides a basis for functional genomics. However, the sequence data currently available is poorly structurally and functionally annotated and many genes do not have standard nomenclature assigned. Results We analysed eight chicken tissues and improved the chicken genome structural annotation by providing experimental support for the in vivo expression of 7,809 computationally predicted proteins, including 30 chicken proteins that were only electronically predicted or hypothetical translations in human. To improve functional annotation (based on Gene Ontology, we mapped these identified proteins to their human and mouse orthologs and used this orthology to transfer Gene Ontology (GO functional annotations to the chicken proteins. The 8,213 orthology-based GO annotations that we produced represent an 8% increase in currently available chicken GO annotations. Orthologous chicken products were also assigned standardized nomenclature based on current chicken nomenclature guidelines. Conclusion We demonstrate the utility of high-throughput expression proteomics for rapid experimental structural annotation of a newly sequenced eukaryote genome. These experimentally-supported predicted proteins were further annotated by assigning the proteins with standardized nomenclature and functional annotation. This method is widely applicable to a diverse range of species. Moreover, information from one genome can be used to improve the annotation of other genomes and

  9. GenomeRNAi: a database for cell-based RNAi phenotypes.

    Science.gov (United States)

    Horn, Thomas; Arziman, Zeynep; Berger, Juerg; Boutros, Michael

    2007-01-01

    RNA interference (RNAi) has emerged as a powerful tool to generate loss-of-function phenotypes in a variety of organisms. Combined with the sequence information of almost completely annotated genomes, RNAi technologies have opened new avenues to conduct systematic genetic screens for every annotated gene in the genome. As increasing large datasets of RNAi-induced phenotypes become available, an important challenge remains the systematic integration and annotation of functional information. Genome-wide RNAi screens have been performed both in Caenorhabditis elegans and Drosophila for a variety of phenotypes and several RNAi libraries have become available to assess phenotypes for almost every gene in the genome. These screens were performed using different types of assays from visible phenotypes to focused transcriptional readouts and provide a rich data source for functional annotation across different species. The GenomeRNAi database provides access to published RNAi phenotypes obtained from cell-based screens and maps them to their genomic locus, including possible non-specific regions. The database also gives access to sequence information of RNAi probes used in various screens. It can be searched by phenotype, by gene, by RNAi probe or by sequence and is accessible at http://rnai.dkfz.de.

  10. Annotated text databases in the context of the Kaj Munk corpus

    DEFF Research Database (Denmark)

    Sandborg-Petersen, Ulrik

    procedure described in Part I can be brought to bear on the task of making Kaj Munk’s works available electronically to the general public. I do so by describing how I have implemented a “Munk Browser” desktop application. Chapter 13 discusses ways in which the EMdF model and the MQL query language can...... language can be extended to support the requirements of the problem of storing and retrieving annotated text even better. Finally, Chapter 15 concludes the dissertation. Appendix A gives the grammar for the subset of the MQL query language which closely resembles Doedens’s QL. Seven already-published...

  11. Searching the protein structure database for ligand-binding site similarities using CPASS v.2

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    Caprez Adam

    2011-01-01

    Full Text Available Abstract Background A recent analysis of protein sequences deposited in the NCBI RefSeq database indicates that ~8.5 million protein sequences are encoded in prokaryotic and eukaryotic genomes, where ~30% are explicitly annotated as "hypothetical" or "uncharacterized" protein. Our Comparison of Protein Active-Site Structures (CPASS v.2 database and software compares the sequence and structural characteristics of experimentally determined ligand binding sites to infer a functional relationship in the absence of global sequence or structure similarity. CPASS is an important component of our Functional Annotation Screening Technology by NMR (FAST-NMR protocol and has been successfully applied to aid the annotation of a number of proteins of unknown function. Findings We report a major upgrade to our CPASS software and database that significantly improves its broad utility. CPASS v.2 is designed with a layered architecture to increase flexibility and portability that also enables job distribution over the Open Science Grid (OSG to increase speed. Similarly, the CPASS interface was enhanced to provide more user flexibility in submitting a CPASS query. CPASS v.2 now allows for both automatic and manual definition of ligand-binding sites and permits pair-wise, one versus all, one versus list, or list versus list comparisons. Solvent accessible surface area, ligand root-mean square difference, and Cβ distances have been incorporated into the CPASS similarity function to improve the quality of the results. The CPASS database has also been updated. Conclusions CPASS v.2 is more than an order of magnitude faster than the original implementation, and allows for multiple simultaneous job submissions. Similarly, the CPASS database of ligand-defined binding sites has increased in size by ~ 38%, dramatically increasing the likelihood of a positive search result. The modification to the CPASS similarity function is effective in reducing CPASS similarity scores

  12. Identification and correction of abnormal, incomplete and mispredicted proteins in public databases

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    Bányai László

    2008-08-01

    Full Text Available Abstract Background Despite significant improvements in computational annotation of genomes, sequences of abnormal, incomplete or incorrectly predicted genes and proteins remain abundant in public databases. Since the majority of incomplete, abnormal or mispredicted entries are not annotated as such, these errors seriously affect the reliability of these databases. Here we describe the MisPred approach that may provide an efficient means for the quality control of databases. The current version of the MisPred approach uses five distinct routines for identifying abnormal, incomplete or mispredicted entries based on the principle that a sequence is likely to be incorrect if some of its features conflict with our current knowledge about protein-coding genes and proteins: (i conflict between the predicted subcellular localization of proteins and the absence of the corresponding sequence signals; (ii presence of extracellular and cytoplasmic domains and the absence of transmembrane segments; (iii co-occurrence of extracellular and nuclear domains; (iv violation of domain integrity; (v chimeras encoded by two or more genes located on different chromosomes. Results Analyses of predicted EnsEMBL protein sequences of nine deuterostome (Homo sapiens, Mus musculus, Rattus norvegicus, Monodelphis domestica, Gallus gallus, Xenopus tropicalis, Fugu rubripes, Danio rerio and Ciona intestinalis and two protostome species (Caenorhabditis elegans and Drosophila melanogaster have revealed that the absence of expected signal peptides and violation of domain integrity account for the majority of mispredictions. Analyses of sequences predicted by NCBI's GNOMON annotation pipeline show that the rates of mispredictions are comparable to those of EnsEMBL. Interestingly, even the manually curated UniProtKB/Swiss-Prot dataset is contaminated with mispredicted or abnormal proteins, although to a much lesser extent than UniProtKB/TrEMBL or the EnsEMBL or GNOMON

  13. From data repositories to submission portals: rethinking the role of domain-specific databases in CollecTF.

    Science.gov (United States)

    Kılıç, Sefa; Sagitova, Dinara M; Wolfish, Shoshannah; Bely, Benoit; Courtot, Mélanie; Ciufo, Stacy; Tatusova, Tatiana; O'Donovan, Claire; Chibucos, Marcus C; Martin, Maria J; Erill, Ivan

    2016-01-01

    Domain-specific databases are essential resources for the biomedical community, leveraging expert knowledge to curate published literature and provide access to referenced data and knowledge. The limited scope of these databases, however, poses important challenges on their infrastructure, visibility, funding and usefulness to the broader scientific community. CollecTF is a community-oriented database documenting experimentally validated transcription factor (TF)-binding sites in the Bacteria domain. In its quest to become a community resource for the annotation of transcriptional regulatory elements in bacterial genomes, CollecTF aims to move away from the conventional data-repository paradigm of domain-specific databases. Through the adoption of well-established ontologies, identifiers and collaborations, CollecTF has progressively become also a portal for the annotation and submission of information on transcriptional regulatory elements to major biological sequence resources (RefSeq, UniProtKB and the Gene Ontology Consortium). This fundamental change in database conception capitalizes on the domain-specific knowledge of contributing communities to provide high-quality annotations, while leveraging the availability of stable information hubs to promote long-term access and provide high-visibility to the data. As a submission portal, CollecTF generates TF-binding site information through direct annotation of RefSeq genome records, definition of TF-based regulatory networks in UniProtKB entries and submission of functional annotations to the Gene Ontology. As a database, CollecTF provides enhanced search and browsing, targeted data exports, binding motif analysis tools and integration with motif discovery and search platforms. This innovative approach will allow CollecTF to focus its limited resources on the generation of high-quality information and the provision of specialized access to the data.Database URL: http://www.collectf.org/. © The Author(s) 2016

  14. ChemProt: a disease chemical biology database

    DEFF Research Database (Denmark)

    Taboureau, Olivier; Nielsen, Sonny Kim; Audouze, Karine Marie Laure

    2011-01-01

    Systems pharmacology is an emergent area that studies drug action across multiple scales of complexity, from molecular and cellular to tissue and organism levels. There is a critical need to develop network-based approaches to integrate the growing body of chemical biology knowledge with network...... biology. Here, we report ChemProt, a disease chemical biology database, which is based on a compilation of multiple chemical-protein annotation resources, as well as disease-associated protein-protein interactions (PPIs). We assembled more than 700 000 unique chemicals with biological annotation for 30...... evaluation of environmental chemicals, natural products and approved drugs, as well as the selection of new compounds based on their activity profile against most known biological targets, including those related to adverse drug events. Results from the disease chemical biology database associate citalopram...

  15. A high-performance spatial database based approach for pathology imaging algorithm evaluation

    Directory of Open Access Journals (Sweden)

    Fusheng Wang

    2013-01-01

    Full Text Available Background: Algorithm evaluation provides a means to characterize variability across image analysis algorithms, validate algorithms by comparison with human annotations, combine results from multiple algorithms for performance improvement, and facilitate algorithm sensitivity studies. The sizes of images and image analysis results in pathology image analysis pose significant challenges in algorithm evaluation. We present an efficient parallel spatial database approach to model, normalize, manage, and query large volumes of analytical image result data. This provides an efficient platform for algorithm evaluation. Our experiments with a set of brain tumor images demonstrate the application, scalability, and effectiveness of the platform. Context: The paper describes an approach and platform for evaluation of pathology image analysis algorithms. The platform facilitates algorithm evaluation through a high-performance database built on the Pathology Analytic Imaging Standards (PAIS data model. Aims: (1 Develop a framework to support algorithm evaluation by modeling and managing analytical results and human annotations from pathology images; (2 Create a robust data normalization tool for converting, validating, and fixing spatial data from algorithm or human annotations; (3 Develop a set of queries to support data sampling and result comparisons; (4 Achieve high performance computation capacity via a parallel data management infrastructure, parallel data loading and spatial indexing optimizations in this infrastructure. Materials and Methods: We have considered two scenarios for algorithm evaluation: (1 algorithm comparison where multiple result sets from different methods are compared and consolidated; and (2 algorithm validation where algorithm results are compared with human annotations. We have developed a spatial normalization toolkit to validate and normalize spatial boundaries produced by image analysis algorithms or human annotations. The

  16. Annotation of nerve cord transcriptome in earthworm Eisenia fetida

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    Vasanthakumar Ponesakki

    2017-12-01

    Full Text Available In annelid worms, the nerve cord serves as a crucial organ to control the sensory and behavioral physiology. The inadequate genome resource of earthworms has prioritized the comprehensive analysis of their transcriptome dataset to monitor the genes express in the nerve cord and predict their role in the neurotransmission and sensory perception of the species. The present study focuses on identifying the potential transcripts and predicting their functional features by annotating the transcriptome dataset of nerve cord tissues prepared by Gong et al., 2010 from the earthworm Eisenia fetida. Totally 9762 transcripts were successfully annotated against the NCBI nr database using the BLASTX algorithm and among them 7680 transcripts were assigned to a total of 44,354 GO terms. The conserve domain analysis indicated the over representation of P-loop NTPase domain and calcium binding EF-hand domain. The COG functional annotation classified 5860 transcript sequences into 25 functional categories. Further, 4502 contig sequences were found to map with 124 KEGG pathways. The annotated contig dataset exhibited 22 crucial neuropeptides having considerable matches to the marine annelid Platynereis dumerilii, suggesting their possible role in neurotransmission and neuromodulation. In addition, 108 human stem cell marker homologs were identified including the crucial epigenetic regulators, transcriptional repressors and cell cycle regulators, which may contribute to the neuronal and segmental regeneration. The complete functional annotation of this nerve cord transcriptome can be further utilized to interpret genetic and molecular mechanisms associated with neuronal development, nervous system regeneration and nerve cord function.

  17. Use of Annotations for Component and Framework Interoperability

    Science.gov (United States)

    David, O.; Lloyd, W.; Carlson, J.; Leavesley, G. H.; Geter, F.

    2009-12-01

    The popular programming languages Java and C# provide annotations, a form of meta-data construct. Software frameworks for web integration, web services, database access, and unit testing now take advantage of annotations to reduce the complexity of APIs and the quantity of integration code between the application and framework infrastructure. Adopting annotation features in frameworks has been observed to lead to cleaner and leaner application code. The USDA Object Modeling System (OMS) version 3.0 fully embraces the annotation approach and additionally defines a meta-data standard for components and models. In version 3.0 framework/model integration previously accomplished using API calls is now achieved using descriptive annotations. This enables the framework to provide additional functionality non-invasively such as implicit multithreading, and auto-documenting capabilities while achieving a significant reduction in the size of the model source code. Using a non-invasive methodology leads to models and modeling components with only minimal dependencies on the modeling framework. Since models and modeling components are not directly bound to framework by the use of specific APIs and/or data types they can more easily be reused both within the framework as well as outside of it. To study the effectiveness of an annotation based framework approach with other modeling frameworks, a framework-invasiveness study was conducted to evaluate the effects of framework design on model code quality. A monthly water balance model was implemented across several modeling frameworks and several software metrics were collected. The metrics selected were measures of non-invasive design methods for modeling frameworks from a software engineering perspective. It appears that the use of annotations positively impacts several software quality measures. In a next step, the PRMS model was implemented in OMS 3.0 and is currently being implemented for water supply forecasting in the

  18. Internet Databases of the Properties, Enzymatic Reactions, and Metabolism of Small Molecules—Search Options and Applications in Food Science

    Directory of Open Access Journals (Sweden)

    Piotr Minkiewicz

    2016-12-01

    Full Text Available Internet databases of small molecules, their enzymatic reactions, and metabolism have emerged as useful tools in food science. Database searching is also introduced as part of chemistry or enzymology courses for food technology students. Such resources support the search for information about single compounds and facilitate the introduction of secondary analyses of large datasets. Information can be retrieved from databases by searching for the compound name or structure, annotating with the help of chemical codes or drawn using molecule editing software. Data mining options may be enhanced by navigating through a network of links and cross-links between databases. Exemplary databases reviewed in this article belong to two classes: tools concerning small molecules (including general and specialized databases annotating food components and tools annotating enzymes and metabolism. Some problems associated with database application are also discussed. Data summarized in computer databases may be used for calculation of daily intake of bioactive compounds, prediction of metabolism of food components, and their biological activity as well as for prediction of interactions between food component and drugs.

  19. MicrobesFlux: a web platform for drafting metabolic models from the KEGG database

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    Feng Xueyang

    2012-08-01

    Full Text Available Abstract Background Concurrent with the efforts currently underway in mapping microbial genomes using high-throughput sequencing methods, systems biologists are building metabolic models to characterize and predict cell metabolisms. One of the key steps in building a metabolic model is using multiple databases to collect and assemble essential information about genome-annotations and the architecture of the metabolic network for a specific organism. To speed up metabolic model development for a large number of microorganisms, we need a user-friendly platform to construct metabolic networks and to perform constraint-based flux balance analysis based on genome databases and experimental results. Results We have developed a semi-automatic, web-based platform (MicrobesFlux for generating and reconstructing metabolic models for annotated microorganisms. MicrobesFlux is able to automatically download the metabolic network (including enzymatic reactions and metabolites of ~1,200 species from the KEGG database (Kyoto Encyclopedia of Genes and Genomes and then convert it to a metabolic model draft. The platform also provides diverse customized tools, such as gene knockouts and the introduction of heterologous pathways, for users to reconstruct the model network. The reconstructed metabolic network can be formulated to a constraint-based flux model to predict and analyze the carbon fluxes in microbial metabolisms. The simulation results can be exported in the SBML format (The Systems Biology Markup Language. Furthermore, we also demonstrated the platform functionalities by developing an FBA model (including 229 reactions for a recent annotated bioethanol producer, Thermoanaerobacter sp. strain X514, to predict its biomass growth and ethanol production. Conclusion MicrobesFlux is an installation-free and open-source platform that enables biologists without prior programming knowledge to develop metabolic models for annotated microorganisms in the KEGG

  20. A data model and database for high-resolution pathology analytical image informatics.

    Science.gov (United States)

    Wang, Fusheng; Kong, Jun; Cooper, Lee; Pan, Tony; Kurc, Tahsin; Chen, Wenjin; Sharma, Ashish; Niedermayr, Cristobal; Oh, Tae W; Brat, Daniel; Farris, Alton B; Foran, David J; Saltz, Joel

    2011-01-01

    The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets. This paper presents a data model, which addresses these challenges, and demonstrates its implementation in a relational database system. This paper describes a data model, referred to as Pathology Analytic Imaging Standards (PAIS), and a database implementation, which are designed to support the data management and query requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines on whole-slide images and tissue microarrays (TMAs). (1) Development of a data model capable of efficiently representing and storing virtual slide related image, annotation, markup, and feature information. (2) Development of a database, based on the data model, capable of supporting queries for data retrieval based on analysis and image metadata, queries for comparison of results from different analyses, and spatial queries on segmented regions, features, and classified objects. The work described in this paper is motivated by the challenges associated with characterization of micro-scale features for comparative and correlative analyses involving whole-slides tissue images and TMAs. Technologies for digitizing tissues have advanced significantly in the past decade. Slide scanners are capable of producing high-magnification, high-resolution images from whole slides and TMAs within several minutes. Hence, it is becoming

  1. A data model and database for high-resolution pathology analytical image informatics

    Directory of Open Access Journals (Sweden)

    Fusheng Wang

    2011-01-01

    Full Text Available Background: The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets. This paper presents a data model, which addresses these challenges, and demonstrates its implementation in a relational database system. Context: This paper describes a data model, referred to as Pathology Analytic Imaging Standards (PAIS, and a database implementation, which are designed to support the data management and query requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines on whole-slide images and tissue microarrays (TMAs. Aims: (1 Development of a data model capable of efficiently representing and storing virtual slide related image, annotation, markup, and feature information. (2 Development of a database, based on the data model, capable of supporting queries for data retrieval based on analysis and image metadata, queries for comparison of results from different analyses, and spatial queries on segmented regions, features, and classified objects. Settings and Design: The work described in this paper is motivated by the challenges associated with characterization of micro-scale features for comparative and correlative analyses involving whole-slides tissue images and TMAs. Technologies for digitizing tissues have advanced significantly in the past decade. Slide scanners are capable of producing high-magnification, high-resolution images from whole

  2. Technostress: Surviving a Database Crash.

    Science.gov (United States)

    Dobb, Linda S.

    1990-01-01

    Discussion of technostress in libraries focuses on a database crash at California Polytechnic State University, San Luis Obispo. Steps taken to restore the data are explained, strategies for handling technological accidents are suggested, the impact on library staff is discussed, and a 10-item annotated bibliography on technostress is provided.…

  3. Plann: A command-line application for annotating plastome sequences1

    Science.gov (United States)

    Huang, Daisie I.; Cronk, Quentin C. B.

    2015-01-01

    Premise of the study: Plann automates the process of annotating a plastome sequence in GenBank format for either downstream processing or for GenBank submission by annotating a new plastome based on a similar, well-annotated plastome. Methods and Results: Plann is a Perl script to be executed on the command line. Plann compares a new plastome sequence to the features annotated in a reference plastome and then shifts the intervals of any matching features to the locations in the new plastome. Plann’s output can be used in the National Center for Biotechnology Information’s tbl2asn to create a Sequin file for GenBank submission. Conclusions: Unlike Web-based annotation packages, Plann is a locally executable script that will accurately annotate a plastome sequence to a locally specified reference plastome. Because it executes from the command line, it is ready to use in other software pipelines and can be easily rerun as a draft plastome is improved. PMID:26312193

  4. OAHG: an integrated resource for annotating human genes with multi-level ontologies.

    Science.gov (United States)

    Cheng, Liang; Sun, Jie; Xu, Wanying; Dong, Lixiang; Hu, Yang; Zhou, Meng

    2016-10-05

    OAHG, an integrated resource, aims to establish a comprehensive functional annotation resource for human protein-coding genes (PCGs), miRNAs, and lncRNAs by multi-level ontologies involving Gene Ontology (GO), Disease Ontology (DO), and Human Phenotype Ontology (HPO). Many previous studies have focused on inferring putative properties and biological functions of PCGs and non-coding RNA genes from different perspectives. During the past several decades, a few of databases have been designed to annotate the functions of PCGs, miRNAs, and lncRNAs, respectively. A part of functional descriptions in these databases were mapped to standardize terminologies, such as GO, which could be helpful to do further analysis. Despite these developments, there is no comprehensive resource recording the function of these three important types of genes. The current version of OAHG, release 1.0 (Jun 2016), integrates three ontologies involving GO, DO, and HPO, six gene functional databases and two interaction databases. Currently, OAHG contains 1,434,694 entries involving 16,929 PCGs, 637 miRNAs, 193 lncRNAs, and 24,894 terms of ontologies. During the performance evaluation, OAHG shows the consistencies with existing gene interactions and the structure of ontology. For example, terms with more similar structure could be associated with more associated genes (Pearson correlation γ 2  = 0.2428, p < 2.2e-16).

  5. Biases in the experimental annotations of protein function and their effect on our understanding of protein function space.

    Directory of Open Access Journals (Sweden)

    Alexandra M Schnoes

    Full Text Available The ongoing functional annotation of proteins relies upon the work of curators to capture experimental findings from scientific literature and apply them to protein sequence and structure data. However, with the increasing use of high-throughput experimental assays, a small number of experimental studies dominate the functional protein annotations collected in databases. Here, we investigate just how prevalent is the "few articles - many proteins" phenomenon. We examine the experimentally validated annotation of proteins provided by several groups in the GO Consortium, and show that the distribution of proteins per published study is exponential, with 0.14% of articles providing the source of annotations for 25% of the proteins in the UniProt-GOA compilation. Since each of the dominant articles describes the use of an assay that can find only one function or a small group of functions, this leads to substantial biases in what we know about the function of many proteins. Mass-spectrometry, microscopy and RNAi experiments dominate high throughput experiments. Consequently, the functional information derived from these experiments is mostly of the subcellular location of proteins, and of the participation of proteins in embryonic developmental pathways. For some organisms, the information provided by different studies overlap by a large amount. We also show that the information provided by high throughput experiments is less specific than those provided by low throughput experiments. Given the experimental techniques available, certain biases in protein function annotation due to high-throughput experiments are unavoidable. Knowing that these biases exist and understanding their characteristics and extent is important for database curators, developers of function annotation programs, and anyone who uses protein function annotation data to plan experiments.

  6. Biases in the Experimental Annotations of Protein Function and Their Effect on Our Understanding of Protein Function Space

    Science.gov (United States)

    Schnoes, Alexandra M.; Ream, David C.; Thorman, Alexander W.; Babbitt, Patricia C.; Friedberg, Iddo

    2013-01-01

    The ongoing functional annotation of proteins relies upon the work of curators to capture experimental findings from scientific literature and apply them to protein sequence and structure data. However, with the increasing use of high-throughput experimental assays, a small number of experimental studies dominate the functional protein annotations collected in databases. Here, we investigate just how prevalent is the “few articles - many proteins” phenomenon. We examine the experimentally validated annotation of proteins provided by several groups in the GO Consortium, and show that the distribution of proteins per published study is exponential, with 0.14% of articles providing the source of annotations for 25% of the proteins in the UniProt-GOA compilation. Since each of the dominant articles describes the use of an assay that can find only one function or a small group of functions, this leads to substantial biases in what we know about the function of many proteins. Mass-spectrometry, microscopy and RNAi experiments dominate high throughput experiments. Consequently, the functional information derived from these experiments is mostly of the subcellular location of proteins, and of the participation of proteins in embryonic developmental pathways. For some organisms, the information provided by different studies overlap by a large amount. We also show that the information provided by high throughput experiments is less specific than those provided by low throughput experiments. Given the experimental techniques available, certain biases in protein function annotation due to high-throughput experiments are unavoidable. Knowing that these biases exist and understanding their characteristics and extent is important for database curators, developers of function annotation programs, and anyone who uses protein function annotation data to plan experiments. PMID:23737737

  7. Analysis of disease-associated objects at the Rat Genome Database

    Science.gov (United States)

    Wang, Shur-Jen; Laulederkind, Stanley J. F.; Hayman, G. T.; Smith, Jennifer R.; Petri, Victoria; Lowry, Timothy F.; Nigam, Rajni; Dwinell, Melinda R.; Worthey, Elizabeth A.; Munzenmaier, Diane H.; Shimoyama, Mary; Jacob, Howard J.

    2013-01-01

    The Rat Genome Database (RGD) is the premier resource for genetic, genomic and phenotype data for the laboratory rat, Rattus norvegicus. In addition to organizing biological data from rats, the RGD team focuses on manual curation of gene–disease associations for rat, human and mouse. In this work, we have analyzed disease-associated strains, quantitative trait loci (QTL) and genes from rats. These disease objects form the basis for seven disease portals. Among disease portals, the cardiovascular disease and obesity/metabolic syndrome portals have the highest number of rat strains and QTL. These two portals share 398 rat QTL, and these shared QTL are highly concentrated on rat chromosomes 1 and 2. For disease-associated genes, we performed gene ontology (GO) enrichment analysis across portals using RatMine enrichment widgets. Fifteen GO terms, five from each GO aspect, were selected to profile enrichment patterns of each portal. Of the selected biological process (BP) terms, ‘regulation of programmed cell death’ was the top enriched term across all disease portals except in the obesity/metabolic syndrome portal where ‘lipid metabolic process’ was the most enriched term. ‘Cytosol’ and ‘nucleus’ were common cellular component (CC) annotations for disease genes, but only the cancer portal genes were highly enriched with ‘nucleus’ annotations. Similar enrichment patterns were observed in a parallel analysis using the DAVID functional annotation tool. The relationship between the preselected 15 GO terms and disease terms was examined reciprocally by retrieving rat genes annotated with these preselected terms. The individual GO term–annotated gene list showed enrichment in physiologically related diseases. For example, the ‘regulation of blood pressure’ genes were enriched with cardiovascular disease annotations, and the ‘lipid metabolic process’ genes with obesity annotations. Furthermore, we were able to enhance enrichment of neurological

  8. DBGC: A Database of Human Gastric Cancer

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    Wang, Chao; Zhang, Jun; Cai, Mingdeng; Zhu, Zhenggang; Gu, Wenjie; Yu, Yingyan; Zhang, Xiaoyan

    2015-01-01

    The Database of Human Gastric Cancer (DBGC) is a comprehensive database that integrates various human gastric cancer-related data resources. Human gastric cancer-related transcriptomics projects, proteomics projects, mutations, biomarkers and drug-sensitive genes from different sources were collected and unified in this database. Moreover, epidemiological statistics of gastric cancer patients in China and clinicopathological information annotated with gastric cancer cases were also integrated into the DBGC. We believe that this database will greatly facilitate research regarding human gastric cancer in many fields. DBGC is freely available at http://bminfor.tongji.edu.cn/dbgc/index.do PMID:26566288

  9. SoFIA: a data integration framework for annotating high-throughput datasets.

    Science.gov (United States)

    Childs, Liam Harold; Mamlouk, Soulafa; Brandt, Jörgen; Sers, Christine; Leser, Ulf

    2016-09-01

    Integrating heterogeneous datasets from several sources is a common bioinformatics task that often requires implementing a complex workflow intermixing database access, data filtering, format conversions, identifier mapping, among further diverse operations. Data integration is especially important when annotating next generation sequencing data, where a multitude of diverse tools and heterogeneous databases can be used to provide a large variety of annotation for genomic locations, such a single nucleotide variants or genes. Each tool and data source is potentially useful for a given project and often more than one are used in parallel for the same purpose. However, software that always produces all available data is difficult to maintain and quickly leads to an excess of data, creating an information overload rather than the desired goal-oriented and integrated result. We present SoFIA, a framework for workflow-driven data integration with a focus on genomic annotation. SoFIA conceptualizes workflow templates as comprehensive workflows that cover as many data integration operations as possible in a given domain. However, these templates are not intended to be executed as a whole; instead, when given an integration task consisting of a set of input data and a set of desired output data, SoFIA derives a minimal workflow that completes the task. These workflows are typically fast and create exactly the information a user wants without requiring them to do any implementation work. Using a comprehensive genome annotation template, we highlight the flexibility, extensibility and power of the framework using real-life case studies. https://github.com/childsish/sofia/releases/latest under the GNU General Public License liam.childs@hu-berlin.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  10. GDR (Genome Database for Rosaceae: integrated web resources for Rosaceae genomics and genetics research

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    Ficklin Stephen

    2004-09-01

    Full Text Available Abstract Background Peach is being developed as a model organism for Rosaceae, an economically important family that includes fruits and ornamental plants such as apple, pear, strawberry, cherry, almond and rose. The genomics and genetics data of peach can play a significant role in the gene discovery and the genetic understanding of related species. The effective utilization of these peach resources, however, requires the development of an integrated and centralized database with associated analysis tools. Description The Genome Database for Rosaceae (GDR is a curated and integrated web-based relational database. GDR contains comprehensive data of the genetically anchored peach physical map, an annotated peach EST database, Rosaceae maps and markers and all publicly available Rosaceae sequences. Annotations of ESTs include contig assembly, putative function, simple sequence repeats, and anchored position to the peach physical map where applicable. Our integrated map viewer provides graphical interface to the genetic, transcriptome and physical mapping information. ESTs, BACs and markers can be queried by various categories and the search result sites are linked to the integrated map viewer or to the WebFPC physical map sites. In addition to browsing and querying the database, users can compare their sequences with the annotated GDR sequences via a dedicated sequence similarity server running either the BLAST or FASTA algorithm. To demonstrate the utility of the integrated and fully annotated database and analysis tools, we describe a case study where we anchored Rosaceae sequences to the peach physical and genetic map by sequence similarity. Conclusions The GDR has been initiated to meet the major deficiency in Rosaceae genomics and genetics research, namely a centralized web database and bioinformatics tools for data storage, analysis and exchange. GDR can be accessed at http://www.genome.clemson.edu/gdr/.

  11. GDR (Genome Database for Rosaceae): integrated web resources for Rosaceae genomics and genetics research.

    Science.gov (United States)

    Jung, Sook; Jesudurai, Christopher; Staton, Margaret; Du, Zhidian; Ficklin, Stephen; Cho, Ilhyung; Abbott, Albert; Tomkins, Jeffrey; Main, Dorrie

    2004-09-09

    Peach is being developed as a model organism for Rosaceae, an economically important family that includes fruits and ornamental plants such as apple, pear, strawberry, cherry, almond and rose. The genomics and genetics data of peach can play a significant role in the gene discovery and the genetic understanding of related species. The effective utilization of these peach resources, however, requires the development of an integrated and centralized database with associated analysis tools. The Genome Database for Rosaceae (GDR) is a curated and integrated web-based relational database. GDR contains comprehensive data of the genetically anchored peach physical map, an annotated peach EST database, Rosaceae maps and markers and all publicly available Rosaceae sequences. Annotations of ESTs include contig assembly, putative function, simple sequence repeats, and anchored position to the peach physical map where applicable. Our integrated map viewer provides graphical interface to the genetic, transcriptome and physical mapping information. ESTs, BACs and markers can be queried by various categories and the search result sites are linked to the integrated map viewer or to the WebFPC physical map sites. In addition to browsing and querying the database, users can compare their sequences with the annotated GDR sequences via a dedicated sequence similarity server running either the BLAST or FASTA algorithm. To demonstrate the utility of the integrated and fully annotated database and analysis tools, we describe a case study where we anchored Rosaceae sequences to the peach physical and genetic map by sequence similarity. The GDR has been initiated to meet the major deficiency in Rosaceae genomics and genetics research, namely a centralized web database and bioinformatics tools for data storage, analysis and exchange. GDR can be accessed at http://www.genome.clemson.edu/gdr/.

  12. Annotating Diseases Using Human Phenotype Ontology Improves Prediction of Disease-Associated Long Non-coding RNAs.

    Science.gov (United States)

    Le, Duc-Hau; Dao, Lan T M

    2018-05-23

    Recently, many long non-coding RNAs (lncRNAs) have been identified and their biological function has been characterized; however, our understanding of their underlying molecular mechanisms related to disease is still limited. To overcome the limitation in experimentally identifying disease-lncRNA associations, computational methods have been proposed as a powerful tool to predict such associations. These methods are usually based on the similarities between diseases or lncRNAs since it was reported that similar diseases are associated with functionally similar lncRNAs. Therefore, prediction performance is highly dependent on how well the similarities can be captured. Previous studies have calculated the similarity between two diseases by mapping exactly each disease to a single Disease Ontology (DO) term, and then use a semantic similarity measure to calculate the similarity between them. However, the problem of this approach is that a disease can be described by more than one DO terms. Until now, there is no annotation database of DO terms for diseases except for genes. In contrast, Human Phenotype Ontology (HPO) is designed to fully annotate human disease phenotypes. Therefore, in this study, we constructed disease similarity networks/matrices using HPO instead of DO. Then, we used these networks/matrices as inputs of two representative machine learning-based and network-based ranking algorithms, that is, regularized least square and heterogeneous graph-based inference, respectively. The results showed that the prediction performance of the two algorithms on HPO-based is better than that on DO-based networks/matrices. In addition, our method can predict 11 novel cancer-associated lncRNAs, which are supported by literature evidence. Copyright © 2018 Elsevier Ltd. All rights reserved.

  13. Specialized microbial databases for inductive exploration of microbial genome sequences

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    Cabau Cédric

    2005-02-01

    Full Text Available Abstract Background The enormous amount of genome sequence data asks for user-oriented databases to manage sequences and annotations. Queries must include search tools permitting function identification through exploration of related objects. Methods The GenoList package for collecting and mining microbial genome databases has been rewritten using MySQL as the database management system. Functions that were not available in MySQL, such as nested subquery, have been implemented. Results Inductive reasoning in the study of genomes starts from "islands of knowledge", centered around genes with some known background. With this concept of "neighborhood" in mind, a modified version of the GenoList structure has been used for organizing sequence data from prokaryotic genomes of particular interest in China. GenoChore http://bioinfo.hku.hk/genochore.html, a set of 17 specialized end-user-oriented microbial databases (including one instance of Microsporidia, Encephalitozoon cuniculi, a member of Eukarya has been made publicly available. These databases allow the user to browse genome sequence and annotation data using standard queries. In addition they provide a weekly update of searches against the world-wide protein sequences data libraries, allowing one to monitor annotation updates on genes of interest. Finally, they allow users to search for patterns in DNA or protein sequences, taking into account a clustering of genes into formal operons, as well as providing extra facilities to query sequences using predefined sequence patterns. Conclusion This growing set of specialized microbial databases organize data created by the first Chinese bacterial genome programs (ThermaList, Thermoanaerobacter tencongensis, LeptoList, with two different genomes of Leptospira interrogans and SepiList, Staphylococcus epidermidis associated to related organisms for comparison.

  14. Multimedia database retrieval technology and applications

    CERN Document Server

    Muneesawang, Paisarn; Guan, Ling

    2014-01-01

    This book explores multimedia applications that emerged from computer vision and machine learning technologies. These state-of-the-art applications include MPEG-7, interactive multimedia retrieval, multimodal fusion, annotation, and database re-ranking. The application-oriented approach maximizes reader understanding of this complex field. Established researchers explain the latest developments in multimedia database technology and offer a glimpse of future technologies. The authors emphasize the crucial role of innovation, inspiring users to develop new applications in multimedia technologies

  15. Re-annotation of the genome sequence of Helicobacter pylori 26695

    Directory of Open Access Journals (Sweden)

    Resende Tiago

    2013-12-01

    Full Text Available Helicobacter pylori is a pathogenic bacterium that colonizes the human epithelia, causing duodenal and gastric ulcers, and gastric cancer. The genome of H. pylori 26695 has been previously sequenced and annotated. In addition, two genome-scale metabolic models have been developed. In order to maintain accurate and relevant information on coding sequences (CDS and to retrieve new information, the assignment of new functions to Helicobacter pylori 26695s genes was performed in this work. The use of software tools, on-line databases and an annotation pipeline for inspecting each gene allowed the attribution of validated EC numbers and TC numbers to metabolic genes encoding enzymes and transport proteins, respectively. 1212 genes encoding proteins were identified in this annotation, being 712 metabolic genes and 500 non-metabolic, while 191 new functions were assignment to the CDS of this bacterium. This information provides relevant biological information for the scientific community dealing with this organism and can be used as the basis for a new metabolic model reconstruction.

  16. Semi-Semantic Annotation: A guideline for the URDU.KON-TB treebank POS annotation

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    Qaiser ABBAS

    2016-12-01

    Full Text Available This work elaborates the semi-semantic part of speech annotation guidelines for the URDU.KON-TB treebank: an annotated corpus. A hierarchical annotation scheme was designed to label the part of speech and then applied on the corpus. This raw corpus was collected from the Urdu Wikipedia and the Jang newspaper and then annotated with the proposed semi-semantic part of speech labels. The corpus contains text of local & international news, social stories, sports, culture, finance, religion, traveling, etc. This exercise finally contributed a part of speech annotation to the URDU.KON-TB treebank. Twenty-two main part of speech categories are divided into subcategories, which conclude the morphological, and semantical information encoded in it. This article reports the annotation guidelines in major; however, it also briefs the development of the URDU.KON-TB treebank, which includes the raw corpus collection, designing & employment of annotation scheme and finally, its statistical evaluation and results. The guidelines presented as follows, will be useful for linguistic community to annotate the sentences not only for the national language Urdu but for the other indigenous languages like Punjab, Sindhi, Pashto, etc., as well.

  17. Deep Question Answering for protein annotation.

    Science.gov (United States)

    Gobeill, Julien; Gaudinat, Arnaud; Pasche, Emilie; Vishnyakova, Dina; Gaudet, Pascale; Bairoch, Amos; Ruch, Patrick

    2015-01-01

    Biomedical professionals have access to a huge amount of literature, but when they use a search engine, they often have to deal with too many documents to efficiently find the appropriate information in a reasonable time. In this perspective, question-answering (QA) engines are designed to display answers, which were automatically extracted from the retrieved documents. Standard QA engines in literature process a user question, then retrieve relevant documents and finally extract some possible answers out of these documents using various named-entity recognition processes. In our study, we try to answer complex genomics questions, which can be adequately answered only using Gene Ontology (GO) concepts. Such complex answers cannot be found using state-of-the-art dictionary- and redundancy-based QA engines. We compare the effectiveness of two dictionary-based classifiers for extracting correct GO answers from a large set of 100 retrieved abstracts per question. In the same way, we also investigate the power of GOCat, a GO supervised classifier. GOCat exploits the GOA database to propose GO concepts that were annotated by curators for similar abstracts. This approach is called deep QA, as it adds an original classification step, and exploits curated biological data to infer answers, which are not explicitly mentioned in the retrieved documents. We show that for complex answers such as protein functional descriptions, the redundancy phenomenon has a limited effect. Similarly usual dictionary-based approaches are relatively ineffective. In contrast, we demonstrate how existing curated data, beyond information extraction, can be exploited by a supervised classifier, such as GOCat, to massively improve both the quantity and the quality of the answers with a +100% improvement for both recall and precision. Database URL: http://eagl.unige.ch/DeepQA4PA/. © The Author(s) 2015. Published by Oxford University Press.

  18. BioAnnote: a software platform for annotating biomedical documents with application in medical learning environments.

    Science.gov (United States)

    López-Fernández, H; Reboiro-Jato, M; Glez-Peña, D; Aparicio, F; Gachet, D; Buenaga, M; Fdez-Riverola, F

    2013-07-01

    Automatic term annotation from biomedical documents and external information linking are becoming a necessary prerequisite in modern computer-aided medical learning systems. In this context, this paper presents BioAnnote, a flexible and extensible open-source platform for automatically annotating biomedical resources. Apart from other valuable features, the software platform includes (i) a rich client enabling users to annotate multiple documents in a user friendly environment, (ii) an extensible and embeddable annotation meta-server allowing for the annotation of documents with local or remote vocabularies and (iii) a simple client/server protocol which facilitates the use of our meta-server from any other third-party application. In addition, BioAnnote implements a powerful scripting engine able to perform advanced batch annotations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  19. Learning pathology using collaborative vs. individual annotation of whole slide images: a mixed methods trial.

    Science.gov (United States)

    Sahota, Michael; Leung, Betty; Dowdell, Stephanie; Velan, Gary M

    2016-12-12

    Students in biomedical disciplines require understanding of normal and abnormal microscopic appearances of human tissues (histology and histopathology). For this purpose, practical classes in these disciplines typically use virtual microscopy, viewing digitised whole slide images in web browsers. To enhance engagement, tools have been developed to enable individual or collaborative annotation of whole slide images within web browsers. To date, there have been no studies that have critically compared the impact on learning of individual and collaborative annotations on whole slide images. Junior and senior students engaged in Pathology practical classes within Medical Science and Medicine programs participated in cross-over trials of individual and collaborative annotation activities. Students' understanding of microscopic morphology was compared using timed online quizzes, while students' perceptions of learning were evaluated using an online questionnaire. For senior medical students, collaborative annotation of whole slide images was superior for understanding key microscopic features when compared to individual annotation; whilst being at least equivalent to individual annotation for junior medical science students. Across cohorts, students agreed that the annotation activities provided a user-friendly learning environment that met their flexible learning needs, improved efficiency, provided useful feedback, and helped them to set learning priorities. Importantly, these activities were also perceived to enhance motivation and improve understanding. Collaborative annotation improves understanding of microscopic morphology for students with sufficient background understanding of the discipline. These findings have implications for the deployment of annotation activities in biomedical curricula, and potentially for postgraduate training in Anatomical Pathology.

  20. SeqAnt: A web service to rapidly identify and annotate DNA sequence variations

    Directory of Open Access Journals (Sweden)

    Patel Viren

    2010-09-01

    Full Text Available Abstract Background The enormous throughput and low cost of second-generation sequencing platforms now allow research and clinical geneticists to routinely perform single experiments that identify tens of thousands to millions of variant sites. Existing methods to annotate variant sites using information from publicly available databases via web browsers are too slow to be useful for the large sequencing datasets being routinely generated by geneticists. Because sequence annotation of variant sites is required before functional characterization can proceed, the lack of a high-throughput pipeline to efficiently annotate variant sites can act as a significant bottleneck in genetics research. Results SeqAnt (Sequence Annotator is an open source web service and software package that rapidly annotates DNA sequence variants and identifies recessive or compound heterozygous loci in human, mouse, fly, and worm genome sequencing experiments. Variants are characterized with respect to their functional type, frequency, and evolutionary conservation. Annotated variants can be viewed on a web browser, downloaded in a tab-delimited text file, or directly uploaded in a BED format to the UCSC genome browser. To demonstrate the speed of SeqAnt, we annotated a series of publicly available datasets that ranged in size from 37 to 3,439,107 variant sites. The total time to completely annotate these data completely ranged from 0.17 seconds to 28 minutes 49.8 seconds. Conclusion SeqAnt is an open source web service and software package that overcomes a critical bottleneck facing research and clinical geneticists using second-generation sequencing platforms. SeqAnt will prove especially useful for those investigators who lack dedicated bioinformatics personnel or infrastructure in their laboratories.

  1. A multi-ontology approach to annotate scientific documents based on a modularization technique.

    Science.gov (United States)

    Gomes, Priscilla Corrêa E Castro; Moura, Ana Maria de Carvalho; Cavalcanti, Maria Cláudia

    2015-12-01

    Scientific text annotation has become an important task for biomedical scientists. Nowadays, there is an increasing need for the development of intelligent systems to support new scientific findings. Public databases available on the Web provide useful data, but much more useful information is only accessible in scientific texts. Text annotation may help as it relies on the use of ontologies to maintain annotations based on a uniform vocabulary. However, it is difficult to use an ontology, especially those that cover a large domain. In addition, since scientific texts explore multiple domains, which are covered by distinct ontologies, it becomes even more difficult to deal with such task. Moreover, there are dozens of ontologies in the biomedical area, and they are usually big in terms of the number of concepts. It is in this context that ontology modularization can be useful. This work presents an approach to annotate scientific documents using modules of different ontologies, which are built according to a module extraction technique. The main idea is to analyze a set of single-ontology annotations on a text to find out the user interests. Based on these annotations a set of modules are extracted from a set of distinct ontologies, and are made available for the user, for complementary annotation. The reduced size and focus of the extracted modules tend to facilitate the annotation task. An experiment was conducted to evaluate this approach, with the participation of a bioinformatician specialist of the Laboratory of Peptides and Proteins of the IOC/Fiocruz, who was interested in discovering new drug targets aiming at the combat of tropical diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. BDVC (Bimodal Database of Violent Content): A database of violent audio and video

    Science.gov (United States)

    Rivera Martínez, Jose Luis; Mijes Cruz, Mario Humberto; Rodríguez Vázqu, Manuel Antonio; Rodríguez Espejo, Luis; Montoya Obeso, Abraham; García Vázquez, Mireya Saraí; Ramírez Acosta, Alejandro Álvaro

    2017-09-01

    Nowadays there is a trend towards the use of unimodal databases for multimedia content description, organization and retrieval applications of a single type of content like text, voice and images, instead bimodal databases allow to associate semantically two different types of content like audio-video, image-text, among others. The generation of a bimodal database of audio-video implies the creation of a connection between the multimedia content through the semantic relation that associates the actions of both types of information. This paper describes in detail the used characteristics and methodology for the creation of the bimodal database of violent content; the semantic relationship is stablished by the proposed concepts that describe the audiovisual information. The use of bimodal databases in applications related to the audiovisual content processing allows an increase in the semantic performance only and only if these applications process both type of content. This bimodal database counts with 580 audiovisual annotated segments, with a duration of 28 minutes, divided in 41 classes. Bimodal databases are a tool in the generation of applications for the semantic web.

  3. Essential Annotation Schema for Ecology (EASE)-A framework supporting the efficient data annotation and faceted navigation in ecology.

    Science.gov (United States)

    Pfaff, Claas-Thido; Eichenberg, David; Liebergesell, Mario; König-Ries, Birgitta; Wirth, Christian

    2017-01-01

    Ecology has become a data intensive science over the last decades which often relies on the reuse of data in cross-experimental analyses. However, finding data which qualifies for the reuse in a specific context can be challenging. It requires good quality metadata and annotations as well as efficient search strategies. To date, full text search (often on the metadata only) is the most widely used search strategy although it is known to be inaccurate. Faceted navigation is providing a filter mechanism which is based on fine granular metadata, categorizing search objects along numeric and categorical parameters relevant for their discovery. Selecting from these parameters during a full text search creates a system of filters which allows to refine and improve the results towards more relevance. We developed a framework for the efficient annotation and faceted navigation in ecology. It consists of an XML schema for storing the annotation of search objects and is accompanied by a vocabulary focused on ecology to support the annotation process. The framework consolidates ideas which originate from widely accepted metadata standards, textbooks, scientific literature, and vocabularies as well as from expert knowledge contributed by researchers from ecology and adjacent disciplines.

  4. Essential Annotation Schema for Ecology (EASE-A framework supporting the efficient data annotation and faceted navigation in ecology.

    Directory of Open Access Journals (Sweden)

    Claas-Thido Pfaff

    Full Text Available Ecology has become a data intensive science over the last decades which often relies on the reuse of data in cross-experimental analyses. However, finding data which qualifies for the reuse in a specific context can be challenging. It requires good quality metadata and annotations as well as efficient search strategies. To date, full text search (often on the metadata only is the most widely used search strategy although it is known to be inaccurate. Faceted navigation is providing a filter mechanism which is based on fine granular metadata, categorizing search objects along numeric and categorical parameters relevant for their discovery. Selecting from these parameters during a full text search creates a system of filters which allows to refine and improve the results towards more relevance. We developed a framework for the efficient annotation and faceted navigation in ecology. It consists of an XML schema for storing the annotation of search objects and is accompanied by a vocabulary focused on ecology to support the annotation process. The framework consolidates ideas which originate from widely accepted metadata standards, textbooks, scientific literature, and vocabularies as well as from expert knowledge contributed by researchers from ecology and adjacent disciplines.

  5. Automatically annotating topics in transcripts of patient-provider interactions via machine learning.

    Science.gov (United States)

    Wallace, Byron C; Laws, M Barton; Small, Kevin; Wilson, Ira B; Trikalinos, Thomas A

    2014-05-01

    Annotated patient-provider encounters can provide important insights into clinical communication, ultimately suggesting how it might be improved to effect better health outcomes. But annotating outpatient transcripts with Roter or General Medical Interaction Analysis System (GMIAS) codes is expensive, limiting the scope of such analyses. We propose automatically annotating transcripts of patient-provider interactions with topic codes via machine learning. We use a conditional random field (CRF) to model utterance topic probabilities. The model accounts for the sequential structure of conversations and the words comprising utterances. We assess predictive performance via 10-fold cross-validation over GMIAS-annotated transcripts of 360 outpatient visits (>230,000 utterances). We then use automated in place of manual annotations to reproduce an analysis of 116 additional visits from a randomized trial that used GMIAS to assess the efficacy of an intervention aimed at improving communication around antiretroviral (ARV) adherence. With respect to 6 topic codes, the CRF achieved a mean pairwise kappa compared with human annotators of 0.49 (range: 0.47-0.53) and a mean overall accuracy of 0.64 (range: 0.62-0.66). With respect to the RCT reanalysis, results using automated annotations agreed with those obtained using manual ones. According to the manual annotations, the median number of ARV-related utterances without and with the intervention was 49.5 versus 76, respectively (paired sign test P = 0.07). When automated annotations were used, the respective numbers were 39 versus 55 (P = 0.04). While moderately accurate, the predicted annotations are far from perfect. Conversational topics are intermediate outcomes, and their utility is still being researched. This foray into automated topic inference suggests that machine learning methods can classify utterances comprising patient-provider interactions into clinically relevant topics with reasonable accuracy.

  6. NoGOA: predicting noisy GO annotations using evidences and sparse representation.

    Science.gov (United States)

    Yu, Guoxian; Lu, Chang; Wang, Jun

    2017-07-21

    Gene Ontology (GO) is a community effort to represent functional features of gene products. GO annotations (GOA) provide functional associations between GO terms and gene products. Due to resources limitation, only a small portion of annotations are manually checked by curators, and the others are electronically inferred. Although quality control techniques have been applied to ensure the quality of annotations, the community consistently report that there are still considerable noisy (or incorrect) annotations. Given the wide application of annotations, however, how to identify noisy annotations is an important but yet seldom studied open problem. We introduce a novel approach called NoGOA to predict noisy annotations. NoGOA applies sparse representation on the gene-term association matrix to reduce the impact of noisy annotations, and takes advantage of sparse representation coefficients to measure the semantic similarity between genes. Secondly, it preliminarily predicts noisy annotations of a gene based on aggregated votes from semantic neighborhood genes of that gene. Next, NoGOA estimates the ratio of noisy annotations for each evidence code based on direct annotations in GOA files archived on different periods, and then weights entries of the association matrix via estimated ratios and propagates weights to ancestors of direct annotations using GO hierarchy. Finally, it integrates evidence-weighted association matrix and aggregated votes to predict noisy annotations. Experiments on archived GOA files of six model species (H. sapiens, A. thaliana, S. cerevisiae, G. gallus, B. Taurus and M. musculus) demonstrate that NoGOA achieves significantly better results than other related methods and removing noisy annotations improves the performance of gene function prediction. The comparative study justifies the effectiveness of integrating evidence codes with sparse representation for predicting noisy GO annotations. Codes and datasets are available at http://mlda.swu.edu.cn/codes.php?name=NoGOA .

  7. The AnnoLite and AnnoLyze programs for comparative annotation of protein structures

    Directory of Open Access Journals (Sweden)

    Dopazo Joaquín

    2007-05-01

    Full Text Available Abstract Background Advances in structural biology, including structural genomics, have resulted in a rapid increase in the number of experimentally determined protein structures. However, about half of the structures deposited by the structural genomics consortia have little or no information about their biological function. Therefore, there is a need for tools for automatically and comprehensively annotating the function of protein structures. We aim to provide such tools by applying comparative protein structure annotation that relies on detectable relationships between protein structures to transfer functional annotations. Here we introduce two programs, AnnoLite and AnnoLyze, which use the structural alignments deposited in the DBAli database. Description AnnoLite predicts the SCOP, CATH, EC, InterPro, PfamA, and GO terms with an average sensitivity of ~90% and average precision of ~80%. AnnoLyze predicts ligand binding site and domain interaction patches with an average sensitivity of ~70% and average precision of ~30%, correctly localizing binding sites for small molecules in ~95% of its predictions. Conclusion The AnnoLite and AnnoLyze programs for comparative annotation of protein structures can reliably and automatically annotate new protein structures. The programs are fully accessible via the Internet as part of the DBAli suite of tools at http://salilab.org/DBAli/.

  8. Cloning, analysis and functional annotation of expressed sequence tags from the Earthworm Eisenia fetida

    Science.gov (United States)

    Pirooznia, Mehdi; Gong, Ping; Guan, Xin; Inouye, Laura S; Yang, Kuan; Perkins, Edward J; Deng, Youping

    2007-01-01

    Background Eisenia fetida, commonly known as red wiggler or compost worm, belongs to the Lumbricidae family of the Annelida phylum. Little is known about its genome sequence although it has been extensively used as a test organism in terrestrial ecotoxicology. In order to understand its gene expression response to environmental contaminants, we cloned 4032 cDNAs or expressed sequence tags (ESTs) from two E. fetida libraries enriched with genes responsive to ten ordnance related compounds using suppressive subtractive hybridization-PCR. Results A total of 3144 good quality ESTs (GenBank dbEST accession number EH669363–EH672369 and EL515444–EL515580) were obtained from the raw clone sequences after cleaning. Clustering analysis yielded 2231 unique sequences including 448 contigs (from 1361 ESTs) and 1783 singletons. Comparative genomic analysis showed that 743 or 33% of the unique sequences shared high similarity with existing genes in the GenBank nr database. Provisional function annotation assigned 830 Gene Ontology terms to 517 unique sequences based on their homology with the annotated genomes of four model organisms Drosophila melanogaster, Mus musculus, Saccharomyces cerevisiae, and Caenorhabditis elegans. Seven percent of the unique sequences were further mapped to 99 Kyoto Encyclopedia of Genes and Genomes pathways based on their matching Enzyme Commission numbers. All the information is stored and retrievable at a highly performed, web-based and user-friendly relational database called EST model database or ESTMD version 2. Conclusion The ESTMD containing the sequence and annotation information of 4032 E. fetida ESTs is publicly accessible at . PMID:18047730

  9. LIIS: A web-based system for culture collections and sample annotation

    Directory of Open Access Journals (Sweden)

    Matthew S Forster

    2014-04-01

    Full Text Available The Lab Information Indexing System (LIIS is a web-driven database application for laboratories looking to store their sample or culture metadata on a central server. The design was driven by a need to replace traditional paper storage with an easier to search format, and extend current spreadsheet storage methods. The system supports the import and export of CSV spreadsheets, and stores general metadata designed to complement the environmental packages provided by the Genomic Standards Consortium. The goals of the LIIS are to simplify the storage and archival processes and to provide an easy to access library of laboratory annotations. The program will find utility in microbial ecology laboratories or any lab that needs to annotate samples/cultures.

  10. The BioC-BioGRID corpus: full text articles annotated for curation of protein–protein and genetic interactions

    Science.gov (United States)

    Kim, Sun; Chatr-aryamontri, Andrew; Chang, Christie S.; Oughtred, Rose; Rust, Jennifer; Wilbur, W. John; Comeau, Donald C.; Dolinski, Kara; Tyers, Mike

    2017-01-01

    A great deal of information on the molecular genetics and biochemistry of model organisms has been reported in the scientific literature. However, this data is typically described in free text form and is not readily amenable to computational analyses. To this end, the BioGRID database systematically curates the biomedical literature for genetic and protein interaction data. This data is provided in a standardized computationally tractable format and includes structured annotation of experimental evidence. BioGRID curation necessarily involves substantial human effort by expert curators who must read each publication to extract the relevant information. Computational text-mining methods offer the potential to augment and accelerate manual curation. To facilitate the development of practical text-mining strategies, a new challenge was organized in BioCreative V for the BioC task, the collaborative Biocurator Assistant Task. This was a non-competitive, cooperative task in which the participants worked together to build BioC-compatible modules into an integrated pipeline to assist BioGRID curators. As an integral part of this task, a test collection of full text articles was developed that contained both biological entity annotations (gene/protein and organism/species) and molecular interaction annotations (protein–protein and genetic interactions (PPIs and GIs)). This collection, which we call the BioC-BioGRID corpus, was annotated by four BioGRID curators over three rounds of annotation and contains 120 full text articles curated in a dataset representing two major model organisms, namely budding yeast and human. The BioC-BioGRID corpus contains annotations for 6409 mentions of genes and their Entrez Gene IDs, 186 mentions of organism names and their NCBI Taxonomy IDs, 1867 mentions of PPIs and 701 annotations of PPI experimental evidence statements, 856 mentions of GIs and 399 annotations of GI evidence statements. The purpose, characteristics and possible future

  11. Annotating Mutational Effects on Proteins and Protein Interactions: Designing Novel and Revisiting Existing Protocols.

    Science.gov (United States)

    Li, Minghui; Goncearenco, Alexander; Panchenko, Anna R

    2017-01-01

    In this review we describe a protocol to annotate the effects of missense mutations on proteins, their functions, stability, and binding. For this purpose we present a collection of the most comprehensive databases which store different types of sequencing data on missense mutations, we discuss their relationships, possible intersections, and unique features. Next, we suggest an annotation workflow using the state-of-the art methods and highlight their usability, advantages, and limitations for different cases. Finally, we address a particularly difficult problem of deciphering the molecular mechanisms of mutations on proteins and protein complexes to understand the origins and mechanisms of diseases.

  12. Essential Annotation Schema for Ecology (EASE)—A framework supporting the efficient data annotation and faceted navigation in ecology

    Science.gov (United States)

    Eichenberg, David; Liebergesell, Mario; König-Ries, Birgitta; Wirth, Christian

    2017-01-01

    Ecology has become a data intensive science over the last decades which often relies on the reuse of data in cross-experimental analyses. However, finding data which qualifies for the reuse in a specific context can be challenging. It requires good quality metadata and annotations as well as efficient search strategies. To date, full text search (often on the metadata only) is the most widely used search strategy although it is known to be inaccurate. Faceted navigation is providing a filter mechanism which is based on fine granular metadata, categorizing search objects along numeric and categorical parameters relevant for their discovery. Selecting from these parameters during a full text search creates a system of filters which allows to refine and improve the results towards more relevance. We developed a framework for the efficient annotation and faceted navigation in ecology. It consists of an XML schema for storing the annotation of search objects and is accompanied by a vocabulary focused on ecology to support the annotation process. The framework consolidates ideas which originate from widely accepted metadata standards, textbooks, scientific literature, and vocabularies as well as from expert knowledge contributed by researchers from ecology and adjacent disciplines. PMID:29023519

  13. Protein Annotation from Protein Interaction Networks and Gene Ontology

    OpenAIRE

    Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

    2011-01-01

    We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

  14. FragKB: structural and literature annotation resource of conserved peptide fragments and residues.

    Directory of Open Access Journals (Sweden)

    Ashish V Tendulkar

    Full Text Available BACKGROUND: FragKB (Fragment Knowledgebase is a repository of clusters of structurally similar fragments from proteins. Fragments are annotated with information at the level of sequence, structure and function, integrating biological descriptions derived from multiple existing resources and text mining. METHODOLOGY: FragKB contains approximately 400,000 conserved fragments from 4,800 representative proteins from PDB. Literature annotations are extracted from more than 1,700 articles and are available for over 12,000 fragments. The underlying systematic annotation workflow of FragKB ensures efficient update and maintenance of this database. The information in FragKB can be accessed through a web interface that facilitates sequence and structural visualization of fragments together with known literature information on the consequences of specific residue mutations and functional annotations of proteins and fragment clusters. FragKB is accessible online at http://ubio.bioinfo.cnio.es/biotools/fragkb/. SIGNIFICANCE: The information presented in FragKB can be used for modeling protein structures, for designing novel proteins and for functional characterization of related fragments. The current release is focused on functional characterization of proteins through inspection of conservation of the fragments.

  15. A Flexible Object-of-Interest Annotation Framework for Online Video Portals

    Directory of Open Access Journals (Sweden)

    Robert Sorschag

    2012-02-01

    Full Text Available In this work, we address the use of object recognition techniques to annotate what is shown where in online video collections. These annotations are suitable to retrieve specific video scenes for object related text queries which is not possible with the manually generated metadata that is used by current portals. We are not the first to present object annotations that are generated with content-based analysis methods. However, the proposed framework possesses some outstanding features that offer good prospects for its application in real video portals. Firstly, it can be easily used as background module in any video environment. Secondly, it is not based on a fixed analysis chain but on an extensive recognition infrastructure that can be used with all kinds of visual features, matching and machine learning techniques. New recognition approaches can be integrated into this infrastructure with low development costs and a configuration of the used recognition approaches can be performed even on a running system. Thus, this framework might also benefit from future advances in computer vision. Thirdly, we present an automatic selection approach to support the use of different recognition strategies for different objects. Last but not least, visual analysis can be performed efficiently on distributed, multi-processor environments and a database schema is presented to store the resulting video annotations as well as the off-line generated low-level features in a compact form. We achieve promising results in an annotation case study and the instance search task of the TRECVID 2011 challenge.

  16. BLAST-based structural annotation of protein residues using Protein Data Bank.

    Science.gov (United States)

    Singh, Harinder; Raghava, Gajendra P S

    2016-01-25

    In the era of next-generation sequencing where thousands of genomes have been already sequenced; size of protein databases is growing with exponential rate. Structural annotation of these proteins is one of the biggest challenges for the computational biologist. Although, it is easy to perform BLAST search against Protein Data Bank (PDB) but it is difficult for a biologist to annotate protein residues from BLAST search. A web-server StarPDB has been developed for structural annotation of a protein based on its similarity with known protein structures. It uses standard BLAST software for performing similarity search of a query protein against protein structures in PDB. This server integrates wide range modules for assigning different types of annotation that includes, Secondary-structure, Accessible surface area, Tight-turns, DNA-RNA and Ligand modules. Secondary structure module allows users to predict regular secondary structure states to each residue in a protein. Accessible surface area predict the exposed or buried residues in a protein. Tight-turns module is designed to predict tight turns like beta-turns in a protein. DNA-RNA module developed for predicting DNA and RNA interacting residues in a protein. Similarly, Ligand module of server allows one to predicted ligands, metal and nucleotides ligand interacting residues in a protein. In summary, this manuscript presents a web server for comprehensive annotation of a protein based on similarity search. It integrates number of visualization tools that facilitate users to understand structure and function of protein residues. This web server is available freely for scientific community from URL http://crdd.osdd.net/raghava/starpdb .

  17. The Effects of Multimedia Annotations on Iranian EFL Learners’ L2 Vocabulary Learning

    Directory of Open Access Journals (Sweden)

    Saeideh Ahangari

    2010-05-01

    Full Text Available In our modern technological world, Computer-Assisted Language learning (CALL is a new realm towards learning a language in general, and learning L2 vocabulary in particular. It is assumed that the use of multimedia annotations promotes language learners’ vocabulary acquisition. Therefore, this study set out to investigate the effects of different multimedia annotations (still picture annotations, dynamic picture annotations, and written annotations on L2 vocabulary learning. To fulfill this objective, the researchers selected sixty four EFL learners as the participants of this study. The participants were randomly assigned to one of the four groups: a control group that received no annotations and three experimental groups that received:  still picture annotations, dynamic picture annotations, and written annotations. Each participant was required to take a pre-test. A vocabulary post- test was also designed and administered to the participants in order to assess the efficacy of each annotation. First for each group a paired t-test was conducted between their pre and post test scores in order to observe their improvement; then through an ANCOVA test the performance of four groups was compared. The results showed that using multimedia annotations resulted in a significant difference in the participants’ vocabulary learning. Based on the results of the present study, multimedia annotations are suggested as a vocabulary teaching strategy.

  18. Effects of Annotations and Homework on Learning Achievement: An Empirical Study of Scratch Programming Pedagogy

    Science.gov (United States)

    Su, Addison Y. S.; Huang, Chester S. J.; Yang, Stephen J. H.; Ding, T. J.; Hsieh, Y. Z.

    2015-01-01

    In Taiwan elementary schools, Scratch programming has been taught for more than four years. Previous studies have shown that personal annotations is a useful learning method that improve learning performance. An annotation-based Scratch programming (ASP) system provides for the creation, share, and review of annotations and homework solutions in…

  19. Automatic medical image annotation and keyword-based image retrieval using relevance feedback.

    Science.gov (United States)

    Ko, Byoung Chul; Lee, JiHyeon; Nam, Jae-Yeal

    2012-08-01

    This paper presents novel multiple keywords annotation for medical images, keyword-based medical image retrieval, and relevance feedback method for image retrieval for enhancing image retrieval performance. For semantic keyword annotation, this study proposes a novel medical image classification method combining local wavelet-based center symmetric-local binary patterns with random forests. For keyword-based image retrieval, our retrieval system use the confidence score that is assigned to each annotated keyword by combining probabilities of random forests with predefined body relation graph. To overcome the limitation of keyword-based image retrieval, we combine our image retrieval system with relevance feedback mechanism based on visual feature and pattern classifier. Compared with other annotation and relevance feedback algorithms, the proposed method shows both improved annotation performance and accurate retrieval results.

  20. TrSDB: a proteome database of transcription factors

    Science.gov (United States)

    Hermoso, Antoni; Aguilar, Daniel; Aviles, Francesc X.; Querol, Enrique

    2004-01-01

    TrSDB—TranScout Database—(http://ibb.uab.es/trsdb) is a proteome database of eukaryotic transcription factors based upon predicted motifs by TranScout and data sources such as InterPro and Gene Ontology Annotation. Nine eukaryotic proteomes are included in the current version. Extensive and diverse information for each database entry, different analyses considering TranScout classification and similarity relationships are offered for research on transcription factors or gene expression. PMID:14681387

  1. dictyBase 2015: Expanding data and annotations in a new software environment.

    Science.gov (United States)

    Basu, Siddhartha; Fey, Petra; Jimenez-Morales, David; Dodson, Robert J; Chisholm, Rex L

    2015-08-01

    dictyBase is the model organism database for the social amoeba Dictyostelium discoideum and related species. The primary mission of dictyBase is to provide the biomedical research community with well-integrated high quality data, and tools that enable original research. Data presented at dictyBase is obtained from sequencing centers, groups performing high throughput experiments such as large-scale mutagenesis studies, and RNAseq data, as well as a growing number of manually added functional gene annotations from the published literature, including Gene Ontology, strain, and phenotype annotations. Through the Dicty Stock Center we provide the community with an impressive amount of annotated strains and plasmids. Recently, dictyBase accomplished a major overhaul to adapt an outdated infrastructure to the current technological advances, thus facilitating the implementation of innovative tools and comparative genomics. It also provides new strategies for high quality annotations that enable bench researchers to benefit from the rapidly increasing volume of available data. dictyBase is highly responsive to its users needs, building a successful relationship that capitalizes on the vast efforts of the Dictyostelium research community. dictyBase has become the trusted data resource for Dictyostelium investigators, other investigators or organizations seeking information about Dictyostelium, as well as educators who use this model system. © 2015 Wiley Periodicals, Inc.

  2. MixtureTree annotator: a program for automatic colorization and visual annotation of MixtureTree.

    Directory of Open Access Journals (Sweden)

    Shu-Chuan Chen

    Full Text Available The MixtureTree Annotator, written in JAVA, allows the user to automatically color any phylogenetic tree in Newick format generated from any phylogeny reconstruction program and output the Nexus file. By providing the ability to automatically color the tree by sequence name, the MixtureTree Annotator provides a unique advantage over any other programs which perform a similar function. In addition, the MixtureTree Annotator is the only package that can efficiently annotate the output produced by MixtureTree with mutation information and coalescent time information. In order to visualize the resulting output file, a modified version of FigTree is used. Certain popular methods, which lack good built-in visualization tools, for example, MEGA, Mesquite, PHY-FI, TreeView, treeGraph and Geneious, may give results with human errors due to either manually adding colors to each node or with other limitations, for example only using color based on a number, such as branch length, or by taxonomy. In addition to allowing the user to automatically color any given Newick tree by sequence name, the MixtureTree Annotator is the only method that allows the user to automatically annotate the resulting tree created by the MixtureTree program. The MixtureTree Annotator is fast and easy-to-use, while still allowing the user full control over the coloring and annotating process.

  3. LCGbase: A Comprehensive Database for Lineage-Based Co-regulated Genes.

    Science.gov (United States)

    Wang, Dapeng; Zhang, Yubin; Fan, Zhonghua; Liu, Guiming; Yu, Jun

    2012-01-01

    Animal genes of different lineages, such as vertebrates and arthropods, are well-organized and blended into dynamic chromosomal structures that represent a primary regulatory mechanism for body development and cellular differentiation. The majority of genes in a genome are actually clustered, which are evolutionarily stable to different extents and biologically meaningful when evaluated among genomes within and across lineages. Until now, many questions concerning gene organization, such as what is the minimal number of genes in a cluster and what is the driving force leading to gene co-regulation, remain to be addressed. Here, we provide a user-friendly database-LCGbase (a comprehensive database for lineage-based co-regulated genes)-hosting information on evolutionary dynamics of gene clustering and ordering within animal kingdoms in two different lineages: vertebrates and arthropods. The database is constructed on a web-based Linux-Apache-MySQL-PHP framework and effective interactive user-inquiry service. Compared to other gene annotation databases with similar purposes, our database has three comprehensible advantages. First, our database is inclusive, including all high-quality genome assemblies of vertebrates and representative arthropod species. Second, it is human-centric since we map all gene clusters from other genomes in an order of lineage-ranks (such as primates, mammals, warm-blooded, and reptiles) onto human genome and start the database from well-defined gene pairs (a minimal cluster where the two adjacent genes are oriented as co-directional, convergent, and divergent pairs) to large gene clusters. Furthermore, users can search for any adjacent genes and their detailed annotations. Third, the database provides flexible parameter definitions, such as the distance of transcription start sites between two adjacent genes, which is extendable to genes that flanking the cluster across species. We also provide useful tools for sequence alignment, gene

  4. UniProtKB/Swiss-Prot, the Manually Annotated Section of the UniProt KnowledgeBase: How to Use the Entry View.

    Science.gov (United States)

    Boutet, Emmanuel; Lieberherr, Damien; Tognolli, Michael; Schneider, Michel; Bansal, Parit; Bridge, Alan J; Poux, Sylvain; Bougueleret, Lydie; Xenarios, Ioannis

    2016-01-01

    The Universal Protein Resource (UniProt, http://www.uniprot.org ) consortium is an initiative of the SIB Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI) and the Protein Information Resource (PIR) to provide the scientific community with a central resource for protein sequences and functional information. The UniProt consortium maintains the UniProt KnowledgeBase (UniProtKB), updated every 4 weeks, and several supplementary databases including the UniProt Reference Clusters (UniRef) and the UniProt Archive (UniParc).The Swiss-Prot section of the UniProt KnowledgeBase (UniProtKB/Swiss-Prot) contains publicly available expertly manually annotated protein sequences obtained from a broad spectrum of organisms. Plant protein entries are produced in the frame of the Plant Proteome Annotation Program (PPAP), with an emphasis on characterized proteins of Arabidopsis thaliana and Oryza sativa. High level annotations provided by UniProtKB/Swiss-Prot are widely used to predict annotation of newly available proteins through automatic pipelines.The purpose of this chapter is to present a guided tour of a UniProtKB/Swiss-Prot entry. We will also present some of the tools and databases that are linked to each entry.

  5. Development of a personalized training system using the Lung Image Database Consortium and Image Database resource Initiative Database.

    Science.gov (United States)

    Lin, Hongli; Wang, Weisheng; Luo, Jiawei; Yang, Xuedong

    2014-12-01

    The aim of this study was to develop a personalized training system using the Lung Image Database Consortium (LIDC) and Image Database resource Initiative (IDRI) Database, because collecting, annotating, and marking a large number of appropriate computed tomography (CT) scans, and providing the capability of dynamically selecting suitable training cases based on the performance levels of trainees and the characteristics of cases are critical for developing a efficient training system. A novel approach is proposed to develop a personalized radiology training system for the interpretation of lung nodules in CT scans using the Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) database, which provides a Content-Boosted Collaborative Filtering (CBCF) algorithm for predicting the difficulty level of each case of each trainee when selecting suitable cases to meet individual needs, and a diagnostic simulation tool to enable trainees to analyze and diagnose lung nodules with the help of an image processing tool and a nodule retrieval tool. Preliminary evaluation of the system shows that developing a personalized training system for interpretation of lung nodules is needed and useful to enhance the professional skills of trainees. The approach of developing personalized training systems using the LIDC/IDRL database is a feasible solution to the challenges of constructing specific training program in terms of cost and training efficiency. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

  6. Annotating images by mining image search results.

    Science.gov (United States)

    Wang, Xin-Jing; Zhang, Lei; Li, Xirong; Ma, Wei-Ying

    2008-11-01

    Although it has been studied for years by the computer vision and machine learning communities, image annotation is still far from practical. In this paper, we propose a novel attempt at model-free image annotation, which is a data-driven approach that annotates images by mining their search results. Some 2.4 million images with their surrounding text are collected from a few photo forums to support this approach. The entire process is formulated in a divide-and-conquer framework where a query keyword is provided along with the uncaptioned image to improve both the effectiveness and efficiency. This is helpful when the collected data set is not dense everywhere. In this sense, our approach contains three steps: 1) the search process to discover visually and semantically similar search results, 2) the mining process to identify salient terms from textual descriptions of the search results, and 3) the annotation rejection process to filter out noisy terms yielded by Step 2. To ensure real-time annotation, two key techniques are leveraged-one is to map the high-dimensional image visual features into hash codes, the other is to implement it as a distributed system, of which the search and mining processes are provided as Web services. As a typical result, the entire process finishes in less than 1 second. Since no training data set is required, our approach enables annotating with unlimited vocabulary and is highly scalable and robust to outliers. Experimental results on both real Web images and a benchmark image data set show the effectiveness and efficiency of the proposed algorithm. It is also worth noting that, although the entire approach is illustrated within the divide-and conquer framework, a query keyword is not crucial to our current implementation. We provide experimental results to prove this.

  7. Improvement of the European thermodynamic database NUCLEA

    Energy Technology Data Exchange (ETDEWEB)

    Brissoneau, L.; Journeau, C.; Piluso, P. [CEA Cadarache, DEN, F-13108 St Paul Les Durance (France); Bakardjieva, S. [Acad Sci Czech Republic, Inst Inorgan Chem, CZ-25068 Rez (Czech Republic); Barrachin, M. [Inst Radioprotect and Surete Nucl, St Paul Les Durance (France); Bechta, S. [NITI, Aleksandrov Res Inst Technol, Sosnovyi Bor (Russian Federation); Bottomley, D. [Commiss European Communities, Joint Res Ctr, Inst Transuranium Elements, D-76125 Karlsruhe (Germany); Cheynet, B.; Fischer, E. [Thermodata, F-38400 St Martin Dheres (France); Kiselova, M. [Nucl Res Inst UJV, Rez 25068 (Czech Republic); Mezentseva, L. [Russian Acad Sci, Inst Silicate Chem, St Petersburg (Russian Federation)

    2010-07-01

    Modelling of corium behaviour during a severe accident requires knowledge of the phases present at equilibrium for a given corium composition, temperature and pressure. The thermodynamic database NUCLEA in combination with a Gibbs Energy minimizer is the European reference tool to achieve this goal. This database has been improved thanks to the analysis of bibliographical data and to EU-funded experiments performed within the SARNET network, PLINIUS as well as the ISTC CORPHAD and EVAN projects. To assess the uncertainty range associated with Energy Dispersive X-ray analyses, a round-robin exercise has been launched in which a UO{sub 2}-containing corium-concrete interaction sample from VULCANO has been analyzed by three European laboratories with satisfactorily small differences. (authors)

  8. Evaluating Hierarchical Structure in Music Annotations.

    Science.gov (United States)

    McFee, Brian; Nieto, Oriol; Farbood, Morwaread M; Bello, Juan Pablo

    2017-01-01

    Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for "flat" descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  9. Evaluating Hierarchical Structure in Music Annotations

    Directory of Open Access Journals (Sweden)

    Brian McFee

    2017-08-01

    Full Text Available Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR, it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  10. Towards understanding the first genome sequence of a crenarchaeon by genome annotation using clusters of orthologous groups of proteins (COGs).

    Science.gov (United States)

    Natale, D A; Shankavaram, U T; Galperin, M Y; Wolf, Y I; Aravind, L; Koonin, E V

    2000-01-01

    Standard archival sequence databases have not been designed as tools for genome annotation and are far from being optimal for this purpose. We used the database of Clusters of Orthologous Groups of proteins (COGs) to reannotate the genomes of two archaea, Aeropyrum pernix, the first member of the Crenarchaea to be sequenced, and Pyrococcus abyssi. A. pernix and P. abyssi proteins were assigned to COGs using the COGNITOR program; the results were verified on a case-by-case basis and augmented by additional database searches using the PSI-BLAST and TBLASTN programs. Functions were predicted for over 300 proteins from A. pernix, which could not be assigned a function using conventional methods with a conservative sequence similarity threshold, an approximately 50% increase compared to the original annotation. A. pernix shares most of the conserved core of proteins that were previously identified in the Euryarchaeota. Cluster analysis or distance matrix tree construction based on the co-occurrence of genomes in COGs showed that A. pernix forms a distinct group within the archaea, although grouping with the two species of Pyrococci, indicative of similar repertoires of conserved genes, was observed. No indication of a specific relationship between Crenarchaeota and eukaryotes was obtained in these analyses. Several proteins that are conserved in Euryarchaeota and most bacteria are unexpectedly missing in A. pernix, including the entire set of de novo purine biosynthesis enzymes, the GTPase FtsZ (a key component of the bacterial and euryarchaeal cell-division machinery), and the tRNA-specific pseudouridine synthase, previously considered universal. A. pernix is represented in 48 COGs that do not contain any euryarchaeal members. Many of these proteins are TCA cycle and electron transport chain enzymes, reflecting the aerobic lifestyle of A. pernix. Special-purpose databases organized on the basis of phylogenetic analysis and carefully curated with respect to known and

  11. EXFOR: Improving the quality of international databases

    International Nuclear Information System (INIS)

    Dupont, Emmeric

    2014-01-01

    The NEA Data Bank is an international centre of reference for basic nuclear tools used for the analysis and prediction of phenomena in nuclear energy applications. The Data Bank collects, compiles, disseminates and contributes to improving computer codes and associated data. In the area of nuclear data, the Data Bank works in close co-operation with other data centres that contribute to the worldwide compilation of experimental nuclear reaction data in the EXFOR database. EXFOR contains basic nuclear data on low- to medium-energy experiments for incident neutron, photon and various charged particle induced reactions on a wide range of nuclei and compounds. Today, with more than 150 000 data sets from more than 20 000 experiments performed since 1935, EXFOR is by far the most important and complete experimental nuclear reaction database. It is widely used to further improve nuclear reaction models and evaluated nuclear data libraries. The Data Bank supervises the development of the Joint Evaluated Fission and Fusion (JEFF) file, which is one of the major evaluated nuclear data libraries used in the field of nuclear science and technology. As part of its mission, the Data Bank works to maintain the highest level of quality in its databases. One method that was proposed to check the mutual consistency of experimental data in EXFOR is to test for outlier measurements more than a few standard deviations from the mean value as, in principle, several measurements of the same reaction quantity should form a continuous distribution. More recently, another method was developed to cross-check evaluated and experimental data in databases in order to detect aberrant values. It was noted that there is no evidence, on the basis of numerical comparisons only, that outliers represent 'bad' data. The fact that such data deviate significantly from other data of the same reaction may, however, be helpful to nuclear data evaluators who focus on one or a few isotopes and may wish to

  12. Brassica database (BRAD) version 2.0: integrating and mining Brassicaceae species genomic resources.

    Science.gov (United States)

    Wang, Xiaobo; Wu, Jian; Liang, Jianli; Cheng, Feng; Wang, Xiaowu

    2015-01-01

    The Brassica database (BRAD) was built initially to assist users apply Brassica rapa and Arabidopsis thaliana genomic data efficiently to their research. However, many Brassicaceae genomes have been sequenced and released after its construction. These genomes are rich resources for comparative genomics, gene annotation and functional evolutionary studies of Brassica crops. Therefore, we have updated BRAD to version 2.0 (V2.0). In BRAD V2.0, 11 more Brassicaceae genomes have been integrated into the database, namely those of Arabidopsis lyrata, Aethionema arabicum, Brassica oleracea, Brassica napus, Camelina sativa, Capsella rubella, Leavenworthia alabamica, Sisymbrium irio and three extremophiles Schrenkiella parvula, Thellungiella halophila and Thellungiella salsuginea. BRAD V2.0 provides plots of syntenic genomic fragments between pairs of Brassicaceae species, from the level of chromosomes to genomic blocks. The Generic Synteny Browser (GBrowse_syn), a module of the Genome Browser (GBrowse), is used to show syntenic relationships between multiple genomes. Search functions for retrieving syntenic and non-syntenic orthologs, as well as their annotation and sequences are also provided. Furthermore, genome and annotation information have been imported into GBrowse so that all functional elements can be visualized in one frame. We plan to continually update BRAD by integrating more Brassicaceae genomes into the database. Database URL: http://brassicadb.org/brad/. © The Author(s) 2015. Published by Oxford University Press.

  13. Community annotation and bioinformatics workforce development in concert--Little Skate Genome Annotation Workshops and Jamborees.

    Science.gov (United States)

    Wang, Qinghua; Arighi, Cecilia N; King, Benjamin L; Polson, Shawn W; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F; Page, Shallee T; Rendino, Marc Farnum; Thomas, William Kelley; Udwary, Daniel W; Wu, Cathy H

    2012-01-01

    Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome.

  14. Community annotation and bioinformatics workforce development in concert—Little Skate Genome Annotation Workshops and Jamborees

    Science.gov (United States)

    Wang, Qinghua; Arighi, Cecilia N.; King, Benjamin L.; Polson, Shawn W.; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F.; Page, Shallee T.; Farnum Rendino, Marc; Thomas, William Kelley; Udwary, Daniel W.; Wu, Cathy H.

    2012-01-01

    Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome. PMID:22434832

  15. Genome Wide Re-Annotation of Caldicellulosiruptor saccharolyticus with New Insights into Genes Involved in Biomass Degradation and Hydrogen Production.

    Science.gov (United States)

    Chowdhary, Nupoor; Selvaraj, Ashok; KrishnaKumaar, Lakshmi; Kumar, Gopal Ramesh

    2015-01-01

    Caldicellulosiruptor saccharolyticus has proven itself to be an excellent candidate for biological hydrogen (H2) production, but still it has major drawbacks like sensitivity to high osmotic pressure and low volumetric H2 productivity, which should be considered before it can be used industrially. A whole genome re-annotation work has been carried out as an attempt to update the incomplete genome information that causes gap in the knowledge especially in the area of metabolic engineering, to improve the H2 producing capabilities of C. saccharolyticus. Whole genome re-annotation was performed through manual means for 2,682 Coding Sequences (CDSs). Bioinformatics tools based on sequence similarity, motif search, phylogenetic analysis and fold recognition were employed for re-annotation. Our methodology could successfully add functions for 409 hypothetical proteins (HPs), 46 proteins previously annotated as putative and assigned more accurate functions for the known protein sequences. Homology based gene annotation has been used as a standard method for assigning function to novel proteins, but over the past few years many non-homology based methods such as genomic context approaches for protein function prediction have been developed. Using non-homology based functional prediction methods, we were able to assign cellular processes or physical complexes for 249 hypothetical sequences. Our re-annotation pipeline highlights the addition of 231 new CDSs generated from MicroScope Platform, to the original genome with functional prediction for 49 of them. The re-annotation of HPs and new CDSs is stored in the relational database that is available on the MicroScope web-based platform. In parallel, a comparative genome analyses were performed among the members of genus Caldicellulosiruptor to understand the function and evolutionary processes. Further, with results from integrated re-annotation studies (homology and genomic context approach), we strongly suggest that Csac

  16. Genome Wide Re-Annotation of Caldicellulosiruptor saccharolyticus with New Insights into Genes Involved in Biomass Degradation and Hydrogen Production.

    Directory of Open Access Journals (Sweden)

    Nupoor Chowdhary

    Full Text Available Caldicellulosiruptor saccharolyticus has proven itself to be an excellent candidate for biological hydrogen (H2 production, but still it has major drawbacks like sensitivity to high osmotic pressure and low volumetric H2 productivity, which should be considered before it can be used industrially. A whole genome re-annotation work has been carried out as an attempt to update the incomplete genome information that causes gap in the knowledge especially in the area of metabolic engineering, to improve the H2 producing capabilities of C. saccharolyticus. Whole genome re-annotation was performed through manual means for 2,682 Coding Sequences (CDSs. Bioinformatics tools based on sequence similarity, motif search, phylogenetic analysis and fold recognition were employed for re-annotation. Our methodology could successfully add functions for 409 hypothetical proteins (HPs, 46 proteins previously annotated as putative and assigned more accurate functions for the known protein sequences. Homology based gene annotation has been used as a standard method for assigning function to novel proteins, but over the past few years many non-homology based methods such as genomic context approaches for protein function prediction have been developed. Using non-homology based functional prediction methods, we were able to assign cellular processes or physical complexes for 249 hypothetical sequences. Our re-annotation pipeline highlights the addition of 231 new CDSs generated from MicroScope Platform, to the original genome with functional prediction for 49 of them. The re-annotation of HPs and new CDSs is stored in the relational database that is available on the MicroScope web-based platform. In parallel, a comparative genome analyses were performed among the members of genus Caldicellulosiruptor to understand the function and evolutionary processes. Further, with results from integrated re-annotation studies (homology and genomic context approach, we strongly

  17. Improving Indicators in a Brazilian Hospital Through Quality-Improvement Programs Based on STS Database Reports

    Directory of Open Access Journals (Sweden)

    Pedro Gabriel Melo de Barros e Silva

    2015-12-01

    Full Text Available ABSTRACT OBJECTIVE: To report the initial changes after quality-improvement programs based on STS-database in a Brazilian hospital. METHODS: Since 2011 a Brazilian hospital has joined STS-Database and in 2012 multifaceted actions based on STS reports were implemented aiming reductions in the time of mechanical ventilation and in the intensive care stay and also improvements in evidence-based perioperative therapies among patients who underwent coronary artery bypass graft surgeries. RESULTS: All the 947 patients submitted to coronary artery bypass graft surgeries from July 2011 to June 2014 were analyzed and there was an improvement in all the three target endpoints after the implementation of the quality-improvement program but the reduction in time on mechanical ventilation was not statistically significant after adjusting for prognostic characteristics. CONCLUSION: The initial experience with STS registry in a Brazilian hospital was associated with improvement in most of targeted quality-indicators.

  18. The BioC-BioGRID corpus: full text articles annotated for curation of protein-protein and genetic interactions.

    Science.gov (United States)

    Islamaj Dogan, Rezarta; Kim, Sun; Chatr-Aryamontri, Andrew; Chang, Christie S; Oughtred, Rose; Rust, Jennifer; Wilbur, W John; Comeau, Donald C; Dolinski, Kara; Tyers, Mike

    2017-01-01

    A great deal of information on the molecular genetics and biochemistry of model organisms has been reported in the scientific literature. However, this data is typically described in free text form and is not readily amenable to computational analyses. To this end, the BioGRID database systematically curates the biomedical literature for genetic and protein interaction data. This data is provided in a standardized computationally tractable format and includes structured annotation of experimental evidence. BioGRID curation necessarily involves substantial human effort by expert curators who must read each publication to extract the relevant information. Computational text-mining methods offer the potential to augment and accelerate manual curation. To facilitate the development of practical text-mining strategies, a new challenge was organized in BioCreative V for the BioC task, the collaborative Biocurator Assistant Task. This was a non-competitive, cooperative task in which the participants worked together to build BioC-compatible modules into an integrated pipeline to assist BioGRID curators. As an integral part of this task, a test collection of full text articles was developed that contained both biological entity annotations (gene/protein and organism/species) and molecular interaction annotations (protein-protein and genetic interactions (PPIs and GIs)). This collection, which we call the BioC-BioGRID corpus, was annotated by four BioGRID curators over three rounds of annotation and contains 120 full text articles curated in a dataset representing two major model organisms, namely budding yeast and human. The BioC-BioGRID corpus contains annotations for 6409 mentions of genes and their Entrez Gene IDs, 186 mentions of organism names and their NCBI Taxonomy IDs, 1867 mentions of PPIs and 701 annotations of PPI experimental evidence statements, 856 mentions of GIs and 399 annotations of GI evidence statements. The purpose, characteristics and possible future

  19. Metingear: a development environment for annotating genome-scale metabolic models.

    Science.gov (United States)

    May, John W; James, A Gordon; Steinbeck, Christoph

    2013-09-01

    Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.

  20. Computational prediction of over-annotated protein-coding genes in the genome of Agrobacterium tumefaciens strain C58

    International Nuclear Information System (INIS)

    Yu Jia-Feng; Sui Tian-Xiang; Wang Ji-Hua; Wang Hong-Mei; Wang Chun-Ling; Jing Li

    2015-01-01

    Agrobacterium tumefaciens strain C58 is a type of pathogen that can cause tumors in some dicotyledonous plants. Ever since the genome of A. tumefaciens strain C58 was sequenced, the quality of annotation of its protein-coding genes has been queried continually, because the annotation varies greatly among different databases. In this paper, the questionable hypothetical genes were re-predicted by integrating the TN curve and Z curve methods. As a result, 30 genes originally annotated as “hypothetical” were discriminated as being non-coding sequences. By testing the re-prediction program 10 times on data sets composed of the function-known genes, the mean accuracy of 99.99% and mean Matthews correlation coefficient value of 0.9999 were obtained. Further sequence analysis and COG analysis showed that the re-annotation results were very reliable. This work can provide an efficient tool and data resources for future studies of A. tumefaciens strain C58. (special topic)

  1. Cyclebase 3.0: a multi-organism database on cell-cycle regulation and phenotypes

    DEFF Research Database (Denmark)

    Santos Delgado, Alberto; Wernersson, Rasmus; Jensen, Lars Juhl

    2015-01-01

    3.0, we have updated the content of the database to reflect changes to genome annotation, added new mRNAand protein expression data, and integrated cell-cycle phenotype information from high-content screens and model-organism databases. The new version of Cyclebase also features a new web interface...

  2. Data-based decision making for instructional improvement in primary education

    NARCIS (Netherlands)

    Gelderblom, Gerrit; Schildkamp, Kim; Pieters, Julius Marie; Ehren, Melanie Catharina Margaretha

    2016-01-01

    Data-based decision making can help teachers improve their instruction. Research shows that instruction has a strong impact on students' learning outcomes. This study investigates whether Dutch primary school teachers use data to improve their instruction. Four aspects of instruction were

  3. Comparison of concept recognizers for building the Open Biomedical Annotator

    Directory of Open Access Journals (Sweden)

    Rubin Daniel

    2009-09-01

    Full Text Available Abstract The National Center for Biomedical Ontology (NCBO is developing a system for automated, ontology-based access to online biomedical resources (Shah NH, et al.: Ontology-driven indexing of public datasets for translational bioinformatics. BMC Bioinformatics 2009, 10(Suppl 2:S1. The system's indexing workflow processes the text metadata of diverse resources such as datasets from GEO and ArrayExpress to annotate and index them with concepts from appropriate ontologies. This indexing requires the use of a concept-recognition tool to identify ontology concepts in the resource's textual metadata. In this paper, we present a comparison of two concept recognizers – NLM's MetaMap and the University of Michigan's Mgrep. We utilize a number of data sources and dictionaries to evaluate the concept recognizers in terms of precision, recall, speed of execution, scalability and customizability. Our evaluations demonstrate that Mgrep has a clear edge over MetaMap for large-scale service oriented applications. Based on our analysis we also suggest areas of potential improvements for Mgrep. We have subsequently used Mgrep to build the Open Biomedical Annotator service. The Annotator service has access to a large dictionary of biomedical terms derived from the United Medical Language System (UMLS and NCBO ontologies. The Annotator also leverages the hierarchical structure of the ontologies and their mappings to expand annotations. The Annotator service is available to the community as a REST Web service for creating ontology-based annotations of their data.

  4. CAZymes Analysis Toolkit (CAT): web service for searching and analyzing carbohydrate-active enzymes in a newly sequenced organism using CAZy database.

    Science.gov (United States)

    Park, Byung H; Karpinets, Tatiana V; Syed, Mustafa H; Leuze, Michael R; Uberbacher, Edward C

    2010-12-01

    The Carbohydrate-Active Enzyme (CAZy) database provides a rich set of manually annotated enzymes that degrade, modify, or create glycosidic bonds. Despite rich and invaluable information stored in the database, software tools utilizing this information for annotation of newly sequenced genomes by CAZy families are limited. We have employed two annotation approaches to fill the gap between manually curated high-quality protein sequences collected in the CAZy database and the growing number of other protein sequences produced by genome or metagenome sequencing projects. The first approach is based on a similarity search against the entire nonredundant sequences of the CAZy database. The second approach performs annotation using links or correspondences between the CAZy families and protein family domains. The links were discovered using the association rule learning algorithm applied to sequences from the CAZy database. The approaches complement each other and in combination achieved high specificity and sensitivity when cross-evaluated with the manually curated genomes of Clostridium thermocellum ATCC 27405 and Saccharophagus degradans 2-40. The capability of the proposed framework to predict the function of unknown protein domains and of hypothetical proteins in the genome of Neurospora crassa is demonstrated. The framework is implemented as a Web service, the CAZymes Analysis Toolkit, and is available at http://cricket.ornl.gov/cgi-bin/cat.cgi.

  5. iPfam: a database of protein family and domain interactions found in the Protein Data Bank.

    Science.gov (United States)

    Finn, Robert D; Miller, Benjamin L; Clements, Jody; Bateman, Alex

    2014-01-01

    The database iPfam, available at http://ipfam.org, catalogues Pfam domain interactions based on known 3D structures that are found in the Protein Data Bank, providing interaction data at the molecular level. Previously, the iPfam domain-domain interaction data was integrated within the Pfam database and website, but it has now been migrated to a separate database. This allows for independent development, improving data access and giving clearer separation between the protein family and interactions datasets. In addition to domain-domain interactions, iPfam has been expanded to include interaction data for domain bound small molecule ligands. Functional annotations are provided from source databases, supplemented by the incorporation of Wikipedia articles where available. iPfam (version 1.0) contains >9500 domain-domain and 15 500 domain-ligand interactions. The new website provides access to this data in a variety of ways, including interactive visualizations of the interaction data.

  6. Towards the VWO Annotation Service: a Success Story of the IMAGE RPI Expert Rating System

    Science.gov (United States)

    Reinisch, B. W.; Galkin, I. A.; Fung, S. F.; Benson, R. F.; Kozlov, A. V.; Khmyrov, G. M.; Garcia, L. N.

    2010-12-01

    . Especially useful are queries of the annotation database for successive plasmagrams containing echo traces. Several success stories of the RPI ERS using this capability will be discussed, particularly in terms of how they may be extended to develop the VWO Annotation Service.

  7. Semantic annotation of consumer health questions.

    Science.gov (United States)

    Kilicoglu, Halil; Ben Abacha, Asma; Mrabet, Yassine; Shooshan, Sonya E; Rodriguez, Laritza; Masterton, Kate; Demner-Fushman, Dina

    2018-02-06

    Consumers increasingly use online resources for their health information needs. While current search engines can address these needs to some extent, they generally do not take into account that most health information needs are complex and can only fully be expressed in natural language. Consumer health question answering (QA) systems aim to fill this gap. A major challenge in developing consumer health QA systems is extracting relevant semantic content from the natural language questions (question understanding). To develop effective question understanding tools, question corpora semantically annotated for relevant question elements are needed. In this paper, we present a two-part consumer health question corpus annotated with several semantic categories: named entities, question triggers/types, question frames, and question topic. The first part (CHQA-email) consists of relatively long email requests received by the U.S. National Library of Medicine (NLM) customer service, while the second part (CHQA-web) consists of shorter questions posed to MedlinePlus search engine as queries. Each question has been annotated by two annotators. The annotation methodology is largely the same between the two parts of the corpus; however, we also explain and justify the differences between them. Additionally, we provide information about corpus characteristics, inter-annotator agreement, and our attempts to measure annotation confidence in the absence of adjudication of annotations. The resulting corpus consists of 2614 questions (CHQA-email: 1740, CHQA-web: 874). Problems are the most frequent named entities, while treatment and general information questions are the most common question types. Inter-annotator agreement was generally modest: question types and topics yielded highest agreement, while the agreement for more complex frame annotations was lower. Agreement in CHQA-web was consistently higher than that in CHQA-email. Pairwise inter-annotator agreement proved most

  8. Predicting word sense annotation agreement

    DEFF Research Database (Denmark)

    Martinez Alonso, Hector; Johannsen, Anders Trærup; Lopez de Lacalle, Oier

    2015-01-01

    High agreement is a common objective when annotating data for word senses. However, a number of factors make perfect agreement impossible, e.g. the limitations of the sense inventories, the difficulty of the examples or the interpretation preferences of the annotations. Estimating potential...... agreement is thus a relevant task to supplement the evaluation of sense annotations. In this article we propose two methods to predict agreement on word-annotation instances. We experiment with a continuous representation and a three-way discretization of observed agreement. In spite of the difficulty...

  9. EchoBASE: an integrated post-genomic database for Escherichia coli.

    Science.gov (United States)

    Misra, Raju V; Horler, Richard S P; Reindl, Wolfgang; Goryanin, Igor I; Thomas, Gavin H

    2005-01-01

    EchoBASE (http://www.ecoli-york.org) is a relational database designed to contain and manipulate information from post-genomic experiments using the model bacterium Escherichia coli K-12. Its aim is to collate information from a wide range of sources to provide clues to the functions of the approximately 1500 gene products that have no confirmed cellular function. The database is built on an enhanced annotation of the updated genome sequence of strain MG1655 and the association of experimental data with the E.coli genes and their products. Experiments that can be held within EchoBASE include proteomics studies, microarray data, protein-protein interaction data, structural data and bioinformatics studies. EchoBASE also contains annotated information on 'orphan' enzyme activities from this microbe to aid characterization of the proteins that catalyse these elusive biochemical reactions.

  10. Alignment-Annotator web server: rendering and annotating sequence alignments.

    Science.gov (United States)

    Gille, Christoph; Fähling, Michael; Weyand, Birgit; Wieland, Thomas; Gille, Andreas

    2014-07-01

    Alignment-Annotator is a novel web service designed to generate interactive views of annotated nucleotide and amino acid sequence alignments (i) de novo and (ii) embedded in other software. All computations are performed at server side. Interactivity is implemented in HTML5, a language native to web browsers. The alignment is initially displayed using default settings and can be modified with the graphical user interfaces. For example, individual sequences can be reordered or deleted using drag and drop, amino acid color code schemes can be applied and annotations can be added. Annotations can be made manually or imported (BioDAS servers, the UniProt, the Catalytic Site Atlas and the PDB). Some edits take immediate effect while others require server interaction and may take a few seconds to execute. The final alignment document can be downloaded as a zip-archive containing the HTML files. Because of the use of HTML the resulting interactive alignment can be viewed on any platform including Windows, Mac OS X, Linux, Android and iOS in any standard web browser. Importantly, no plugins nor Java are required and therefore Alignment-Anotator represents the first interactive browser-based alignment visualization. http://www.bioinformatics.org/strap/aa/ and http://strap.charite.de/aa/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Annotation, submission and screening of repetitive elements in Repbase: RepbaseSubmitter and Censor

    Directory of Open Access Journals (Sweden)

    Hankus Lukasz

    2006-10-01

    Full Text Available Abstract Background Repbase is a reference database of eukaryotic repetitive DNA, which includes prototypic sequences of repeats and basic information described in annotations. Updating and maintenance of the database requires specialized tools, which we have created and made available for use with Repbase, and which may be useful as a template for other curated databases. Results We describe the software tools RepbaseSubmitter and Censor, which are designed to facilitate updating and screening the content of Repbase. RepbaseSubmitter is a java-based interface for formatting and annotating Repbase entries. It eliminates many common formatting errors, and automates actions such as calculation of sequence lengths and composition, thus facilitating curation of Repbase sequences. In addition, it has several features for predicting protein coding regions in sequences; searching and including Pubmed references in Repbase entries; and searching the NCBI taxonomy database for correct inclusion of species information and taxonomic position. Censor is a tool to rapidly identify repetitive elements by comparison to known repeats. It uses WU-BLAST for speed and sensitivity, and can conduct DNA-DNA, DNA-protein, or translated DNA-translated DNA searches of genomic sequence. Defragmented output includes a map of repeats present in the query sequence, with the options to report masked query sequence(s, repeat sequences found in the query, and alignments. Conclusion Censor and RepbaseSubmitter are available as both web-based services and downloadable versions. They can be found at http://www.girinst.org/repbase/submission.html (RepbaseSubmitter and http://www.girinst.org/censor/index.php (Censor.

  12. Improvement of medication event interventions through use of an electronic database.

    Science.gov (United States)

    Merandi, Jenna; Morvay, Shelly; Lewe, Dorcas; Stewart, Barb; Catt, Char; Chanthasene, Phillip P; McClead, Richard; Kappeler, Karl; Mirtallo, Jay M

    2013-10-01

    Patient safety enhancements achieved through the use of an electronic Web-based system for responding to adverse drug events (ADEs) are described. A two-phase initiative was carried out at an academic pediatric hospital to improve processes related to "medication event huddles" (interdisciplinary meetings focused on ADE interventions). Phase 1 of the initiative entailed a review of huddles and interventions over a 16-month baseline period during which multiple databases were used to manage the huddle process and staff interventions were assigned via manually generated e-mail reminders. Phase 1 data collection included ADE details (e.g., medications and staff involved, location and date of event) and the types and frequencies of interventions. Based on the phase 1 analysis, an electronic database was created to eliminate the use of multiple systems for huddle scheduling and documentation and to automatically generate e-mail reminders on assigned interventions. In phase 2 of the initiative, the impact of the database during a 5-month period was evaluated; the primary outcome was the percentage of interventions documented as completed after database implementation. During the postimplementation period, 44.7% of assigned interventions were completed, compared with a completion rate of 21% during the preimplementation period, and interventions documented as incomplete decreased from 77% to 43.7% (p Process changes, education, and medication order improvements were the most frequently documented categories of interventions. Implementation of a user-friendly electronic database improved intervention completion and documentation after medication event huddles.

  13. Canis mtDNA HV1 database: a web-based tool for collecting and surveying Canis mtDNA HV1 haplotype in public database.

    Science.gov (United States)

    Thai, Quan Ke; Chung, Dung Anh; Tran, Hoang-Dung

    2017-06-26

    Canine and wolf mitochondrial DNA haplotypes, which can be used for forensic or phylogenetic analyses, have been defined in various schemes depending on the region analyzed. In recent studies, the 582 bp fragment of the HV1 region is most commonly used. 317 different canine HV1 haplotypes have been reported in the rapidly growing public database GenBank. These reported haplotypes contain several inconsistencies in their haplotype information. To overcome this issue, we have developed a Canis mtDNA HV1 database. This database collects data on the HV1 582 bp region in dog mitochondrial DNA from the GenBank to screen and correct the inconsistencies. It also supports users in detection of new novel mutation profiles and assignment of new haplotypes. The Canis mtDNA HV1 database (CHD) contains 5567 nucleotide entries originating from 15 subspecies in the species Canis lupus. Of these entries, 3646 were haplotypes and grouped into 804 distinct sequences. 319 sequences were recognized as previously assigned haplotypes, while the remaining 485 sequences had new mutation profiles and were marked as new haplotype candidates awaiting further analysis for haplotype assignment. Of the 3646 nucleotide entries, only 414 were annotated with correct haplotype information, while 3232 had insufficient or lacked haplotype information and were corrected or modified before storing in the CHD. The CHD can be accessed at http://chd.vnbiology.com . It provides sequences, haplotype information, and a web-based tool for mtDNA HV1 haplotyping. The CHD is updated monthly and supplies all data for download. The Canis mtDNA HV1 database contains information about canine mitochondrial DNA HV1 sequences with reconciled annotation. It serves as a tool for detection of inconsistencies in GenBank and helps identifying new HV1 haplotypes. Thus, it supports the scientific community in naming new HV1 haplotypes and to reconcile existing annotation of HV1 582 bp sequences.

  14. Vesiclepedia: a compendium for extracellular vesicles with continuous community annotation.

    Directory of Open Access Journals (Sweden)

    Hina Kalra

    Full Text Available Extracellular vesicles (EVs are membraneous vesicles released by a variety of cells into their microenvironment. Recent studies have elucidated the role of EVs in intercellular communication, pathogenesis, drug, vaccine and gene-vector delivery, and as possible reservoirs of biomarkers. These findings have generated immense interest, along with an exponential increase in molecular data pertaining to EVs. Here, we describe Vesiclepedia, a manually curated compendium of molecular data (lipid, RNA, and protein identified in different classes of EVs from more than 300 independent studies published over the past several years. Even though databases are indispensable resources for the scientific community, recent studies have shown that more than 50% of the databases are not regularly updated. In addition, more than 20% of the database links are inactive. To prevent such database and link decay, we have initiated a continuous community annotation project with the active involvement of EV researchers. The EV research community can set a gold standard in data sharing with Vesiclepedia, which could evolve as a primary resource for the field.

  15. Data Quality Assessment and Recommendations to Improve the Quality of Hemodialysis Database

    Directory of Open Access Journals (Sweden)

    Neda Firouraghi

    2018-01-01

    Full Text Available Introduction: Since clinical data contain abnormalities, quality assessment and reporting of data errors are necessary. Data quality analysis consists of developing strategies, making recommendations to avoid future errors and improving the quality of data entry by identifying error types and their causes. Therefore, this approach can be extremely useful to improve the quality of the databases. The aim of this study was to analyze hemodialysis (HD patients’ data in order to improve the quality of data entry and avoid future errors. Method: The study was done on Shiraz University of Medical Sciences HD database in 2015. The database consists of 2367 patients who had at least 12 months follow up (22.34±11.52 months in 2012-2014. Duplicated data were removed; outliers were detected based on statistical methods, expert opinion and the relationship between variables; then, the missing values were handled in 72 variables by using IBM SPSS Statistics 22 in order to improve the quality of the database. According to the results, some recommendations were given to improve the data entry process. Results: The variables had outliers in the range of 0-9.28 percent. Seven variables had missing values over 20 percent and in the others they were between 0 and 19.73 percent. The majority of missing values belong to serum alkaline phosphatase, uric acid, high and low density lipoprotein, total iron binding capacity, hepatitis B surface antibody titer, and parathyroid hormone. The variables with displacement (the values of two or more variables were recorded in the wrong attribute were weight, serum creatinine, blood urea nitrogen, systolic and diastolic blood pressure. These variables may lead to decreased data quality. Conclusion: According to the results and expert opinion, applying some data entry principles, such as defining ranges of values, using the relationship between hemodialysis features, developing alert systems about empty or duplicated data and

  16. dEMBF: A Comprehensive Database of Enzymes of Microalgal Biofuel Feedstock.

    Science.gov (United States)

    Misra, Namrata; Panda, Prasanna Kumar; Parida, Bikram Kumar; Mishra, Barada Kanta

    2016-01-01

    Microalgae have attracted wide attention as one of the most versatile renewable feedstocks for production of biofuel. To develop genetically engineered high lipid yielding algal strains, a thorough understanding of the lipid biosynthetic pathway and the underpinning enzymes is essential. In this work, we have systematically mined the genomes of fifteen diverse algal species belonging to Chlorophyta, Heterokontophyta, Rhodophyta, and Haptophyta, to identify and annotate the putative enzymes of lipid metabolic pathway. Consequently, we have also developed a database, dEMBF (Database of Enzymes of Microalgal Biofuel Feedstock), which catalogues the complete list of identified enzymes along with their computed annotation details including length, hydrophobicity, amino acid composition, subcellular location, gene ontology, KEGG pathway, orthologous group, Pfam domain, intron-exon organization, transmembrane topology, and secondary/tertiary structural data. Furthermore, to facilitate functional and evolutionary study of these enzymes, a collection of built-in applications for BLAST search, motif identification, sequence and phylogenetic analysis have been seamlessly integrated into the database. dEMBF is the first database that brings together all enzymes responsible for lipid synthesis from available algal genomes, and provides an integrative platform for enzyme inquiry and analysis. This database will be extremely useful for algal biofuel research. It can be accessed at http://bbprof.immt.res.in/embf.

  17. BG7: A New Approach for Bacterial Genome Annotation Designed for Next Generation Sequencing Data

    Science.gov (United States)

    Pareja-Tobes, Pablo; Manrique, Marina; Pareja-Tobes, Eduardo; Pareja, Eduardo; Tobes, Raquel

    2012-01-01

    BG7 is a new system for de novo bacterial, archaeal and viral genome annotation based on a new approach specifically designed for annotating genomes sequenced with next generation sequencing technologies. The system is versatile and able to annotate genes even in the step of preliminary assembly of the genome. It is especially efficient detecting unexpected genes horizontally acquired from bacterial or archaeal distant genomes, phages, plasmids, and mobile elements. From the initial phases of the gene annotation process, BG7 exploits the massive availability of annotated protein sequences in databases. BG7 predicts ORFs and infers their function based on protein similarity with a wide set of reference proteins, integrating ORF prediction and functional annotation phases in just one step. BG7 is especially tolerant to sequencing errors in start and stop codons, to frameshifts, and to assembly or scaffolding errors. The system is also tolerant to the high level of gene fragmentation which is frequently found in not fully assembled genomes. BG7 current version – which is developed in Java, takes advantage of Amazon Web Services (AWS) cloud computing features, but it can also be run locally in any operating system. BG7 is a fast, automated and scalable system that can cope with the challenge of analyzing the huge amount of genomes that are being sequenced with NGS technologies. Its capabilities and efficiency were demonstrated in the 2011 EHEC Germany outbreak in which BG7 was used to get the first annotations right the next day after the first entero-hemorrhagic E. coli genome sequences were made publicly available. The suitability of BG7 for genome annotation has been proved for Illumina, 454, Ion Torrent, and PacBio sequencing technologies. Besides, thanks to its plasticity, our system could be very easily adapted to work with new technologies in the future. PMID:23185310

  18. BG7: a new approach for bacterial genome annotation designed for next generation sequencing data.

    Directory of Open Access Journals (Sweden)

    Pablo Pareja-Tobes

    Full Text Available BG7 is a new system for de novo bacterial, archaeal and viral genome annotation based on a new approach specifically designed for annotating genomes sequenced with next generation sequencing technologies. The system is versatile and able to annotate genes even in the step of preliminary assembly of the genome. It is especially efficient detecting unexpected genes horizontally acquired from bacterial or archaeal distant genomes, phages, plasmids, and mobile elements. From the initial phases of the gene annotation process, BG7 exploits the massive availability of annotated protein sequences in databases. BG7 predicts ORFs and infers their function based on protein similarity with a wide set of reference proteins, integrating ORF prediction and functional annotation phases in just one step. BG7 is especially tolerant to sequencing errors in start and stop codons, to frameshifts, and to assembly or scaffolding errors. The system is also tolerant to the high level of gene fragmentation which is frequently found in not fully assembled genomes. BG7 current version - which is developed in Java, takes advantage of Amazon Web Services (AWS cloud computing features, but it can also be run locally in any operating system. BG7 is a fast, automated and scalable system that can cope with the challenge of analyzing the huge amount of genomes that are being sequenced with NGS technologies. Its capabilities and efficiency were demonstrated in the 2011 EHEC Germany outbreak in which BG7 was used to get the first annotations right the next day after the first entero-hemorrhagic E. coli genome sequences were made publicly available. The suitability of BG7 for genome annotation has been proved for Illumina, 454, Ion Torrent, and PacBio sequencing technologies. Besides, thanks to its plasticity, our system could be very easily adapted to work with new technologies in the future.

  19. Annotation as a New Paradigm in Research Archiving. Two Case Studies: Republic of Letters- Hebrew Text Database

    NARCIS (Netherlands)

    Roorda, D.; van den Heuvel, C.M.J.M.

    2012-01-01

    We outline a paradigm to preserve results of digital scholarship, whether they are query results, feature values, or topic assignments. This paradigm is characterized by using annotations as multifunctional carriers and making them portable. The testing grounds we have chosen are two significant

  20. UnoViS: the MedIT public unobtrusive vital signs database.

    Science.gov (United States)

    Wartzek, Tobias; Czaplik, Michael; Antink, Christoph Hoog; Eilebrecht, Benjamin; Walocha, Rafael; Leonhardt, Steffen

    2015-01-01

    While PhysioNet is a large database for standard clinical vital signs measurements, such a database does not exist for unobtrusively measured signals. This inhibits progress in the vital area of signal processing for unobtrusive medical monitoring as not everybody owns the specific measurement systems to acquire signals. Furthermore, if no common database exists, a comparison between different signal processing approaches is not possible. This gap will be closed by our UnoViS database. It contains different recordings in various scenarios ranging from a clinical study to measurements obtained while driving a car. Currently, 145 records with a total of 16.2 h of measurement data is available, which are provided as MATLAB files or in the PhysioNet WFDB file format. In its initial state, only (multichannel) capacitive ECG and unobtrusive PPG signals are, together with a reference ECG, included. All ECG signals contain annotations by a peak detector and by a medical expert. A dataset from a clinical study contains further clinical annotations. Additionally, supplementary functions are provided, which simplify the usage of the database and thus the development and evaluation of new algorithms. The development of urgently needed methods for very robust parameter extraction or robust signal fusion in view of frequent severe motion artifacts in unobtrusive monitoring is now possible with the database.

  1. MetaPathways v2.5: quantitative functional, taxonomic and usability improvements.

    Science.gov (United States)

    Konwar, Kishori M; Hanson, Niels W; Bhatia, Maya P; Kim, Dongjae; Wu, Shang-Ju; Hahn, Aria S; Morgan-Lang, Connor; Cheung, Hiu Kan; Hallam, Steven J

    2015-10-15

    Next-generation sequencing is producing vast amounts of sequence information from natural and engineered ecosystems. Although this data deluge has an enormous potential to transform our lives, knowledge creation and translation need software applications that scale with increasing data processing and analysis requirements. Here, we present improvements to MetaPathways, an annotation and analysis pipeline for environmental sequence information that expedites this transformation. We specifically address pathway prediction hazards through integration of a weighted taxonomic distance and enable quantitative comparison of assembled annotations through a normalized read-mapping measure. Additionally, we improve LAST homology searches through BLAST-equivalent E-values and output formats that are natively compatible with prevailing software applications. Finally, an updated graphical user interface allows for keyword annotation query and projection onto user-defined functional gene hierarchies, including the Carbohydrate-Active Enzyme database. MetaPathways v2.5 is available on GitHub: http://github.com/hallamlab/metapathways2. shallam@mail.ubc.ca Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  2. Objective-guided image annotation.

    Science.gov (United States)

    Mao, Qi; Tsang, Ivor Wai-Hung; Gao, Shenghua

    2013-04-01

    Automatic image annotation, which is usually formulated as a multi-label classification problem, is one of the major tools used to enhance the semantic understanding of web images. Many multimedia applications (e.g., tag-based image retrieval) can greatly benefit from image annotation. However, the insufficient performance of image annotation methods prevents these applications from being practical. On the other hand, specific measures are usually designed to evaluate how well one annotation method performs for a specific objective or application, but most image annotation methods do not consider optimization of these measures, so that they are inevitably trapped into suboptimal performance of these objective-specific measures. To address this issue, we first summarize a variety of objective-guided performance measures under a unified representation. Our analysis reveals that macro-averaging measures are very sensitive to infrequent keywords, and hamming measure is easily affected by skewed distributions. We then propose a unified multi-label learning framework, which directly optimizes a variety of objective-specific measures of multi-label learning tasks. Specifically, we first present a multilayer hierarchical structure of learning hypotheses for multi-label problems based on which a variety of loss functions with respect to objective-guided measures are defined. And then, we formulate these loss functions as relaxed surrogate functions and optimize them by structural SVMs. According to the analysis of various measures and the high time complexity of optimizing micro-averaging measures, in this paper, we focus on example-based measures that are tailor-made for image annotation tasks but are seldom explored in the literature. Experiments show consistency with the formal analysis on two widely used multi-label datasets, and demonstrate the superior performance of our proposed method over state-of-the-art baseline methods in terms of example-based measures on four

  3. The Eimeria Transcript DB: an integrated resource for annotated transcripts of protozoan parasites of the genus Eimeria

    Science.gov (United States)

    Rangel, Luiz Thibério; Novaes, Jeniffer; Durham, Alan M.; Madeira, Alda Maria B. N.; Gruber, Arthur

    2013-01-01

    Parasites of the genus Eimeria infect a wide range of vertebrate hosts, including chickens. We have recently reported a comparative analysis of the transcriptomes of Eimeria acervulina, Eimeria maxima and Eimeria tenella, integrating ORESTES data produced by our group and publicly available Expressed Sequence Tags (ESTs). All cDNA reads have been assembled, and the reconstructed transcripts have been submitted to a comprehensive functional annotation pipeline. Additional studies included orthology assignment across apicomplexan parasites and clustering analyses of gene expression profiles among different developmental stages of the parasites. To make all this body of information publicly available, we constructed the Eimeria Transcript Database (EimeriaTDB), a web repository that provides access to sequence data, annotation and comparative analyses. Here, we describe the web interface, available sequence data sets and query tools implemented on the site. The main goal of this work is to offer a public repository of sequence and functional annotation data of reconstructed transcripts of parasites of the genus Eimeria. We believe that EimeriaTDB will represent a valuable and complementary resource for the Eimeria scientific community and for those researchers interested in comparative genomics of apicomplexan parasites. Database URL: http://www.coccidia.icb.usp.br/eimeriatdb/ PMID:23411718

  4. DPTEdb, an integrative database of transposable elements in dioecious plants.

    Science.gov (United States)

    Li, Shu-Fen; Zhang, Guo-Jun; Zhang, Xue-Jin; Yuan, Jin-Hong; Deng, Chuan-Liang; Gu, Lian-Feng; Gao, Wu-Jun

    2016-01-01

    Dioecious plants usually harbor 'young' sex chromosomes, providing an opportunity to study the early stages of sex chromosome evolution. Transposable elements (TEs) are mobile DNA elements frequently found in plants and are suggested to play important roles in plant sex chromosome evolution. The genomes of several dioecious plants have been sequenced, offering an opportunity to annotate and mine the TE data. However, comprehensive and unified annotation of TEs in these dioecious plants is still lacking. In this study, we constructed a dioecious plant transposable element database (DPTEdb). DPTEdb is a specific, comprehensive and unified relational database and web interface. We used a combination of de novo, structure-based and homology-based approaches to identify TEs from the genome assemblies of previously published data, as well as our own. The database currently integrates eight dioecious plant species and a total of 31 340 TEs along with classification information. DPTEdb provides user-friendly web interfaces to browse, search and download the TE sequences in the database. Users can also use tools, including BLAST, GetORF, HMMER, Cut sequence and JBrowse, to analyze TE data. Given the role of TEs in plant sex chromosome evolution, the database will contribute to the investigation of TEs in structural, functional and evolutionary dynamics of the genome of dioecious plants. In addition, the database will supplement the research of sex diversification and sex chromosome evolution of dioecious plants.Database URL: http://genedenovoweb.ticp.net:81/DPTEdb/index.php. © The Author(s) 2016. Published by Oxford University Press.

  5. Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'

    Directory of Open Access Journals (Sweden)

    Snowdon Stuart

    2009-07-01

    Full Text Available Abstract Background Metabolomics experiments using Mass Spectrometry (MS technology measure the mass to charge ratio (m/z and intensity of ionised molecules in crude extracts of complex biological samples to generate high dimensional metabolite 'fingerprint' or metabolite 'profile' data. High resolution MS instruments perform routinely with a mass accuracy of Results Metabolite 'structures' harvested from publicly accessible databases were converted into a common format to generate a comprehensive archive in MZedDB. 'Rules' were derived from chemical information that allowed MZedDB to generate a list of adducts and neutral loss fragments putatively able to form for each structure and calculate, on the fly, the exact molecular weight of every potential ionisation product to provide targets for annotation searches based on accurate mass. We demonstrate that data matrices representing populations of ionisation products generated from different biological matrices contain a large proportion (sometimes > 50% of molecular isotopes, salt adducts and neutral loss fragments. Correlation analysis of ESI-MS data features confirmed the predicted relationships of m/z signals. An integrated isotope enumerator in MZedDB allowed verification of exact isotopic pattern distributions to corroborate experimental data. Conclusion We conclude that although ultra-high accurate mass instruments provide major insight into the chemical diversity of biological extracts, the facile annotation of a large proportion of signals is not possible by simple, automated query of current databases using computed molecular formulae. Parameterising MZedDB to take into account predicted ionisation behaviour and the biological source of any sample improves greatly both the frequency and accuracy of potential annotation 'hits' in ESI-MS data.

  6. Nutrition & Adolescent Pregnancy: A Selected Annotated Bibliography.

    Science.gov (United States)

    National Agricultural Library (USDA), Washington, DC.

    This annotated bibliography on nutrition and adolescent pregnancy is intended to be a source of technical assistance for nurses, nutritionists, physicians, educators, social workers, and other personnel concerned with improving the health of teenage mothers and their babies. It is divided into two major sections. The first section lists selected…

  7. Protannotator: a semiautomated pipeline for chromosome-wise functional annotation of the "missing" human proteome.

    Science.gov (United States)

    Islam, Mohammad T; Garg, Gagan; Hancock, William S; Risk, Brian A; Baker, Mark S; Ranganathan, Shoba

    2014-01-03

    The chromosome-centric human proteome project (C-HPP) aims to define the complete set of proteins encoded in each human chromosome. The neXtProt database (September 2013) lists 20,128 proteins for the human proteome, of which 3831 human proteins (∼19%) are considered "missing" according to the standard metrics table (released September 27, 2013). In support of the C-HPP initiative, we have extended the annotation strategy developed for human chromosome 7 "missing" proteins into a semiautomated pipeline to functionally annotate the "missing" human proteome. This pipeline integrates a suite of bioinformatics analysis and annotation software tools to identify homologues and map putative functional signatures, gene ontology, and biochemical pathways. From sequential BLAST searches, we have primarily identified homologues from reviewed nonhuman mammalian proteins with protein evidence for 1271 (33.2%) "missing" proteins, followed by 703 (18.4%) homologues from reviewed nonhuman mammalian proteins and subsequently 564 (14.7%) homologues from reviewed human proteins. Functional annotations for 1945 (50.8%) "missing" proteins were also determined. To accelerate the identification of "missing" proteins from proteomics studies, we generated proteotypic peptides in silico. Matching these proteotypic peptides to ENCODE proteogenomic data resulted in proteomic evidence for 107 (2.8%) of the 3831 "missing proteins, while evidence from a recent membrane proteomic study supported the existence for another 15 "missing" proteins. The chromosome-wise functional annotation of all "missing" proteins is freely available to the scientific community through our web server (http://biolinfo.org/protannotator).

  8. SoyTEdb: a comprehensive database of transposable elements in the soybean genome

    Directory of Open Access Journals (Sweden)

    Zhu Liucun

    2010-02-01

    Full Text Available Abstract Background Transposable elements are the most abundant components of all characterized genomes of higher eukaryotes. It has been documented that these elements not only contribute to the shaping and reshaping of their host genomes, but also play significant roles in regulating gene expression, altering gene function, and creating new genes. Thus, complete identification of transposable elements in sequenced genomes and construction of comprehensive transposable element databases are essential for accurate annotation of genes and other genomic components, for investigation of potential functional interaction between transposable elements and genes, and for study of genome evolution. The recent availability of the soybean genome sequence has provided an unprecedented opportunity for discovery, and structural and functional characterization of transposable elements in this economically important legume crop. Description Using a combination of structure-based and homology-based approaches, a total of 32,552 retrotransposons (Class I and 6,029 DNA transposons (Class II with clear boundaries and insertion sites were structurally annotated and clearly categorized, and a soybean transposable element database, SoyTEdb, was established. These transposable elements have been anchored in and integrated with the soybean physical map and genetic map, and are browsable and visualizable at any scale along the 20 soybean chromosomes, along with predicted genes and other sequence annotations. BLAST search and other infrastracture tools were implemented to facilitate annotation of transposable elements or fragments from soybean and other related legume species. The majority (> 95% of these elements (particularly a few hundred low-copy-number families are first described in this study. Conclusion SoyTEdb provides resources and information related to transposable elements in the soybean genome, representing the most comprehensive and the largest manually

  9. WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

    Directory of Open Access Journals (Sweden)

    Parichit Sharma

    Full Text Available The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture

  10. WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

    Science.gov (United States)

    Sharma, Parichit; Mantri, Shrikant S

    2014-01-01

    The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design

  11. Computational prediction of over-annotated protein-coding genes in the genome of Agrobacterium tumefaciens strain C58

    Science.gov (United States)

    Yu, Jia-Feng; Sui, Tian-Xiang; Wang, Hong-Mei; Wang, Chun-Ling; Jing, Li; Wang, Ji-Hua

    2015-12-01

    Agrobacterium tumefaciens strain C58 is a type of pathogen that can cause tumors in some dicotyledonous plants. Ever since the genome of A. tumefaciens strain C58 was sequenced, the quality of annotation of its protein-coding genes has been queried continually, because the annotation varies greatly among different databases. In this paper, the questionable hypothetical genes were re-predicted by integrating the TN curve and Z curve methods. As a result, 30 genes originally annotated as “hypothetical” were discriminated as being non-coding sequences. By testing the re-prediction program 10 times on data sets composed of the function-known genes, the mean accuracy of 99.99% and mean Matthews correlation coefficient value of 0.9999 were obtained. Further sequence analysis and COG analysis showed that the re-annotation results were very reliable. This work can provide an efficient tool and data resources for future studies of A. tumefaciens strain C58. Project supported by the National Natural Science Foundation of China (Grant Nos. 61302186 and 61271378) and the Funding from the State Key Laboratory of Bioelectronics of Southeast University.

  12. PlantNATsDB: a comprehensive database of plant natural antisense transcripts.

    Science.gov (United States)

    Chen, Dijun; Yuan, Chunhui; Zhang, Jian; Zhang, Zhao; Bai, Lin; Meng, Yijun; Chen, Ling-Ling; Chen, Ming

    2012-01-01

    Natural antisense transcripts (NATs), as one type of regulatory RNAs, occur prevalently in plant genomes and play significant roles in physiological and pathological processes. Although their important biological functions have been reported widely, a comprehensive database is lacking up to now. Consequently, we constructed a plant NAT database (PlantNATsDB) involving approximately 2 million NAT pairs in 69 plant species. GO annotation and high-throughput small RNA sequencing data currently available were integrated to investigate the biological function of NATs. PlantNATsDB provides various user-friendly web interfaces to facilitate the presentation of NATs and an integrated, graphical network browser to display the complex networks formed by different NATs. Moreover, a 'Gene Set Analysis' module based on GO annotation was designed to dig out the statistical significantly overrepresented GO categories from the specific NAT network. PlantNATsDB is currently the most comprehensive resource of NATs in the plant kingdom, which can serve as a reference database to investigate the regulatory function of NATs. The PlantNATsDB is freely available at http://bis.zju.edu.cn/pnatdb/.

  13. HOLLYWOOD: a comparative relational database of alternative splicing.

    Science.gov (United States)

    Holste, Dirk; Huo, George; Tung, Vivian; Burge, Christopher B

    2006-01-01

    RNA splicing is an essential step in gene expression, and is often variable, giving rise to multiple alternatively spliced mRNA and protein isoforms from a single gene locus. The design of effective databases to support experimental and computational investigations of alternative splicing (AS) is a significant challenge. In an effort to integrate accurate exon and splice site annotation with current knowledge about splicing regulatory elements and predicted AS events, and to link information about the splicing of orthologous genes in different species, we have developed the Hollywood system. This database was built upon genomic annotation of splicing patterns of known genes derived from spliced alignment of complementary DNAs (cDNAs) and expressed sequence tags, and links features such as splice site sequence and strength, exonic splicing enhancers and silencers, conserved and non-conserved patterns of splicing, and cDNA library information for inferred alternative exons. Hollywood was implemented as a relational database and currently contains comprehensive information for human and mouse. It is accompanied by a web query tool that allows searches for sets of exons with specific splicing characteristics or splicing regulatory element composition, or gives a graphical or sequence-level summary of splicing patterns for a specific gene. A streamlined graphical representation of gene splicing patterns is provided, and these patterns can alternatively be layered onto existing information in the UCSC Genome Browser. The database is accessible at http://hollywood.mit.edu.

  14. Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center

    Science.gov (United States)

    Wattam, Alice R.; Davis, James J.; Assaf, Rida; Boisvert, Sébastien; Brettin, Thomas; Bun, Christopher; Conrad, Neal; Dietrich, Emily M.; Disz, Terry; Gabbard, Joseph L.; Gerdes, Svetlana; Henry, Christopher S.; Kenyon, Ronald W.; Machi, Dustin; Mao, Chunhong; Nordberg, Eric K.; Olsen, Gary J.; Murphy-Olson, Daniel E.; Olson, Robert; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Shukla, Maulik; Vonstein, Veronika; Warren, Andrew; Xia, Fangfang; Yoo, Hyunseung; Stevens, Rick L.

    2017-01-01

    The Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center (https://www.patricbrc.org). Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user-created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data. Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by ‘virtual integration’ to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics. PMID:27899627

  15. Improved annotation of 3' untranslated regions and complex loci by combination of strand-specific direct RNA sequencing, RNA-Seq and ESTs.

    Directory of Open Access Journals (Sweden)

    Nicholas J Schurch

    Full Text Available The reference annotations made for a genome sequence provide the framework for all subsequent analyses of the genome. Correct and complete annotation in addition to the underlying genomic sequence is particularly important when interpreting the results of RNA-seq experiments where short sequence reads are mapped against the genome and assigned to genes according to the annotation. Inconsistencies in annotations between the reference and the experimental system can lead to incorrect interpretation of the effect on RNA expression of an experimental treatment or mutation in the system under study. Until recently, the genome-wide annotation of 3' untranslated regions received less attention than coding regions and the delineation of intron/exon boundaries. In this paper, data produced for samples in Human, Chicken and A. thaliana by the novel single-molecule, strand-specific, Direct RNA Sequencing technology from Helicos Biosciences which locates 3' polyadenylation sites to within +/- 2 nt, were combined with archival EST and RNA-Seq data. Nine examples are illustrated where this combination of data allowed: (1 gene and 3' UTR re-annotation (including extension of one 3' UTR by 5.9 kb; (2 disentangling of gene expression in complex regions; (3 clearer interpretation of small RNA expression and (4 identification of novel genes. While the specific examples displayed here may become obsolete as genome sequences and their annotations are refined, the principles laid out in this paper will be of general use both to those annotating genomes and those seeking to interpret existing publically available annotations in the context of their own experimental data.

  16. Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS

    DEFF Research Database (Denmark)

    Wang, Yunpeng; Thompson, Wesley K; Schork, Andrew J

    2016-01-01

    Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotr...

  17. Essential Requirements for Digital Annotation Systems

    Directory of Open Access Journals (Sweden)

    ADRIANO, C. M.

    2012-06-01

    Full Text Available Digital annotation systems are usually based on partial scenarios and arbitrary requirements. Accidental and essential characteristics are usually mixed in non explicit models. Documents and annotations are linked together accidentally according to the current technology, allowing for the development of disposable prototypes, but not to the support of non-functional requirements such as extensibility, robustness and interactivity. In this paper we perform a careful analysis on the concept of annotation, studying the scenarios supported by digital annotation tools. We also derived essential requirements based on a classification of annotation systems applied to existing tools. The analysis performed and the proposed classification can be applied and extended to other type of collaborative systems.

  18. The Ensembl genome database project.

    Science.gov (United States)

    Hubbard, T; Barker, D; Birney, E; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Huminiecki, L; Kasprzyk, A; Lehvaslaiho, H; Lijnzaad, P; Melsopp, C; Mongin, E; Pettett, R; Pocock, M; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Clamp, M

    2002-01-01

    The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of the human genome sequence, with confirmed gene predictions that have been integrated with external data sources, and is available as either an interactive web site or as flat files. It is also an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements from sequence analysis to data storage and visualisation. The Ensembl site is one of the leading sources of human genome sequence annotation and provided much of the analysis for publication by the international human genome project of the draft genome. The Ensembl system is being installed around the world in both companies and academic sites on machines ranging from supercomputers to laptops.

  19. Annotation of phenotypic diversity: decoupling data curation and ontology curation using Phenex.

    Science.gov (United States)

    Balhoff, James P; Dahdul, Wasila M; Dececchi, T Alexander; Lapp, Hilmar; Mabee, Paula M; Vision, Todd J

    2014-01-01

    Phenex (http://phenex.phenoscape.org/) is a desktop application for semantically annotating the phenotypic character matrix datasets common in evolutionary biology. Since its initial publication, we have added new features that address several major bottlenecks in the efficiency of the phenotype curation process: allowing curators during the data curation phase to provisionally request terms that are not yet available from a relevant ontology; supporting quality control against annotation guidelines to reduce later manual review and revision; and enabling the sharing of files for collaboration among curators. We decoupled data annotation from ontology development by creating an Ontology Request Broker (ORB) within Phenex. Curators can use the ORB to request a provisional term for use in data annotation; the provisional term can be automatically replaced with a permanent identifier once the term is added to an ontology. We added a set of annotation consistency checks to prevent common curation errors, reducing the need for later correction. We facilitated collaborative editing by improving the reliability of Phenex when used with online folder sharing services, via file change monitoring and continual autosave. With the addition of these new features, and in particular the Ontology Request Broker, Phenex users have been able to focus more effectively on data annotation. Phenoscape curators using Phenex have reported a smoother annotation workflow, with much reduced interruptions from ontology maintenance and file management issues.

  20. Minimization of annotation work: diagnosis of mammographic masses via active learning

    Science.gov (United States)

    Zhao, Yu; Zhang, Jingyang; Xie, Hongzhi; Zhang, Shuyang; Gu, Lixu

    2018-06-01

    The prerequisite for establishing an effective prediction system for mammographic diagnosis is the annotation of each mammographic image. The manual annotation work is time-consuming and laborious, which becomes a great hindrance for researchers. In this article, we propose a novel active learning algorithm that can adequately address this problem, leading to the minimization of the labeling costs on the premise of guaranteed performance. Our proposed method is different from the existing active learning methods designed for the general problem as it is specifically designed for mammographic images. Through its modified discriminant functions and improved sample query criteria, the proposed method can fully utilize the pairing of mammographic images and select the most valuable images from both the mediolateral and craniocaudal views. Moreover, in order to extend active learning to the ordinal regression problem, which has no precedent in existing studies, but is essential for mammographic diagnosis (mammographic diagnosis is not only a classification task, but also an ordinal regression task for predicting an ordinal variable, viz. the malignancy risk of lesions), multiple sample query criteria need to be taken into consideration simultaneously. We formulate it as a criteria integration problem and further present an algorithm based on self-adaptive weighted rank aggregation to achieve a good solution. The efficacy of the proposed method was demonstrated on thousands of mammographic images from the digital database for screening mammography. The labeling costs of obtaining optimal performance in the classification and ordinal regression task respectively fell to 33.8 and 19.8 percent of their original costs. The proposed method also generated 1228 wins, 369 ties and 47 losses for the classification task, and 1933 wins, 258 ties and 185 losses for the ordinal regression task compared to the other state-of-the-art active learning algorithms. By taking the

  1. Making web annotations persistent over time

    Energy Technology Data Exchange (ETDEWEB)

    Sanderson, Robert [Los Alamos National Laboratory; Van De Sompel, Herbert [Los Alamos National Laboratory

    2010-01-01

    As Digital Libraries (DL) become more aligned with the web architecture, their functional components need to be fundamentally rethought in terms of URIs and HTTP. Annotation, a core scholarly activity enabled by many DL solutions, exhibits a clearly unacceptable characteristic when existing models are applied to the web: due to the representations of web resources changing over time, an annotation made about a web resource today may no longer be relevant to the representation that is served from that same resource tomorrow. We assume the existence of archived versions of resources, and combine the temporal features of the emerging Open Annotation data model with the capability offered by the Memento framework that allows seamless navigation from the URI of a resource to archived versions of that resource, and arrive at a solution that provides guarantees regarding the persistence of web annotations over time. More specifically, we provide theoretical solutions and proof-of-concept experimental evaluations for two problems: reconstructing an existing annotation so that the correct archived version is displayed for all resources involved in the annotation, and retrieving all annotations that involve a given archived version of a web resource.

  2. Protein annotation from protein interaction networks and Gene Ontology.

    Science.gov (United States)

    Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

    2011-10-01

    We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

  3. Aspergillus flavus Blast2GO gene ontology database: elevated growth temperature alters amino acid metabolism

    Science.gov (United States)

    The availability of a representative gene ontology (GO) database is a prerequisite for a successful functional genomics study. Using online Blast2GO resources we constructed a GO database of Aspergillus flavus. Of the predicted total 13,485 A. flavus genes 8,987 were annotated with GO terms. The mea...

  4. UNITE: a database providing web-based methods for the molecular identification of ectomycorrhizal fungi.

    Science.gov (United States)

    Kõljalg, Urmas; Larsson, Karl-Henrik; Abarenkov, Kessy; Nilsson, R Henrik; Alexander, Ian J; Eberhardt, Ursula; Erland, Susanne; Høiland, Klaus; Kjøller, Rasmus; Larsson, Ellen; Pennanen, Taina; Sen, Robin; Taylor, Andy F S; Tedersoo, Leho; Vrålstad, Trude; Ursing, Björn M

    2005-06-01

    Identification of ectomycorrhizal (ECM) fungi is often achieved through comparisons of ribosomal DNA internal transcribed spacer (ITS) sequences with accessioned sequences deposited in public databases. A major problem encountered is that annotation of the sequences in these databases is not always complete or trustworthy. In order to overcome this deficiency, we report on UNITE, an open-access database. UNITE comprises well annotated fungal ITS sequences from well defined herbarium specimens that include full herbarium reference identification data, collector/source and ecological data. At present UNITE contains 758 ITS sequences from 455 species and 67 genera of ECM fungi. UNITE can be searched by taxon name, via sequence similarity using blastn, and via phylogenetic sequence identification using galaxie. Following implementation, galaxie performs a phylogenetic analysis of the query sequence after alignment either to pre-existing generic alignments, or to matches retrieved from a blast search on the UNITE data. It should be noted that the current version of UNITE is dedicated to the reliable identification of ECM fungi. The UNITE database is accessible through the URL http://unite.zbi.ee

  5. Monitoring outcomes with relational databases: does it improve quality of care?

    Science.gov (United States)

    Clemmer, Terry P

    2004-12-01

    There are 3 key ingredients in improving quality of medial care: 1) using a scientific process of improvement, 2) executing the process at the lowest possible level in the organization, and 3) measuring the results of any change reliably. Relational databases when used within these guidelines are of great value in these efforts if they contain reliable information that is pertinent to the project and used in a scientific process of quality improvement by a front line team. Unfortunately, the data are frequently unreliable and/or not pertinent to the local process and is used by persons at very high levels in the organization without a scientific process and without reliable measurement of the outcome. Under these circumstances the effectiveness of relational databases in improving care is marginal at best, frequently wasteful and has the potential to be harmful. This article explores examples of these concepts.

  6. Using relational databases for improved sequence similarity searching and large-scale genomic analyses.

    Science.gov (United States)

    Mackey, Aaron J; Pearson, William R

    2004-10-01

    Relational databases are designed to integrate diverse types of information and manage large sets of search results, greatly simplifying genome-scale analyses. Relational databases are essential for management and analysis of large-scale sequence analyses, and can also be used to improve the statistical significance of similarity searches by focusing on subsets of sequence libraries most likely to contain homologs. This unit describes using relational databases to improve the efficiency of sequence similarity searching and to demonstrate various large-scale genomic analyses of homology-related data. This unit describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. These include basic use of the database to generate a novel sequence library subset, how to extend and use seqdb_demo for the storage of sequence similarity search results and making use of various kinds of stored search results to address aspects of comparative genomic analysis.

  7. Contributions to In Silico Genome Annotation

    KAUST Repository

    Kalkatawi, Manal M.

    2017-11-30

    Genome annotation is an important topic since it provides information for the foundation of downstream genomic and biological research. It is considered as a way of summarizing part of existing knowledge about the genomic characteristics of an organism. Annotating different regions of a genome sequence is known as structural annotation, while identifying functions of these regions is considered as a functional annotation. In silico approaches can facilitate both tasks that otherwise would be difficult and timeconsuming. This study contributes to genome annotation by introducing several novel bioinformatics methods, some based on machine learning (ML) approaches. First, we present Dragon PolyA Spotter (DPS), a method for accurate identification of the polyadenylation signals (PAS) within human genomic DNA sequences. For this, we derived a novel feature-set able to characterize properties of the genomic region surrounding the PAS, enabling development of high accuracy optimized ML predictive models. DPS considerably outperformed the state-of-the-art results. The second contribution concerns developing generic models for structural annotation, i.e., the recognition of different genomic signals and regions (GSR) within eukaryotic DNA. We developed DeepGSR, a systematic framework that facilitates generating ML models to predict GSR with high accuracy. To the best of our knowledge, no available generic and automated method exists for such task that could facilitate the studies of newly sequenced organisms. The prediction module of DeepGSR uses deep learning algorithms to derive highly abstract features that depend mainly on proper data representation and hyperparameters calibration. DeepGSR, which was evaluated on recognition of PAS and translation initiation sites (TIS) in different organisms, yields a simpler and more precise representation of the problem under study, compared to some other hand-tailored models, while producing high accuracy prediction results. Finally

  8. Active learning reduces annotation time for clinical concept extraction.

    Science.gov (United States)

    Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony

    2017-10-01

    To investigate: (1) the annotation time savings by various active learning query strategies compared to supervised learning and a random sampling baseline, and (2) the benefits of active learning-assisted pre-annotations in accelerating the manual annotation process compared to de novo annotation. There are 73 and 120 discharge summary reports provided by Beth Israel institute in the train and test sets of the concept extraction task in the i2b2/VA 2010 challenge, respectively. The 73 reports were used in user study experiments for manual annotation. First, all sequences within the 73 reports were manually annotated from scratch. Next, active learning models were built to generate pre-annotations for the sequences selected by a query strategy. The annotation/reviewing time per sequence was recorded. The 120 test reports were used to measure the effectiveness of the active learning models. When annotating from scratch, active learning reduced the annotation time up to 35% and 28% compared to a fully supervised approach and a random sampling baseline, respectively. Reviewing active learning-assisted pre-annotations resulted in 20% further reduction of the annotation time when compared to de novo annotation. The number of concepts that require manual annotation is a good indicator of the annotation time for various active learning approaches as demonstrated by high correlation between time rate and concept annotation rate. Active learning has a key role in reducing the time required to manually annotate domain concepts from clinical free text, either when annotating from scratch or reviewing active learning-assisted pre-annotations. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Semi-supervised learning based probabilistic latent semantic analysis for automatic image annotation

    Institute of Scientific and Technical Information of China (English)

    Tian Dongping

    2017-01-01

    In recent years, multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas, especially for automatic image annotation, whose purpose is to provide an efficient and effective searching environment for users to query their images more easily.In this paper, a semi-supervised learning based probabilistic latent semantic analysis ( PL-SA) model for automatic image annotation is presenred.Since it' s often hard to obtain or create la-beled images in large quantities while unlabeled ones are easier to collect, a transductive support vector machine ( TSVM) is exploited to enhance the quality of the training image data.Then, differ-ent image features with different magnitudes will result in different performance for automatic image annotation.To this end, a Gaussian normalization method is utilized to normalize different features extracted from effective image regions segmented by the normalized cuts algorithm so as to reserve the intrinsic content of images as complete as possible.Finally, a PLSA model with asymmetric mo-dalities is constructed based on the expectation maximization( EM) algorithm to predict a candidate set of annotations with confidence scores.Extensive experiments on the general-purpose Corel5k dataset demonstrate that the proposed model can significantly improve performance of traditional PL-SA for the task of automatic image annotation.

  10. MAGIC Database and Interfaces: An Integrated Package for Gene Discovery and Expression

    Directory of Open Access Journals (Sweden)

    Lee H. Pratt

    2006-03-01

    Full Text Available The rapidly increasing rate at which biological data is being produced requires a corresponding growth in relational databases and associated tools that can help laboratories contend with that data. With this need in mind, we describe here a Modular Approach to a Genomic, Integrated and Comprehensive (MAGIC Database. This Oracle 9i database derives from an initial focus in our laboratory on gene discovery via production and analysis of expressed sequence tags (ESTs, and subsequently on gene expression as assessed by both EST clustering and microarrays. The MAGIC Gene Discovery portion of the database focuses on information derived from DNA sequences and on its biological relevance. In addition to MAGIC SEQ-LIMS, which is designed to support activities in the laboratory, it contains several additional subschemas. The latter include MAGIC Admin for database administration, MAGIC Sequence for sequence processing as well as sequence and clone attributes, MAGIC Cluster for the results of EST clustering, MAGIC Polymorphism in support of microsatellite and single-nucleotide-polymorphism discovery, and MAGIC Annotation for electronic annotation by BLAST and BLAT. The MAGIC Microarray portion is a MIAME-compliant database with two components at present. These are MAGIC Array-LIMS, which makes possible remote entry of all information into the database, and MAGIC Array Analysis, which provides data mining and visualization. Because all aspects of interaction with the MAGIC Database are via a web browser, it is ideally suited not only for individual research laboratories but also for core facilities that serve clients at any distance.

  11. Assessment of disease named entity recognition on a corpus of annotated sentences.

    Science.gov (United States)

    Jimeno, Antonio; Jimenez-Ruiz, Ernesto; Lee, Vivian; Gaudan, Sylvain; Berlanga, Rafael; Rebholz-Schuhmann, Dietrich

    2008-04-11

    In recent years, the recognition of semantic types from the biomedical scientific literature has been focused on named entities like protein and gene names (PGNs) and gene ontology terms (GO terms). Other semantic types like diseases have not received the same level of attention. Different solutions have been proposed to identify disease named entities in the scientific literature. While matching the terminology with language patterns suffers from low recall (e.g., Whatizit) other solutions make use of morpho-syntactic features to better cover the full scope of terminological variability (e.g., MetaMap). Currently, MetaMap that is provided from the National Library of Medicine (NLM) is the state of the art solution for the annotation of concepts from UMLS (Unified Medical Language System) in the literature. Nonetheless, its performance has not yet been assessed on an annotated corpus. In addition, little effort has been invested so far to generate an annotated dataset that links disease entities in text to disease entries in a database, thesaurus or ontology and that could serve as a gold standard to benchmark text mining solutions. As part of our research work, we have taken a corpus that has been delivered in the past for the identification of associations of genes to diseases based on the UMLS Metathesaurus and we have reprocessed and re-annotated the corpus. We have gathered annotations for disease entities from two curators, analyzed their disagreement (0.51 in the kappa-statistic) and composed a single annotated corpus for public use. Thereafter, three solutions for disease named entity recognition including MetaMap have been applied to the corpus to automatically annotate it with UMLS Metathesaurus concepts. The resulting annotations have been benchmarked to compare their performance. The annotated corpus is publicly available at ftp://ftp.ebi.ac.uk/pub/software/textmining/corpora/diseases and can serve as a benchmark to other systems. In addition, we found

  12. The UniProtKB/Swiss-Prot knowledgebase and its Plant Proteome Annotation Program.

    Science.gov (United States)

    Schneider, Michel; Lane, Lydie; Boutet, Emmanuel; Lieberherr, Damien; Tognolli, Michael; Bougueleret, Lydie; Bairoch, Amos

    2009-04-13

    The UniProt knowledgebase, UniProtKB, is the main product of the UniProt consortium. It consists of two sections, UniProtKB/Swiss-Prot, the manually curated section, and UniProtKB/TrEMBL, the computer translation of the EMBL/GenBank/DDBJ nucleotide sequence database. Taken together, these two sections cover all the proteins characterized or inferred from all publicly available nucleotide sequences. The Plant Proteome Annotation Program (PPAP) of UniProtKB/Swiss-Prot focuses on the manual annotation of plant-specific proteins and protein families. Our major effort is currently directed towards the two model plants Arabidopsis thaliana and Oryza sativa. In UniProtKB/Swiss-Prot, redundancy is minimized by merging all data from different sources in a single entry. The proposed protein sequence is frequently modified after comparison with ESTs, full length transcripts or homologous proteins from other species. The information present in manually curated entries allows the reconstruction of all described isoforms. The annotation also includes proteomics data such as PTM and protein identification MS experimental results. UniProtKB and the other products of the UniProt consortium are accessible online at www.uniprot.org.

  13. Microtask crowdsourcing for disease mention annotation in PubMed abstracts.

    Science.gov (United States)

    Good, Benjamin M; Nanis, Max; Wu, Chunlei; Su, Andrew I

    2015-01-01

    Identifying concepts and relationships in biomedical text enables knowledge to be applied in computational analyses. Many biological natural language processing (BioNLP) projects attempt to address this challenge, but the state of the art still leaves much room for improvement. Progress in BioNLP research depends on large, annotated corpora for evaluating information extraction systems and training machine learning models. Traditionally, such corpora are created by small numbers of expert annotators often working over extended periods of time. Recent studies have shown that workers on microtask crowdsourcing platforms such as Amazon's Mechanical Turk (AMT) can, in aggregate, generate high-quality annotations of biomedical text. Here, we investigated the use of the AMT in capturing disease mentions in PubMed abstracts. We used the NCBI Disease corpus as a gold standard for refining and benchmarking our crowdsourcing protocol. After several iterations, we arrived at a protocol that reproduced the annotations of the 593 documents in the 'training set' of this gold standard with an overall F measure of 0.872 (precision 0.862, recall 0.883). The output can also be tuned to optimize for precision (max = 0.984 when recall = 0.269) or recall (max = 0.980 when precision = 0.436). Each document was completed by 15 workers, and their annotations were merged based on a simple voting method. In total 145 workers combined to complete all 593 documents in the span of 9 days at a cost of $.066 per abstract per worker. The quality of the annotations, as judged with the F measure, increases with the number of workers assigned to each task; however minimal performance gains were observed beyond 8 workers per task. These results add further evidence that microtask crowdsourcing can be a valuable tool for generating well-annotated corpora in BioNLP. Data produced for this analysis are available at http://figshare.com/articles/Disease_Mention_Annotation_with_Mechanical_Turk/1126402.

  14. SIRSALE: integrated video database management tools

    Science.gov (United States)

    Brunie, Lionel; Favory, Loic; Gelas, J. P.; Lefevre, Laurent; Mostefaoui, Ahmed; Nait-Abdesselam, F.

    2002-07-01

    Video databases became an active field of research during the last decade. The main objective in such systems is to provide users with capabilities to friendly search, access and playback distributed stored video data in the same way as they do for traditional distributed databases. Hence, such systems need to deal with hard issues : (a) video documents generate huge volumes of data and are time sensitive (streams must be delivered at a specific bitrate), (b) contents of video data are very hard to be automatically extracted and need to be humanly annotated. To cope with these issues, many approaches have been proposed in the literature including data models, query languages, video indexing etc. In this paper, we present SIRSALE : a set of video databases management tools that allow users to manipulate video documents and streams stored in large distributed repositories. All the proposed tools are based on generic models that can be customized for specific applications using ad-hoc adaptation modules. More precisely, SIRSALE allows users to : (a) browse video documents by structures (sequences, scenes, shots) and (b) query the video database content by using a graphical tool, adapted to the nature of the target video documents. This paper also presents an annotating interface which allows archivists to describe the content of video documents. All these tools are coupled to a video player integrating remote VCR functionalities and are based on active network technology. So, we present how dedicated active services allow an optimized video transport for video streams (with Tamanoir active nodes). We then describe experiments of using SIRSALE on an archive of news video and soccer matches. The system has been demonstrated to professionals with a positive feedback. Finally, we discuss open issues and present some perspectives.

  15. Formalization of taxon-based constraints to detect inconsistencies in annotation and ontology development

    Directory of Open Access Journals (Sweden)

    Mungall Christopher J

    2010-10-01

    Full Text Available Abstract Background The Gene Ontology project supports categorization of gene products according to their location of action, the molecular functions that they carry out, and the processes that they are involved in. Although the ontologies are intentionally developed to be taxon neutral, and to cover all species, there are inherent taxon specificities in some branches. For example, the process 'lactation' is specific to mammals and the location 'mitochondrion' is specific to eukaryotes. The lack of an explicit formalization of these constraints can lead to errors and inconsistencies in automated and manual annotation. Results We have formalized the taxonomic constraints implicit in some GO classes, and specified these at various levels in the ontology. We have also developed an inference system that can be used to check for violations of these constraints in annotations. Using the constraints in conjunction with the inference system, we have detected and removed errors in annotations and improved the structure of the ontology. Conclusions Detection of inconsistencies in taxon-specificity enables gradual improvement of the ontologies, the annotations, and the formalized constraints. This is progressively improving the quality of our data. The full system is available for download, and new constraints or proposed changes to constraints can be submitted online at https://sourceforge.net/tracker/?atid=605890&group_id=36855.

  16. De novo assembly, characterization and functional annotation of pineapple fruit transcriptome through massively parallel sequencing.

    Science.gov (United States)

    Ong, Wen Dee; Voo, Lok-Yung Christopher; Kumar, Vijay Subbiah

    2012-01-01

    Pineapple (Ananas comosus var. comosus), is an important tropical non-climacteric fruit with high commercial potential. Understanding the mechanism and processes underlying fruit ripening would enable scientists to enhance the improvement of quality traits such as, flavor, texture, appearance and fruit sweetness. Although, the pineapple is an important fruit, there is insufficient transcriptomic or genomic information that is available in public databases. Application of high throughput transcriptome sequencing to profile the pineapple fruit transcripts is therefore needed. To facilitate this, we have performed transcriptome sequencing of ripe yellow pineapple fruit flesh using Illumina technology. About 4.7 millions Illumina paired-end reads were generated and assembled using the Velvet de novo assembler. The assembly produced 28,728 unique transcripts with a mean length of approximately 200 bp. Sequence similarity search against non-redundant NCBI database identified a total of 16,932 unique transcripts (58.93%) with significant hits. Out of these, 15,507 unique transcripts were assigned to gene ontology terms. Functional annotation against Kyoto Encyclopedia of Genes and Genomes pathway database identified 13,598 unique transcripts (47.33%) which were mapped to 126 pathways. The assembly revealed many transcripts that were previously unknown. The unique transcripts derived from this work have rapidly increased of the number of the pineapple fruit mRNA transcripts as it is now available in public databases. This information can be further utilized in gene expression, genomics and other functional genomics studies in pineapple.

  17. RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes

    Energy Technology Data Exchange (ETDEWEB)

    Brettin, Thomas; Davis, James J.; Disz, Terry; Edwards, Robert A.; Gerdes, Svetlana; Olsen, Gary J.; Olson, Robert; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Shukla, Maulik; Thomason, James A.; Stevens, Rick; Vonstein, Veronika; Wattam, Alice R.; Xia, Fangfang

    2015-02-10

    The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.

  18. RASTtk: a modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes.

    Science.gov (United States)

    Brettin, Thomas; Davis, James J; Disz, Terry; Edwards, Robert A; Gerdes, Svetlana; Olsen, Gary J; Olson, Robert; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D; Shukla, Maulik; Thomason, James A; Stevens, Rick; Vonstein, Veronika; Wattam, Alice R; Xia, Fangfang

    2015-02-10

    The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.

  19. tRNA sequence data, annotation data and curation data - tRNADB-CE | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data List Contact us tRNAD... tRNA sequence data, annotation data and curation data - tRNADB-CE | LSDB Archive ...

  20. Application of material databases for improved reliability of reactor pressure vessels

    International Nuclear Information System (INIS)

    Griesbach, T.J.; Server, W.L.; Beaudoin, B.F.; Burgos, B.N.

    1994-01-01

    A vital part of reactor vessel Life Cycle Management program must begin with an accurate characterization of the vessel material properties. Uncertainties in vessel material properties or use of bounding values may result in unnecessary conservatisms in vessel integrity calculations. These conservatisms may be eliminated through a better understanding of the material properties in reactor vessels, both in the unirradiated and irradiated conditions. Reactor vessel material databases are available for quantifying the chemistry and Charpy shift behavior of individual heats of reactor vessel materials. Application of the databases for vessels with embrittlement concerns has proven to be an effective embrittlement management tool. This paper presents details of database development and applications which demonstrate the value of using material databases for improving material chemistry and for maximizing the data from integrated material surveillance programs

  1. A Public Image Database for Benchmark of Plant Seedling Classification Algorithms

    DEFF Research Database (Denmark)

    Giselsson, Thomas Mosgaard; Nyholm Jørgensen, Rasmus; Jensen, Peter Kryger

    A database of images of approximately 960 unique plants belonging to 12 species at several growth stages is made publicly available. It comprises annotated RGB images with a physical resolution of roughly 10 pixels per mm. To standardise the evaluation of classification results obtained...

  2. wANNOVAR: annotating genetic variants for personal genomes via the web.

    Science.gov (United States)

    Chang, Xiao; Wang, Kai

    2012-07-01

    High-throughput DNA sequencing platforms have become widely available. As a result, personal genomes are increasingly being sequenced in research and clinical settings. However, the resulting massive amounts of variants data pose significant challenges to the average biologists and clinicians without bioinformatics skills. We developed a web server called wANNOVAR to address the critical needs for functional annotation of genetic variants from personal genomes. The server provides simple and intuitive interface to help users determine the functional significance of variants. These include annotating single nucleotide variants and insertions/deletions for their effects on genes, reporting their conservation levels (such as PhyloP and GERP++ scores), calculating their predicted functional importance scores (such as SIFT and PolyPhen scores), retrieving allele frequencies in public databases (such as the 1000 Genomes Project and NHLBI-ESP 5400 exomes), and implementing a 'variants reduction' protocol to identify a subset of potentially deleterious variants/genes. We illustrated how wANNOVAR can help draw biological insights from sequencing data, by analysing genetic variants generated on two Mendelian diseases. We conclude that wANNOVAR will help biologists and clinicians take advantage of the personal genome information to expedite scientific discoveries. The wANNOVAR server is available at http://wannovar.usc.edu, and will be continuously updated to reflect the latest annotation information.

  3. Image annotation under X Windows

    Science.gov (United States)

    Pothier, Steven

    1991-08-01

    A mechanism for attaching graphic and overlay annotation to multiple bits/pixel imagery while providing levels of performance approaching that of native mode graphics systems is presented. This mechanism isolates programming complexity from the application programmer through software encapsulation under the X Window System. It ensures display accuracy throughout operations on the imagery and annotation including zooms, pans, and modifications of the annotation. Trade-offs that affect speed of display, consumption of memory, and system functionality are explored. The use of resource files to tune the display system is discussed. The mechanism makes use of an abstraction consisting of four parts; a graphics overlay, a dithered overlay, an image overly, and a physical display window. Data structures are maintained that retain the distinction between the four parts so that they can be modified independently, providing system flexibility. A unique technique for associating user color preferences with annotation is introduced. An interface that allows interactive modification of the mapping between image value and color is discussed. A procedure that provides for the colorization of imagery on 8-bit display systems using pixel dithering is explained. Finally, the application of annotation mechanisms to various applications is discussed.

  4. OLS Client and OLS Dialog: Open Source Tools to Annotate Public Omics Datasets.

    Science.gov (United States)

    Perez-Riverol, Yasset; Ternent, Tobias; Koch, Maximilian; Barsnes, Harald; Vrousgou, Olga; Jupp, Simon; Vizcaíno, Juan Antonio

    2017-10-01

    The availability of user-friendly software to annotate biological datasets and experimental details is becoming essential in data management practices, both in local storage systems and in public databases. The Ontology Lookup Service (OLS, http://www.ebi.ac.uk/ols) is a popular centralized service to query, browse and navigate biomedical ontologies and controlled vocabularies. Recently, the OLS framework has been completely redeveloped (version 3.0), including enhancements in the data model, like the added support for Web Ontology Language based ontologies, among many other improvements. However, the new OLS is not backwards compatible and new software tools are needed to enable access to this widely used framework now that the previous version is no longer available. We here present the OLS Client as a free, open-source Java library to retrieve information from the new version of the OLS. It enables rapid tool creation by providing a robust, pluggable programming interface and common data model to programmatically access the OLS. The library has already been integrated and is routinely used by several bioinformatics resources and related data annotation tools. Secondly, we also introduce an updated version of the OLS Dialog (version 2.0), a Java graphical user interface that can be easily plugged into Java desktop applications to access the OLS. The software and related documentation are freely available at https://github.com/PRIDE-Utilities/ols-client and https://github.com/PRIDE-Toolsuite/ols-dialog. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Motion lecture annotation system to learn Naginata performances

    Science.gov (United States)

    Kobayashi, Daisuke; Sakamoto, Ryota; Nomura, Yoshihiko

    2013-12-01

    This paper describes a learning assistant system using motion capture data and annotation to teach "Naginata-jutsu" (a skill to practice Japanese halberd) performance. There are some video annotation tools such as YouTube. However these video based tools have only single angle of view. Our approach that uses motion-captured data allows us to view any angle. A lecturer can write annotations related to parts of body. We have made a comparison of effectiveness between the annotation tool of YouTube and the proposed system. The experimental result showed that our system triggered more annotations than the annotation tool of YouTube.

  6. Pathway analysis for intracellular Porphyromonas gingivalis using a strain ATCC 33277 specific database

    Directory of Open Access Journals (Sweden)

    Wang Tiansong

    2009-09-01

    Full Text Available Abstract Background Porphyromonas gingivalis is a Gram-negative intracellular pathogen associated with periodontal disease. We have previously reported on whole-cell quantitative proteomic analyses to investigate the differential expression of virulence factors as the organism transitions from an extracellular to intracellular lifestyle. The original results with the invasive strain P. gingivalis ATCC 33277 were obtained using the genome sequence available at the time, strain W83 [GenBank: AE015924]. We present here a re-processed dataset using the recently published genome annotation specific for strain ATCC 33277 [GenBank: AP009380] and an analysis of differential abundance based on metabolic pathways rather than individual proteins. Results Qualitative detection was observed for 1266 proteins using the strain ATCC 33277 annotation for 18 hour internalized P. gingivalis within human gingival epithelial cells and controls exposed to gingival cell culture medium, an improvement of 7% over the W83 annotation. Internalized cells showed increased abundance of proteins in the energy pathway from asparagine/aspartate amino acids to ATP. The pathway producing one short chain fatty acid, propionate, showed increased abundance, while that of another, butyrate, trended towards decreased abundance. The translational machinery, including ribosomal proteins and tRNA synthetases, showed a significant increase in protein relative abundance, as did proteins responsible for transcription. Conclusion Use of the ATCC 33277 specific genome annotation resulted in improved proteome coverage with respect to the number of proteins observed both qualitatively in terms of protein identifications and quantitatively in terms of the number of calculated abundance ratios. Pathway analysis showed a significant increase in overall protein synthetic and transcriptional machinery in the absence of significant growth. These results suggest that the interior of host cells

  7. An Improved Algorithm for Generating Database Transactions from Relational Algebra Specifications

    Directory of Open Access Journals (Sweden)

    Daniel J. Dougherty

    2010-03-01

    Full Text Available Alloy is a lightweight modeling formalism based on relational algebra. In prior work with Fisler, Giannakopoulos, Krishnamurthi, and Yoo, we have presented a tool, Alchemy, that compiles Alloy specifications into implementations that execute against persistent databases. The foundation of Alchemy is an algorithm for rewriting relational algebra formulas into code for database transactions. In this paper we report on recent progress in improving the robustness and efficiency of this transformation.

  8. BEACON: automated tool for Bacterial GEnome Annotation ComparisON

    KAUST Repository

    Kalkatawi, Manal M.

    2015-08-18

    Background Genome annotation is one way of summarizing the existing knowledge about genomic characteristics of an organism. There has been an increased interest during the last several decades in computer-based structural and functional genome annotation. Many methods for this purpose have been developed for eukaryotes and prokaryotes. Our study focuses on comparison of functional annotations of prokaryotic genomes. To the best of our knowledge there is no fully automated system for detailed comparison of functional genome annotations generated by different annotation methods (AMs). Results The presence of many AMs and development of new ones introduce needs to: a/ compare different annotations for a single genome, and b/ generate annotation by combining individual ones. To address these issues we developed an Automated Tool for Bacterial GEnome Annotation ComparisON (BEACON) that benefits both AM developers and annotation analysers. BEACON provides detailed comparison of gene function annotations of prokaryotic genomes obtained by different AMs and generates extended annotations through combination of individual ones. For the illustration of BEACON’s utility, we provide a comparison analysis of multiple different annotations generated for four genomes and show on these examples that the extended annotation can increase the number of genes annotated by putative functions up to 27 %, while the number of genes without any function assignment is reduced. Conclusions We developed BEACON, a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at: http://www.cbrc.kaust.edu.sa/BEACON/

  9. BEACON: automated tool for Bacterial GEnome Annotation ComparisON.

    Science.gov (United States)

    Kalkatawi, Manal; Alam, Intikhab; Bajic, Vladimir B

    2015-08-18

    Genome annotation is one way of summarizing the existing knowledge about genomic characteristics of an organism. There has been an increased interest during the last several decades in computer-based structural and functional genome annotation. Many methods for this purpose have been developed for eukaryotes and prokaryotes. Our study focuses on comparison of functional annotations of prokaryotic genomes. To the best of our knowledge there is no fully automated system for detailed comparison of functional genome annotations generated by different annotation methods (AMs). The presence of many AMs and development of new ones introduce needs to: a/ compare different annotations for a single genome, and b/ generate annotation by combining individual ones. To address these issues we developed an Automated Tool for Bacterial GEnome Annotation ComparisON (BEACON) that benefits both AM developers and annotation analysers. BEACON provides detailed comparison of gene function annotations of prokaryotic genomes obtained by different AMs and generates extended annotations through combination of individual ones. For the illustration of BEACON's utility, we provide a comparison analysis of multiple different annotations generated for four genomes and show on these examples that the extended annotation can increase the number of genes annotated by putative functions up to 27%, while the number of genes without any function assignment is reduced. We developed BEACON, a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at: http://www.cbrc.kaust.edu.sa/BEACON/ .

  10. JGI Plant Genomics Gene Annotation Pipeline

    Energy Technology Data Exchange (ETDEWEB)

    Shu, Shengqiang; Rokhsar, Dan; Goodstein, David; Hayes, David; Mitros, Therese

    2014-07-14

    Plant genomes vary in size and are highly complex with a high amount of repeats, genome duplication and tandem duplication. Gene encodes a wealth of information useful in studying organism and it is critical to have high quality and stable gene annotation. Thanks to advancement of sequencing technology, many plant species genomes have been sequenced and transcriptomes are also sequenced. To use these vastly large amounts of sequence data to make gene annotation or re-annotation in a timely fashion, an automatic pipeline is needed. JGI plant genomics gene annotation pipeline, called integrated gene call (IGC), is our effort toward this aim with aid of a RNA-seq transcriptome assembly pipeline. It utilizes several gene predictors based on homolog peptides and transcript ORFs. See Methods for detail. Here we present genome annotation of JGI flagship green plants produced by this pipeline plus Arabidopsis and rice except for chlamy which is done by a third party. The genome annotations of these species and others are used in our gene family build pipeline and accessible via JGI Phytozome portal whose URL and front page snapshot are shown below.

  11. Annotating temporal information in clinical narratives.

    Science.gov (United States)

    Sun, Weiyi; Rumshisky, Anna; Uzuner, Ozlem

    2013-12-01

    Temporal information in clinical narratives plays an important role in patients' diagnosis, treatment and prognosis. In order to represent narrative information accurately, medical natural language processing (MLP) systems need to correctly identify and interpret temporal information. To promote research in this area, the Informatics for Integrating Biology and the Bedside (i2b2) project developed a temporally annotated corpus of clinical narratives. This corpus contains 310 de-identified discharge summaries, with annotations of clinical events, temporal expressions and temporal relations. This paper describes the process followed for the development of this corpus and discusses annotation guideline development, annotation methodology, and corpus quality. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. The Saccharomyces Genome Database Variant Viewer.

    Science.gov (United States)

    Sheppard, Travis K; Hitz, Benjamin C; Engel, Stacia R; Song, Giltae; Balakrishnan, Rama; Binkley, Gail; Costanzo, Maria C; Dalusag, Kyla S; Demeter, Janos; Hellerstedt, Sage T; Karra, Kalpana; Nash, Robert S; Paskov, Kelley M; Skrzypek, Marek S; Weng, Shuai; Wong, Edith D; Cherry, J Michael

    2016-01-04

    The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. Finding the Subcellular Location of Barley, Wheat, Rice and Maize Proteins: The Compendium of Crop Proteins with Annotated Locations (cropPAL).

    Science.gov (United States)

    Hooper, Cornelia M; Castleden, Ian R; Aryamanesh, Nader; Jacoby, Richard P; Millar, A Harvey

    2016-01-01

    Barley, wheat, rice and maize provide the bulk of human nutrition and have extensive industrial use as agricultural products. The genomes of these crops each contains >40,000 genes encoding proteins; however, the major genome databases for these species lack annotation information of protein subcellular location for >80% of these gene products. We address this gap, by constructing the compendium of crop protein subcellular locations called crop Proteins with Annotated Locations (cropPAL). Subcellular location is most commonly determined by fluorescent protein tagging of live cells or mass spectrometry detection in subcellular purifications, but can also be predicted from amino acid sequence or protein expression patterns. The cropPAL database collates 556 published studies, from >300 research institutes in >30 countries that have been previously published, as well as compiling eight pre-computed subcellular predictions for all Hordeum vulgare, Triticum aestivum, Oryza sativa and Zea mays protein sequences. The data collection including metadata for proteins and published studies can be accessed through a search portal http://crop-PAL.org. The subcellular localization information housed in cropPAL helps to depict plant cells as compartmentalized protein networks that can be investigated for improving crop yield and quality, and developing new biotechnological solutions to agricultural challenges. © The Author 2015. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  14. Database resources for the tuberculosis community.

    Science.gov (United States)

    Lew, Jocelyne M; Mao, Chunhong; Shukla, Maulik; Warren, Andrew; Will, Rebecca; Kuznetsov, Dmitry; Xenarios, Ioannis; Robertson, Brian D; Gordon, Stephen V; Schnappinger, Dirk; Cole, Stewart T; Sobral, Bruno

    2013-01-01

    Access to online repositories for genomic and associated "-omics" datasets is now an essential part of everyday research activity. It is important therefore that the Tuberculosis community is aware of the databases and tools available to them online, as well as for the database hosts to know what the needs of the research community are. One of the goals of the Tuberculosis Annotation Jamboree, held in Washington DC on March 7th-8th 2012, was therefore to provide an overview of the current status of three key Tuberculosis resources, TubercuList (tuberculist.epfl.ch), TB Database (www.tbdb.org), and Pathosystems Resource Integration Center (PATRIC, www.patricbrc.org). Here we summarize some key updates and upcoming features in TubercuList, and provide an overview of the PATRIC site and its online tools for pathogen RNA-Seq analysis. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. DomSign: a top-down annotation pipeline to enlarge enzyme space in the protein universe.

    Science.gov (United States)

    Wang, Tianmin; Mori, Hiroshi; Zhang, Chong; Kurokawa, Ken; Xing, Xin-Hui; Yamada, Takuji

    2015-03-21

    Computational predictions of catalytic function are vital for in-depth understanding of enzymes. Because several novel approaches performing better than the common BLAST tool are rarely applied in research, we hypothesized that there is a large gap between the number of known annotated enzymes and the actual number in the protein universe, which significantly limits our ability to extract additional biologically relevant functional information from the available sequencing data. To reliably expand the enzyme space, we developed DomSign, a highly accurate domain signature-based enzyme functional prediction tool to assign Enzyme Commission (EC) digits. DomSign is a top-down prediction engine that yields results comparable, or superior, to those from many benchmark EC number prediction tools, including BLASTP, when a homolog with an identity >30% is not available in the database. Performance tests showed that DomSign is a highly reliable enzyme EC number annotation tool. After multiple tests, the accuracy is thought to be greater than 90%. Thus, DomSign can be applied to large-scale datasets, with the goal of expanding the enzyme space with high fidelity. Using DomSign, we successfully increased the percentage of EC-tagged enzymes from 12% to 30% in UniProt-TrEMBL. In the Kyoto Encyclopedia of Genes and Genomes bacterial database, the percentage of EC-tagged enzymes for each bacterial genome could be increased from 26.0% to 33.2% on average. Metagenomic mining was also efficient, as exemplified by the application of DomSign to the Human Microbiome Project dataset, recovering nearly one million new EC-labeled enzymes. Our results offer preliminarily confirmation of the existence of the hypothesized huge number of "hidden enzymes" in the protein universe, the identification of which could substantially further our understanding of the metabolisms of diverse organisms and also facilitate bioengineering by providing a richer enzyme resource. Furthermore, our results

  16. Automatic annotation of head velocity and acceleration in Anvil

    DEFF Research Database (Denmark)

    Jongejan, Bart

    2012-01-01

    We describe an automatic face tracker plugin for the ANVIL annotation tool. The face tracker produces data for velocity and for acceleration in two dimensions. We compare the annotations generated by the face tracking algorithm with independently made manual annotations for head movements....... The annotations are a useful supplement to manual annotations and may help human annotators to quickly and reliably determine onset of head movements and to suggest which kind of head movement is taking place....

  17. Mesotext. Framing and exploring annotations

    NARCIS (Netherlands)

    Boot, P.; Boot, P.; Stronks, E.

    2007-01-01

    From the introduction: Annotation is an important item on the wish list for digital scholarly tools. It is one of John Unsworth’s primitives of scholarship (Unsworth 2000). Especially in linguistics,a number of tools have been developed that facilitate the creation of annotations to source material

  18. Annotating images by mining image search results

    NARCIS (Netherlands)

    Wang, X.J.; Zhang, L.; Li, X.; Ma, W.Y.

    2008-01-01

    Although it has been studied for years by the computer vision and machine learning communities, image annotation is still far from practical. In this paper, we propose a novel attempt at model-free image annotation, which is a data-driven approach that annotates images by mining their search

  19. Phylogeny, Functional Annotation, and Protein Interaction Network Analyses of the Xenopus tropicalis Basic Helix-Loop-Helix Transcription Factors

    Directory of Open Access Journals (Sweden)

    Wuyi Liu

    2013-01-01

    Full Text Available The previous survey identified 70 basic helix-loop-helix (bHLH proteins, but it was proved to be incomplete, and the functional information and regulatory networks of frog bHLH transcription factors were not fully known. Therefore, we conducted an updated genome-wide survey in the Xenopus tropicalis genome project databases and identified 105 bHLH sequences. Among the retrieved 105 sequences, phylogenetic analyses revealed that 103 bHLH proteins belonged to 43 families or subfamilies with 46, 26, 11, 3, 15, and 4 members in the corresponding supergroups. Next, gene ontology (GO enrichment analyses showed 65 significant GO annotations of biological processes and molecular functions and KEGG pathways counted in frequency. To explore the functional pathways, regulatory gene networks, and/or related gene groups coding for Xenopus tropicalis bHLH proteins, the identified bHLH genes were put into the databases KOBAS and STRING to get the signaling information of pathways and protein interaction networks according to available public databases and known protein interactions. From the genome annotation and pathway analysis using KOBAS, we identified 16 pathways in the Xenopus tropicalis genome. From the STRING interaction analysis, 68 hub proteins were identified, and many hub proteins created a tight network or a functional module within the protein families.

  20. Feedback Driven Annotation and Refactoring of Parallel Programs

    DEFF Research Database (Denmark)

    Larsen, Per

    and communication in embedded programs. Runtime checks are developed to ensure that annotations correctly describe observable program behavior. The performance impact of runtime checking is evaluated on several benchmark kernels and is negligible in all cases. The second aspect is compilation feedback. Annotations...... are not effective unless programmers are told how and when they are benecial. A prototype compilation feedback system was developed in collaboration with IBM Haifa Research Labs. It reports issues that prevent further analysis to the programmer. Performance evaluation shows that three programs performes signicantly......This thesis combines programmer knowledge and feedback to improve modeling and optimization of software. The research is motivated by two observations. First, there is a great need for automatic analysis of software for embedded systems - to expose and model parallelism inherent in programs. Second...

  1. EST Express: PHP/MySQL based automated annotation of ESTs from expression libraries.

    Science.gov (United States)

    Smith, Robin P; Buchser, William J; Lemmon, Marcus B; Pardinas, Jose R; Bixby, John L; Lemmon, Vance P

    2008-04-10

    Several biological techniques result in the acquisition of functional sets of cDNAs that must be sequenced and analyzed. The emergence of redundant databases such as UniGene and centralized annotation engines such as Entrez Gene has allowed the development of software that can analyze a great number of sequences in a matter of seconds. We have developed "EST Express", a suite of analytical tools that identify and annotate ESTs originating from specific mRNA populations. The software consists of a user-friendly GUI powered by PHP and MySQL that allows for online collaboration between researchers and continuity with UniGene, Entrez Gene and RefSeq. Two key features of the software include a novel, simplified Entrez Gene parser and tools to manage cDNA library sequencing projects. We have tested the software on a large data set (2,016 samples) produced by subtractive hybridization. EST Express is an open-source, cross-platform web server application that imports sequences from cDNA libraries, such as those generated through subtractive hybridization or yeast two-hybrid screens. It then provides several layers of annotation based on Entrez Gene and RefSeq to allow the user to highlight useful genes and manage cDNA library projects.

  2. EST Express: PHP/MySQL based automated annotation of ESTs from expression libraries

    Directory of Open Access Journals (Sweden)

    Pardinas Jose R

    2008-04-01

    Full Text Available Abstract Background Several biological techniques result in the acquisition of functional sets of cDNAs that must be sequenced and analyzed. The emergence of redundant databases such as UniGene and centralized annotation engines such as Entrez Gene has allowed the development of software that can analyze a great number of sequences in a matter of seconds. Results We have developed "EST Express", a suite of analytical tools that identify and annotate ESTs originating from specific mRNA populations. The software consists of a user-friendly GUI powered by PHP and MySQL that allows for online collaboration between researchers and continuity with UniGene, Entrez Gene and RefSeq. Two key features of the software include a novel, simplified Entrez Gene parser and tools to manage cDNA library sequencing projects. We have tested the software on a large data set (2,016 samples produced by subtractive hybridization. Conclusion EST Express is an open-source, cross-platform web server application that imports sequences from cDNA libraries, such as those generated through subtractive hybridization or yeast two-hybrid screens. It then provides several layers of annotation based on Entrez Gene and RefSeq to allow the user to highlight useful genes and manage cDNA library projects.

  3. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences

    OpenAIRE

    Huerta-Cepas, J.; Szklarczyk, D.; Forslund, K.; Cook, H.; Heller, D.; Walter, M.C.; Rattei, T.; Mende, D.R.; Sunagawa, S.; Kuhn, M.; Jensen, L.J.; von Mering, C.; Bork, P.

    2016-01-01

    eggNOG is a public resource that provides Orthologous Groups (OGs) of proteins at different taxonomic levels, each with integrated and summarized functional annotations. Developments since the latest public release include changes to the algorithm for creating OGs across taxonomic levels, making nested groups hierarchically consistent. This allows for a better propagation of functional terms across nested OGs and led to the novel annotation of 95 890 previously uncharacterized OGs, increasing...

  4. A phylogenomic gene cluster resource: The phylogeneticallyinferred groups (PhlGs) database

    Energy Technology Data Exchange (ETDEWEB)

    Dehal, Paramvir S.; Boore, Jeffrey L.

    2005-08-25

    We present here the PhIGs database, a phylogenomic resource for sequenced genomes. Although many methods exist for clustering gene families, very few attempt to create truly orthologous clusters sharing descent from a single ancestral gene across a range of evolutionary depths. Although these non-phylogenetic gene family clusters have been used broadly for gene annotation, errors are known to be introduced by the artifactual association of slowly evolving paralogs and lack of annotation for those more rapidly evolving. A full phylogenetic framework is necessary for accurate inference of function and for many studies that address pattern and mechanism of the evolution of the genome. The automated generation of evolutionary gene clusters, creation of gene trees, determination of orthology and paralogy relationships, and the correlation of this information with gene annotations, expression information, and genomic context is an important resource to the scientific community.

  5. Fedora Content Modelling for Improved Services for Research Databases

    DEFF Research Database (Denmark)

    Elbæk, Mikael Karstensen; Heller, Alfred; Pedersen, Gert Schmeltz

    A re-implementation of the research database of the Technical University of Denmark, DTU, is based on Fedora. The backbone consists of content models for primary and secondary entities and their relationships, giving flexible and powerful extraction capabilities for interoperability and reporting....... By adopting such an abstract data model, the platform enables new and improved services for researchers, librarians and administrators....

  6. Teaching and Learning Communities through Online Annotation

    Science.gov (United States)

    van der Pluijm, B.

    2016-12-01

    What do colleagues do with your assigned textbook? What they say or think about the material? Want students to be more engaged in their learning experience? If so, online materials that complement standard lecture format provide new opportunity through managed, online group annotation that leverages the ubiquity of internet access, while personalizing learning. The concept is illustrated with the new online textbook "Processes in Structural Geology and Tectonics", by Ben van der Pluijm and Stephen Marshak, which offers a platform for sharing of experiences, supplementary materials and approaches, including readings, mathematical applications, exercises, challenge questions, quizzes, alternative explanations, and more. The annotation framework used is Hypothes.is, which offers a free, open platform markup environment for annotation of websites and PDF postings. The annotations can be public, grouped or individualized, as desired, including export access and download of annotations. A teacher group, hosted by a moderator/owner, limits access to members of a user group of teachers, so that its members can use, copy or transcribe annotations for their own lesson material. Likewise, an instructor can host a student group that encourages sharing of observations, questions and answers among students and instructor. Also, the instructor can create one or more closed groups that offers study help and hints to students. Options galore, all of which aim to engage students and to promote greater responsibility for their learning experience. Beyond new capacity, the ability to analyze student annotation supports individual learners and their needs. For example, student notes can be analyzed for key phrases and concepts, and identify misunderstandings, omissions and problems. Also, example annotations can be shared to enhance notetaking skills and to help with studying. Lastly, online annotation allows active application to lecture posted slides, supporting real-time notetaking

  7. Displaying Annotations for Digitised Globes

    Science.gov (United States)

    Gede, Mátyás; Farbinger, Anna

    2018-05-01

    Thanks to the efforts of the various globe digitising projects, nowadays there are plenty of old globes that can be examined as 3D models on the computer screen. These globes usually contain a lot of interesting details that an average observer would not entirely discover for the first time. The authors developed a website that can display annotations for such digitised globes. These annotations help observers of the globe to discover all the important, interesting details. Annotations consist of a plain text title, a HTML formatted descriptive text and a corresponding polygon and are stored in KML format. The website is powered by the Cesium virtual globe engine.

  8. THE DIMENSIONS OF COMPOSITION ANNOTATION.

    Science.gov (United States)

    MCCOLLY, WILLIAM

    ENGLISH TEACHER ANNOTATIONS WERE STUDIED TO DETERMINE THE DIMENSIONS AND PROPERTIES OF THE ENTIRE SYSTEM FOR WRITING CORRECTIONS AND CRITICISMS ON COMPOSITIONS. FOUR SETS OF COMPOSITIONS WERE WRITTEN BY STUDENTS IN GRADES 9 THROUGH 13. TYPESCRIPTS OF THE COMPOSITIONS WERE ANNOTATED BY CLASSROOM ENGLISH TEACHERS. THEN, 32 ENGLISH TEACHERS JUDGED…

  9. Disbiome database: linking the microbiome to disease.

    Science.gov (United States)

    Janssens, Yorick; Nielandt, Joachim; Bronselaer, Antoon; Debunne, Nathan; Verbeke, Frederick; Wynendaele, Evelien; Van Immerseel, Filip; Vandewynckel, Yves-Paul; De Tré, Guy; De Spiegeleer, Bart

    2018-06-04

    Recent research has provided fascinating indications and evidence that the host health is linked to its microbial inhabitants. Due to the development of high-throughput sequencing technologies, more and more data covering microbial composition changes in different disease types are emerging. However, this information is dispersed over a wide variety of medical and biomedical disciplines. Disbiome is a database which collects and presents published microbiota-disease information in a standardized way. The diseases are classified using the MedDRA classification system and the micro-organisms are linked to their NCBI and SILVA taxonomy. Finally, each study included in the Disbiome database is assessed for its reporting quality using a standardized questionnaire. Disbiome is the first database giving a clear, concise and up-to-date overview of microbial composition differences in diseases, together with the relevant information of the studies published. The strength of this database lies within the combination of the presence of references to other databases, which enables both specific and diverse search strategies within the Disbiome database, and the human annotation which ensures a simple and structured presentation of the available data.

  10. Ginseng Genome Database: an open-access platform for genomics of Panax ginseng.

    Science.gov (United States)

    Jayakodi, Murukarthick; Choi, Beom-Soon; Lee, Sang-Choon; Kim, Nam-Hoon; Park, Jee Young; Jang, Woojong; Lakshmanan, Meiyappan; Mohan, Shobhana V G; Lee, Dong-Yup; Yang, Tae-Jin

    2018-04-12

    The ginseng (Panax ginseng C.A. Meyer) is a perennial herbaceous plant that has been used in traditional oriental medicine for thousands of years. Ginsenosides, which have significant pharmacological effects on human health, are the foremost bioactive constituents in this plant. Having realized the importance of this plant to humans, an integrated omics resource becomes indispensable to facilitate genomic research, molecular breeding and pharmacological study of this herb. The first draft genome sequences of P. ginseng cultivar "Chunpoong" were reported recently. Here, using the draft genome, transcriptome, and functional annotation datasets of P. ginseng, we have constructed the Ginseng Genome Database http://ginsengdb.snu.ac.kr /, the first open-access platform to provide comprehensive genomic resources of P. ginseng. The current version of this database provides the most up-to-date draft genome sequence (of approximately 3000 Mbp of scaffold sequences) along with the structural and functional annotations for 59,352 genes and digital expression of genes based on transcriptome data from different tissues, growth stages and treatments. In addition, tools for visualization and the genomic data from various analyses are provided. All data in the database were manually curated and integrated within a user-friendly query page. This database provides valuable resources for a range of research fields related to P. ginseng and other species belonging to the Apiales order as well as for plant research communities in general. Ginseng genome database can be accessed at http://ginsengdb.snu.ac.kr /.

  11. A computational approach for the annotation of hydrogen-bonded base interactions in crystallographic structures of the ribozymes

    Energy Technology Data Exchange (ETDEWEB)

    Hamdani, Hazrina Yusof, E-mail: hazrina@mfrlab.org [School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi (Malaysia); Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, Kepala Batas (Malaysia); Artymiuk, Peter J., E-mail: p.artymiuk@sheffield.ac.uk [Dept. of Molecular Biology and Biotechnology, Firth Court, University of Sheffield, S10 T2N Sheffield (United Kingdom); Firdaus-Raih, Mohd, E-mail: firdaus@mfrlab.org [School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi (Malaysia)

    2015-09-25

    A fundamental understanding of the atomic level interactions in ribonucleic acid (RNA) and how they contribute towards RNA architecture is an important knowledge platform to develop through the discovery of motifs from simple arrangements base pairs, to more complex arrangements such as triples and larger patterns involving non-standard interactions. The network of hydrogen bond interactions is important in connecting bases to form potential tertiary motifs. Therefore, there is an urgent need for the development of automated methods for annotating RNA 3D structures based on hydrogen bond interactions. COnnection tables Graphs for Nucleic ACids (COGNAC) is automated annotation system using graph theoretical approaches that has been developed for the identification of RNA 3D motifs. This program searches for patterns in the unbroken networks of hydrogen bonds for RNA structures and capable of annotating base pairs and higher-order base interactions, which ranges from triples to sextuples. COGNAC was able to discover 22 out of 32 quadruples occurrences of the Haloarcula marismortui large ribosomal subunit (PDB ID: 1FFK) and two out of three occurrences of quintuple interaction reported by the non-canonical interactions in RNA (NCIR) database. These and several other interactions of interest will be discussed in this paper. These examples demonstrate that the COGNAC program can serve as an automated annotation system that can be used to annotate conserved base-base interactions and could be added as additional information to established RNA secondary structure prediction methods.

  12. A computational approach for the annotation of hydrogen-bonded base interactions in crystallographic structures of the ribozymes

    International Nuclear Information System (INIS)

    Hamdani, Hazrina Yusof; Artymiuk, Peter J.; Firdaus-Raih, Mohd

    2015-01-01

    A fundamental understanding of the atomic level interactions in ribonucleic acid (RNA) and how they contribute towards RNA architecture is an important knowledge platform to develop through the discovery of motifs from simple arrangements base pairs, to more complex arrangements such as triples and larger patterns involving non-standard interactions. The network of hydrogen bond interactions is important in connecting bases to form potential tertiary motifs. Therefore, there is an urgent need for the development of automated methods for annotating RNA 3D structures based on hydrogen bond interactions. COnnection tables Graphs for Nucleic ACids (COGNAC) is automated annotation system using graph theoretical approaches that has been developed for the identification of RNA 3D motifs. This program searches for patterns in the unbroken networks of hydrogen bonds for RNA structures and capable of annotating base pairs and higher-order base interactions, which ranges from triples to sextuples. COGNAC was able to discover 22 out of 32 quadruples occurrences of the Haloarcula marismortui large ribosomal subunit (PDB ID: 1FFK) and two out of three occurrences of quintuple interaction reported by the non-canonical interactions in RNA (NCIR) database. These and several other interactions of interest will be discussed in this paper. These examples demonstrate that the COGNAC program can serve as an automated annotation system that can be used to annotate conserved base-base interactions and could be added as additional information to established RNA secondary structure prediction methods

  13. Differentiating signals to make biological sense - A guide through databases for MS-based non-targeted metabolomics.

    Science.gov (United States)

    Gil de la Fuente, Alberto; Grace Armitage, Emily; Otero, Abraham; Barbas, Coral; Godzien, Joanna

    2017-09-01

    Metabolite identification is one of the most challenging steps in metabolomics studies and reflects one of the greatest bottlenecks in the entire workflow. The success of this step determines the success of the entire research, therefore the quality at which annotations are given requires special attention. A variety of tools and resources are available to aid metabolite identification or annotation, offering different and often complementary functionalities. In preparation for this article, almost 50 databases were reviewed, from which 17 were selected for discussion, chosen for their online ESI-MS functionality. The general characteristics and functions of each database is discussed in turn, considering the advantages and limitations of each along with recommendations for optimal use of each tool, as derived from experiences encountered at the Centre for Metabolomics and Bioanalysis (CEMBIO) in Madrid. These databases were evaluated considering their utility in non-targeted metabolomics, including aspects such as identifier assignment, structural assignment and interpretation of results. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Annotate-it: a Swiss-knife approach to annotation, analysis and interpretation of single nucleotide variation in human disease.

    Science.gov (United States)

    Sifrim, Alejandro; Van Houdt, Jeroen Kj; Tranchevent, Leon-Charles; Nowakowska, Beata; Sakai, Ryo; Pavlopoulos, Georgios A; Devriendt, Koen; Vermeesch, Joris R; Moreau, Yves; Aerts, Jan

    2012-01-01

    The increasing size and complexity of exome/genome sequencing data requires new tools for clinical geneticists to discover disease-causing variants. Bottlenecks in identifying the causative variation include poor cross-sample querying, constantly changing functional annotation and not considering existing knowledge concerning the phenotype. We describe a methodology that facilitates exploration of patient sequencing data towards identification of causal variants under different genetic hypotheses. Annotate-it facilitates handling, analysis and interpretation of high-throughput single nucleotide variant data. We demonstrate our strategy using three case studies. Annotate-it is freely available and test data are accessible to all users at http://www.annotate-it.org.

  15. trieFinder: an efficient program for annotating Digital Gene Expression (DGE) tags.

    Science.gov (United States)

    Renaud, Gabriel; LaFave, Matthew C; Liang, Jin; Wolfsberg, Tyra G; Burgess, Shawn M

    2014-10-13

    Quantification of a transcriptional profile is a useful way to evaluate the activity of a cell at a given point in time. Although RNA-Seq has revolutionized transcriptional profiling, the costs of RNA-Seq are still significantly higher than microarrays, and often the depth of data delivered from RNA-Seq is in excess of what is needed for simple transcript quantification. Digital Gene Expression (DGE) is a cost-effective, sequence-based approach for simple transcript quantification: by sequencing one read per molecule of RNA, this technique can be used to efficiently count transcripts while obviating the need for transcript-length normalization and reducing the total numbers of reads necessary for accurate quantification. Here, we present trieFinder, a program specifically designed to rapidly map, parse, and annotate DGE tags of various lengths against cDNA and/or genomic sequence databases. The trieFinder algorithm maps DGE tags in a two-step process. First, it scans FASTA files of RefSeq, UniGene, and genomic DNA sequences to create a database of all tags that can be derived from a predefined restriction site. Next, it compares the experimental DGE tags to this tag database, taking advantage of the fact that the tags are stored as a prefix tree, or "trie", which allows for linear-time searches for exact matches. DGE tags with mismatches are analyzed by recursive calls in the data structure. We find that, in terms of alignment speed, the mapping functionality of trieFinder compares favorably with Bowtie. trieFinder can quickly provide the user an annotation of the DGE tags from three sources simultaneously, simplifying transcript quantification and novel transcript detection, delivering the data in a simple parsed format, obviating the need to post-process the alignment results. trieFinder is available at http://research.nhgri.nih.gov/software/trieFinder/.

  16. A Novel Quality Measure and Correction Procedure for the Annotation of Microbial Translation Initiation Sites.

    Directory of Open Access Journals (Sweden)

    Lex Overmars

    Full Text Available The identification of translation initiation sites (TISs constitutes an important aspect of sequence-based genome analysis. An erroneous TIS annotation can impair the identification of regulatory elements and N-terminal signal peptides, and also may flaw the determination of descent, for any particular gene. We have formulated a reference-free method to score the TIS annotation quality. The method is based on a comparison of the observed and expected distribution of all TISs in a particular genome given prior gene-calling. We have assessed the TIS annotations for all available NCBI RefSeq microbial genomes and found that approximately 87% is of appropriate quality, whereas 13% needs substantial improvement. We have analyzed a number of factors that could affect TIS annotation quality such as GC-content, taxonomy, the fraction of genes with a Shine-Dalgarno sequence and the year of publication. The analysis showed that only the first factor has a clear effect. We have then formulated a straightforward Principle Component Analysis-based TIS identification strategy to self-organize and score potential TISs. The strategy is independent of reference data and a priori calculations. A representative set of 277 genomes was subjected to the analysis and we found a clear increase in TIS annotation quality for the genomes with a low quality score. The PCA-based annotation was also compared with annotation with the current tool of reference, Prodigal. The comparison for the model genome of Escherichia coli K12 showed that both methods supplement each other and that prediction agreement can be used as an indicator of a correct TIS annotation. Importantly, the data suggest that the addition of a PCA-based strategy to a Prodigal prediction can be used to 'flag' TIS annotations for re-evaluation and in addition can be used to evaluate a given annotation in case a Prodigal annotation is lacking.

  17. Annotated chemical patent corpus: a gold standard for text mining.

    Directory of Open Access Journals (Sweden)

    Saber A Akhondi

    Full Text Available Exploring the chemical and biological space covered by patent applications is crucial in early-stage medicinal chemistry activities. Patent analysis can provide understanding of compound prior art, novelty checking, validation of biological assays, and identification of new starting points for chemical exploration. Extracting chemical and biological entities from patents through manual extraction by expert curators can take substantial amount of time and resources. Text mining methods can help to ease this process. To validate the performance of such methods, a manually annotated patent corpus is essential. In this study we have produced a large gold standard chemical patent corpus. We developed annotation guidelines and selected 200 full patents from the World Intellectual Property Organization, United States Patent and Trademark Office, and European Patent Office. The patents were pre-annotated automatically and made available to four independent annotator groups each consisting of two to ten annotators. The annotators marked chemicals in different subclasses, diseases, targets, and modes of action. Spelling mistakes and spurious line break due to optical character recognition errors were also annotated. A subset of 47 patents was annotated by at least three annotator groups, from which harmonized annotations and inter-annotator agreement scores were derived. One group annotated the full set. The patent corpus includes 400,125 annotations for the full set and 36,537 annotations for the harmonized set. All patents and annotated entities are publicly available at www.biosemantics.org.

  18. Generation of a predicted protein database from EST data and application to iTRAQ analyses in grape (Vitis vinifera cv. Cabernet Sauvignon) berries at ripening initiation

    Science.gov (United States)

    Lücker, Joost; Laszczak, Mario; Smith, Derek; Lund, Steven T

    2009-01-01

    Background iTRAQ is a proteomics technique that uses isobaric tags for relative and absolute quantitation of tryptic peptides. In proteomics experiments, the detection and high confidence annotation of proteins and the significance of corresponding expression differences can depend on the quality and the species specificity of the tryptic peptide map database used for analysis of the data. For species for which finished genome sequence data are not available, identification of proteins relies on similarity to proteins from other species using comprehensive peptide map databases such as the MSDB. Results We were interested in characterizing ripening initiation ('veraison') in grape berries at the protein level in order to better define the molecular control of this important process for grape growers and wine makers. We developed a bioinformatic pipeline for processing EST data in order to produce a predicted tryptic peptide database specifically targeted to the wine grape cultivar, Vitis vinifera cv. Cabernet Sauvignon, and lacking truncated N- and C-terminal fragments. By searching iTRAQ MS/MS data generated from berry exocarp and mesocarp samples at ripening initiation, we determined that implementation of the custom database afforded a large improvement in high confidence peptide annotation in comparison to the MSDB. We used iTRAQ MS/MS in conjunction with custom peptide db searches to quantitatively characterize several important pathway components for berry ripening previously described at the transcriptional level and confirmed expression patterns for these at the protein level. Conclusion We determined that a predicted peptide database for MS/MS applications can be derived from EST data using advanced clustering and trimming approaches and successfully implemented for quantitative proteome profiling. Quantitative shotgun proteome profiling holds great promise for characterizing biological processes such as fruit ripening initiation and may be further

  19. Managing the data deluge: data-driven GO category assignment improves while complexity of functional annotation increases.

    Science.gov (United States)

    Gobeill, Julien; Pasche, Emilie; Vishnyakova, Dina; Ruch, Patrick

    2013-01-01

    The available curated data lag behind current biological knowledge contained in the literature. Text mining can assist biologists and curators to locate and access this knowledge, for instance by characterizing the functional profile of publications. Gene Ontology (GO) category assignment in free text already supports various applications, such as powering ontology-based search engines, finding curation-relevant articles (triage) or helping the curator to identify and encode functions. Popular text mining tools for GO classification are based on so called thesaurus-based--or dictionary-based--approaches, which exploit similarities between the input text and GO terms themselves. But their effectiveness remains limited owing to the complex nature of GO terms, which rarely occur in text. In contrast, machine learning approaches exploit similarities between the input text and already curated instances contained in a knowledge base to infer a functional profile. GO Annotations (GOA) and MEDLINE make possible to exploit a growing amount of curated abstracts (97 000 in November 2012) for populating this knowledge base. Our study compares a state-of-the-art thesaurus-based system with a machine learning system (based on a k-Nearest Neighbours algorithm) for the task of proposing a functional profile for unseen MEDLINE abstracts, and shows how resources and performances have evolved. Systems are evaluated on their ability to propose for a given abstract the GO terms (2.8 on average) used for curation in GOA. We show that since 2006, although a massive effort was put into adding synonyms in GO (+300%), our thesaurus-based system effectiveness is rather constant, reaching from 0.28 to 0.31 for Recall at 20 (R20). In contrast, thanks to its knowledge base growth, our machine learning system has steadily improved, reaching from 0.38 in 2006 to 0.56 for R20 in 2012. Integrated in semi-automatic workflows or in fully automatic pipelines, such systems are more and more efficient

  20. Annotating gene sets by mining large literature collections with protein networks.

    Science.gov (United States)

    Wang, Sheng; Ma, Jianzhu; Yu, Michael Ku; Zheng, Fan; Huang, Edward W; Han, Jiawei; Peng, Jian; Ideker, Trey

    2018-01-01

    Analysis of patient genomes and transcriptomes routinely recognizes new gene sets associated with human disease. Here we present an integrative natural language processing system which infers common functions for a gene set through automatic mining of the scientific literature with biological networks. This system links genes with associated literature phrases and combines these links with protein interactions in a single heterogeneous network. Multiscale functional annotations are inferred based on network distances between phrases and genes and then visualized as an ontology of biological concepts. To evaluate this system, we predict functions for gene sets representing known pathways and find that our approach achieves substantial improvement over the conventional text-mining baseline method. Moreover, our system discovers novel annotations for gene sets or pathways without previously known functions. Two case studies demonstrate how the system is used in discovery of new cancer-related pathways with ontological annotations.

  1. Diverse Image Annotation

    KAUST Repository

    Wu, Baoyuan

    2017-11-09

    In this work we study the task of image annotation, of which the goal is to describe an image using a few tags. Instead of predicting the full list of tags, here we target for providing a short list of tags under a limited number (e.g., 3), to cover as much information as possible of the image. The tags in such a short list should be representative and diverse. It means they are required to be not only corresponding to the contents of the image, but also be different to each other. To this end, we treat the image annotation as a subset selection problem based on the conditional determinantal point process (DPP) model, which formulates the representation and diversity jointly. We further explore the semantic hierarchy and synonyms among the candidate tags, and require that two tags in a semantic hierarchy or in a pair of synonyms should not be selected simultaneously. This requirement is then embedded into the sampling algorithm according to the learned conditional DPP model. Besides, we find that traditional metrics for image annotation (e.g., precision, recall and F1 score) only consider the representation, but ignore the diversity. Thus we propose new metrics to evaluate the quality of the selected subset (i.e., the tag list), based on the semantic hierarchy and synonyms. Human study through Amazon Mechanical Turk verifies that the proposed metrics are more close to the humans judgment than traditional metrics. Experiments on two benchmark datasets show that the proposed method can produce more representative and diverse tags, compared with existing image annotation methods.

  2. Diverse Image Annotation

    KAUST Repository

    Wu, Baoyuan; Jia, Fan; Liu, Wei; Ghanem, Bernard

    2017-01-01

    In this work we study the task of image annotation, of which the goal is to describe an image using a few tags. Instead of predicting the full list of tags, here we target for providing a short list of tags under a limited number (e.g., 3), to cover as much information as possible of the image. The tags in such a short list should be representative and diverse. It means they are required to be not only corresponding to the contents of the image, but also be different to each other. To this end, we treat the image annotation as a subset selection problem based on the conditional determinantal point process (DPP) model, which formulates the representation and diversity jointly. We further explore the semantic hierarchy and synonyms among the candidate tags, and require that two tags in a semantic hierarchy or in a pair of synonyms should not be selected simultaneously. This requirement is then embedded into the sampling algorithm according to the learned conditional DPP model. Besides, we find that traditional metrics for image annotation (e.g., precision, recall and F1 score) only consider the representation, but ignore the diversity. Thus we propose new metrics to evaluate the quality of the selected subset (i.e., the tag list), based on the semantic hierarchy and synonyms. Human study through Amazon Mechanical Turk verifies that the proposed metrics are more close to the humans judgment than traditional metrics. Experiments on two benchmark datasets show that the proposed method can produce more representative and diverse tags, compared with existing image annotation methods.

  3. Annotating individual human genomes.

    Science.gov (United States)

    Torkamani, Ali; Scott-Van Zeeland, Ashley A; Topol, Eric J; Schork, Nicholas J

    2011-10-01

    Advances in DNA sequencing technologies have made it possible to rapidly, accurately and affordably sequence entire individual human genomes. As impressive as this ability seems, however, it will not likely amount to much if one cannot extract meaningful information from individual sequence data. Annotating variations within individual genomes and providing information about their biological or phenotypic impact will thus be crucially important in moving individual sequencing projects forward, especially in the context of the clinical use of sequence information. In this paper we consider the various ways in which one might annotate individual sequence variations and point out limitations in the available methods for doing so. It is arguable that, in the foreseeable future, DNA sequencing of individual genomes will become routine for clinical, research, forensic, and personal purposes. We therefore also consider directions and areas for further research in annotating genomic variants. Copyright © 2011 Elsevier Inc. All rights reserved.

  4. ANNOTATING INDIVIDUAL HUMAN GENOMES*

    Science.gov (United States)

    Torkamani, Ali; Scott-Van Zeeland, Ashley A.; Topol, Eric J.; Schork, Nicholas J.

    2014-01-01

    Advances in DNA sequencing technologies have made it possible to rapidly, accurately and affordably sequence entire individual human genomes. As impressive as this ability seems, however, it will not likely to amount to much if one cannot extract meaningful information from individual sequence data. Annotating variations within individual genomes and providing information about their biological or phenotypic impact will thus be crucially important in moving individual sequencing projects forward, especially in the context of the clinical use of sequence information. In this paper we consider the various ways in which one might annotate individual sequence variations and point out limitations in the available methods for doing so. It is arguable that, in the foreseeable future, DNA sequencing of individual genomes will become routine for clinical, research, forensic, and personal purposes. We therefore also consider directions and areas for further research in annotating genomic variants. PMID:21839162

  5. The Microbe Directory: An annotated, searchable inventory of microbes’ characteristics

    Science.gov (United States)

    Mohammad, Rawhi; Danko, David; Bezdan, Daniela; Afshinnekoo, Ebrahim; Segata, Nicola; Mason, Christopher E.

    2018-01-01

    The Microbe Directory is a collective research effort to profile and annotate more than 7,500 unique microbial species from the MetaPhlAn2 database that includes bacteria, archaea, viruses, fungi, and protozoa. By collecting and summarizing data on various microbes’ characteristics, the project comprises a database that can be used downstream of large-scale metagenomic taxonomic analyses, allowing one to interpret and explore their taxonomic classifications to have a deeper understanding of the microbial ecosystem they are studying. Such characteristics include, but are not limited to: optimal pH, optimal temperature, Gram stain, biofilm-formation, spore-formation, antimicrobial resistance, and COGEM class risk rating. The database has been manually curated by trained student-researchers from Weill Cornell Medicine and CUNY—Hunter College, and its analysis remains an ongoing effort with open-source capabilities so others can contribute. Available in SQL, JSON, and CSV (i.e. Excel) formats, the Microbe Directory can be queried for the aforementioned parameters by a microorganism’s taxonomy. In addition to the raw database, The Microbe Directory has an online counterpart ( https://microbe.directory/) that provides a user-friendly interface for storage, retrieval, and analysis into which other microbial database projects could be incorporated. The Microbe Directory was primarily designed to serve as a resource for researchers conducting metagenomic analyses, but its online web interface should also prove useful to any individual who wishes to learn more about any particular microbe. PMID:29630066

  6. The Microbe Directory: An annotated, searchable inventory of microbes' characteristics.

    Science.gov (United States)

    Shaaban, Heba; Westfall, David A; Mohammad, Rawhi; Danko, David; Bezdan, Daniela; Afshinnekoo, Ebrahim; Segata, Nicola; Mason, Christopher E

    2018-01-05

    The Microbe Directory is a collective research effort to profile and annotate more than 7,500 unique microbial species from the MetaPhlAn2 database that includes bacteria, archaea, viruses, fungi, and protozoa. By collecting and summarizing data on various microbes' characteristics, the project comprises a database that can be used downstream of large-scale metagenomic taxonomic analyses, allowing one to interpret and explore their taxonomic classifications to have a deeper understanding of the microbial ecosystem they are studying. Such characteristics include, but are not limited to: optimal pH, optimal temperature, Gram stain, biofilm-formation, spore-formation, antimicrobial resistance, and COGEM class risk rating. The database has been manually curated by trained student-researchers from Weill Cornell Medicine and CUNY-Hunter College, and its analysis remains an ongoing effort with open-source capabilities so others can contribute. Available in SQL, JSON, and CSV (i.e. Excel) formats, the Microbe Directory can be queried for the aforementioned parameters by a microorganism's taxonomy. In addition to the raw database, The Microbe Directory has an online counterpart ( https://microbe.directory/) that provides a user-friendly interface for storage, retrieval, and analysis into which other microbial database projects could be incorporated. The Microbe Directory was primarily designed to serve as a resource for researchers conducting metagenomic analyses, but its online web interface should also prove useful to any individual who wishes to learn more about any particular microbe.

  7. NegGOA: negative GO annotations selection using ontology structure.

    Science.gov (United States)

    Fu, Guangyuan; Wang, Jun; Yang, Bo; Yu, Guoxian

    2016-10-01

    Predicting the biological functions of proteins is one of the key challenges in the post-genomic era. Computational models have demonstrated the utility of applying machine learning methods to predict protein function. Most prediction methods explicitly require a set of negative examples-proteins that are known not carrying out a particular function. However, Gene Ontology (GO) almost always only provides the knowledge that proteins carry out a particular function, and functional annotations of proteins are incomplete. GO structurally organizes more than tens of thousands GO terms and a protein is annotated with several (or dozens) of these terms. For these reasons, the negative examples of a protein can greatly help distinguishing true positive examples of the protein from such a large candidate GO space. In this paper, we present a novel approach (called NegGOA) to select negative examples. Specifically, NegGOA takes advantage of the ontology structure, available annotations and potentiality of additional annotations of a protein to choose negative examples of the protein. We compare NegGOA with other negative examples selection algorithms and find that NegGOA produces much fewer false negatives than them. We incorporate the selected negative examples into an efficient function prediction model to predict the functions of proteins in Yeast, Human, Mouse and Fly. NegGOA also demonstrates improved accuracy than these comparing algorithms across various evaluation metrics. In addition, NegGOA is less suffered from incomplete annotations of proteins than these comparing methods. The Matlab and R codes are available at https://sites.google.com/site/guoxian85/neggoa gxyu@swu.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  8. ChemProt-2.0: visual navigation in a disease chemical biology database

    DEFF Research Database (Denmark)

    Kjærulff, Sonny Kim; Wich, Louis; Kringelum, Jens Vindahl

    2013-01-01

    ChemProt-2.0 (http://www.cbs.dtu.dk/services/ChemProt-2.0) is a public available compilation of multiple chemical-protein annotation resources integrated with diseases and clinical outcomes information. The database has been updated to > 1.15 million compounds with 5.32 millions bioactivity measu...

  9. GSV Annotated Bibliography

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, Randy S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pope, Paul A. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Jiang, Ming [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Trucano, Timothy G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Aragon, Cecilia R. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ni, Kevin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Wei, Thomas [Argonne National Lab. (ANL), Argonne, IL (United States); Chilton, Lawrence K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bakel, Alan [Argonne National Lab. (ANL), Argonne, IL (United States)

    2010-09-14

    The following annotated bibliography was developed as part of the geospatial algorithm verification and validation (GSV) project for the Simulation, Algorithms and Modeling program of NA-22. Verification and Validation of geospatial image analysis algorithms covers a wide range of technologies. Papers in the bibliography are thus organized into the following five topic areas: Image processing and analysis, usability and validation of geospatial image analysis algorithms, image distance measures, scene modeling and image rendering, and transportation simulation models. Many other papers were studied during the course of the investigation including. The annotations for these articles can be found in the paper "On the verification and validation of geospatial image analysis algorithms".

  10. Adolescent Literacy Resources: An Annotated Bibliography. Second Edition 2009

    Science.gov (United States)

    Center on Instruction, 2009

    2009-01-01

    This annotated bibliography updated from a 2007 edition, is intended as a resource for technical assistance providers as they work with states on adolescent literacy. This revision includes current research and documents of practical use in guiding improvements in grades 4-12 reading instruction in the content areas and in interventions for…

  11. Solar Tutorial and Annotation Resource (STAR)

    Science.gov (United States)

    Showalter, C.; Rex, R.; Hurlburt, N. E.; Zita, E. J.

    2009-12-01

    We have written a software suite designed to facilitate solar data analysis by scientists, students, and the public, anticipating enormous datasets from future instruments. Our “STAR" suite includes an interactive learning section explaining 15 classes of solar events. Users learn software tools that exploit humans’ superior ability (over computers) to identify many events. Annotation tools include time slice generation to quantify loop oscillations, the interpolation of event shapes using natural cubic splines (for loops, sigmoids, and filaments) and closed cubic splines (for coronal holes). Learning these tools in an environment where examples are provided prepares new users to comfortably utilize annotation software with new data. Upon completion of our tutorial, users are presented with media of various solar events and asked to identify and annotate the images, to test their mastery of the system. Goals of the project include public input into the data analysis of very large datasets from future solar satellites, and increased public interest and knowledge about the Sun. In 2010, the Solar Dynamics Observatory (SDO) will be launched into orbit. SDO’s advancements in solar telescope technology will generate a terabyte per day of high-quality data, requiring innovation in data management. While major projects develop automated feature recognition software, so that computers can complete much of the initial event tagging and analysis, still, that software cannot annotate features such as sigmoids, coronal magnetic loops, coronal dimming, etc., due to large amounts of data concentrated in relatively small areas. Previously, solar physicists manually annotated these features, but with the imminent influx of data it is unrealistic to expect specialized researchers to examine every image that computers cannot fully process. A new approach is needed to efficiently process these data. Providing analysis tools and data access to students and the public have proven

  12. MIPS bacterial genomes functional annotation benchmark dataset.

    Science.gov (United States)

    Tetko, Igor V; Brauner, Barbara; Dunger-Kaltenbach, Irmtraud; Frishman, Goar; Montrone, Corinna; Fobo, Gisela; Ruepp, Andreas; Antonov, Alexey V; Surmeli, Dimitrij; Mewes, Hans-Wernen

    2005-05-15

    Any development of new methods for automatic functional annotation of proteins according to their sequences requires high-quality data (as benchmark) as well as tedious preparatory work to generate sequence parameters required as input data for the machine learning methods. Different program settings and incompatible protocols make a comparison of the analyzed methods difficult. The MIPS Bacterial Functional Annotation Benchmark dataset (MIPS-BFAB) is a new, high-quality resource comprising four bacterial genomes manually annotated according to the MIPS functional catalogue (FunCat). These resources include precalculated sequence parameters, such as sequence similarity scores, InterPro domain composition and other parameters that could be used to develop and benchmark methods for functional annotation of bacterial protein sequences. These data are provided in XML format and can be used by scientists who are not necessarily experts in genome annotation. BFAB is available at http://mips.gsf.de/proj/bfab

  13. Data Integration for Spatio-Temporal Patterns of Gene Expression of Zebrafish development: the GEMS database

    Directory of Open Access Journals (Sweden)

    Belmamoune Mounia

    2008-06-01

    Full Text Available The Gene Expression Management System (GEMS is a database system for patterns of gene expression. These patterns result from systematic whole-mount fluorescent in situ hybridization studies on zebrafish embryos. GEMS is an integrative platform that addresses one of the important challenges of developmental biology: how to integrate genetic data that underpin morphological changes during embryogenesis. Our motivation to build this system was by the need to be able to organize and compare multiple patterns of gene expression at tissue level. Integration with other developmental and biomolecular databases will further support our understanding of development. The GEMS operates in concert with a database containing a digital atlas of zebrafish embryo; this digital atlas of zebrafish development has been conceived prior to the expansion of the GEMS. The atlas contains 3D volume models of canonical stages of zebrafish development in which in each volume model element is annotated with an anatomical term. These terms are extracted from a formal anatomical ontology, i.e. the Developmental Anatomy Ontology of Zebrafish (DAOZ. In the GEMS, anatomical terms from this ontology together with terms from the Gene Ontology (GO are also used to annotate patterns of gene expression and in this manner providing mechanisms for integration and retrieval . The annotations are the glue for integration of patterns of gene expression in GEMS as well as in other biomolecular databases. At the one hand, zebrafish anatomy terminology allows gene expression data within GEMS to be integrated with phenotypical data in the 3D atlas of zebrafish development. At the other hand, GO terms extend GEMS expression patterns integration to a wide range of bioinformatics resources.

  14. A SNP-centric database for the investigation of the human genome

    Directory of Open Access Journals (Sweden)

    Kohane Isaac S

    2004-03-01

    Full Text Available Abstract Background Single Nucleotide Polymorphisms (SNPs are an increasingly important tool for genetic and biomedical research. Although current genomic databases contain information on several million SNPs and are growing at a very fast rate, the true value of a SNP in this context is a function of the quality of the annotations that characterize it. Retrieving and analyzing such data for a large number of SNPs often represents a major bottleneck in the design of large-scale association studies. Description SNPper is a web-based application designed to facilitate the retrieval and use of human SNPs for high-throughput research purposes. It provides a rich local database generated by combining SNP data with the Human Genome sequence and with several other data sources, and offers the user a variety of querying, visualization and data export tools. In this paper we describe the structure and organization of the SNPper database, we review the available data export and visualization options, and we describe how the architecture of SNPper and its specialized data structures support high-volume SNP analysis. Conclusions The rich annotation database and the powerful data manipulation and presentation facilities it offers make SNPper a very useful online resource for SNP research. Its success proves the great need for integrated and interoperable resources in the field of computational biology, and shows how such systems may play a critical role in supporting the large-scale computational analysis of our genome.

  15. Annotating non-coding regions of the genome.

    Science.gov (United States)

    Alexander, Roger P; Fang, Gang; Rozowsky, Joel; Snyder, Michael; Gerstein, Mark B

    2010-08-01

    Most of the human genome consists of non-protein-coding DNA. Recently, progress has been made in annotating these non-coding regions through the interpretation of functional genomics experiments and comparative sequence analysis. One can conceptualize functional genomics analysis as involving a sequence of steps: turning the output of an experiment into a 'signal' at each base pair of the genome; smoothing this signal and segmenting it into small blocks of initial annotation; and then clustering these small blocks into larger derived annotations and networks. Finally, one can relate functional genomics annotations to conserved units and measures of conservation derived from comparative sequence analysis.

  16. Systems Theory and Communication. Annotated Bibliography.

    Science.gov (United States)

    Covington, William G., Jr.

    This annotated bibliography presents annotations of 31 books and journal articles dealing with systems theory and its relation to organizational communication, marketing, information theory, and cybernetics. Materials were published between 1963 and 1992 and are listed alphabetically by author. (RS)

  17. TypeLoader: A fast and efficient automated workflow for the annotation and submission of novel full-length HLA alleles.

    Science.gov (United States)

    Surendranath, V; Albrecht, V; Hayhurst, J D; Schöne, B; Robinson, J; Marsh, S G E; Schmidt, A H; Lange, V

    2017-07-01

    Recent years have seen a rapid increase in the discovery of novel allelic variants of the human leukocyte antigen (HLA) genes. Commonly, only the exons encoding the peptide binding domains of novel HLA alleles are submitted. As a result, the IPD-IMGT/HLA Database lacks sequence information outside those regions for the majority of known alleles. This has implications for the application of the new sequencing technologies, which deliver sequence data often covering the complete gene. As these technologies simplify the characterization of the complete gene regions, it is desirable for novel alleles to be submitted as full-length sequences to the database. However, the manual annotation of full-length alleles and the generation of specific formats required by the sequence repositories is prone to error and time consuming. We have developed TypeLoader to address both these facets. With only the full-length sequence as a starting point, Typeloader performs automatic sequence annotation and subsequently handles all steps involved in preparing the specific formats for submission with very little manual intervention. TypeLoader is routinely used at the DKMS Life Science Lab and has aided in the successful submission of more than 900 novel HLA alleles as full-length sequences to the European Nucleotide Archive repository and the IPD-IMGT/HLA Database with a 95% reduction in the time spent on annotation and submission when compared with handling these processes manually. TypeLoader is implemented as a web application and can be easily installed and used on a standalone Linux desktop system or within a Linux client/server architecture. TypeLoader is downloadable from http://www.github.com/DKMS-LSL/typeloader. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  18. Annotation-based enrichment of Digital Objects using open-source frameworks

    Directory of Open Access Journals (Sweden)

    Marcus Emmanuel Barnes

    2017-07-01

    Full Text Available The W3C Web Annotation Data Model, Protocol, and Vocabulary unify approaches to annotations across the web, enabling their aggregation, discovery and persistence over time. In addition, new javascript libraries provide the ability for users to annotate multi-format content. In this paper, we describe how we have leveraged these developments to provide annotation features alongside Islandora’s existing preservation, access, and management capabilities. We also discuss our experience developing with the Web Annotation Model as an open web architecture standard, as well as our approach to integrating mature external annotation libraries. The resulting software (the Web Annotation Utility Module for Islandora accommodates annotation across multiple formats. This solution can be used in various digital scholarship contexts.

  19. PairWise Neighbours database: overlaps and spacers among prokaryote genomes

    Directory of Open Access Journals (Sweden)

    Garcia-Vallvé Santiago

    2009-06-01

    Full Text Available Abstract Background Although prokaryotes live in a variety of habitats and possess different metabolic and genomic complexity, they have several genomic architectural features in common. The overlapping genes are a common feature of the prokaryote genomes. The overlapping lengths tend to be short because as the overlaps become longer they have more risk of deleterious mutations. The spacers between genes tend to be short too because of the tendency to reduce the non coding DNA among prokaryotes. However they must be long enough to maintain essential regulatory signals such as the Shine-Dalgarno (SD sequence, which is responsible of an efficient translation. Description PairWise Neighbours is an interactive and intuitive database used for retrieving information about the spacers and overlapping genes among bacterial and archaeal genomes. It contains 1,956,294 gene pairs from 678 fully sequenced prokaryote genomes and is freely available at the URL http://genomes.urv.cat/pwneigh. This database provides information about the overlaps and their conservation across species. Furthermore, it allows the wide analysis of the intergenic regions providing useful information such as the location and strength of the SD sequence. Conclusion There are experiments and bioinformatic analysis that rely on correct annotations of the initiation site. Therefore, a database that studies the overlaps and spacers among prokaryotes appears to be desirable. PairWise Neighbours database permits the reliability analysis of the overlapping structures and the study of the SD presence and location among the adjacent genes, which may help to check the annotation of the initiation sites.

  20. cuticleDB: a relational database of Arthropod cuticular proteins

    Directory of Open Access Journals (Sweden)

    Willis Judith H

    2004-09-01

    Full Text Available Abstract Background The insect exoskeleton or cuticle is a bi-partite composite of proteins and chitin that provides protective, skeletal and structural functions. Little information is available about the molecular structure of this important complex that exhibits a helicoidal architecture. Scores of sequences of cuticular proteins have been obtained from direct protein sequencing, from cDNAs, and from genomic analyses. Most of these cuticular protein sequences contain motifs found only in arthropod proteins. Description cuticleDB is a relational database containing all structural proteins of Arthropod cuticle identified to date. Many come from direct sequencing of proteins isolated from cuticle and from sequences from cDNAs that share common features with these authentic cuticular proteins. It also includes proteins from the Drosophila melanogaster and the Anopheles gambiae genomes, that have been predicted to be cuticular proteins, based on a Pfam motif (PF00379 responsible for chitin binding in Arthropod cuticle. The total number of the database entries is 445: 370 derive from insects, 60 from Crustacea and 15 from Chelicerata. The database can be accessed from our web server at http://bioinformatics.biol.uoa.gr/cuticleDB. Conclusions CuticleDB was primarily designed to contain correct and full annotation of cuticular protein data. The database will be of help to future genome annotators. Users will be able to test hypotheses for the existence of known and also of yet unknown motifs in cuticular proteins. An analysis of motifs may contribute to understanding how proteins contribute to the physical properties of cuticle as well as to the precise nature of their interaction with chitin.

  1. Sequence- and Structure-Based Functional Annotation and Assessment of Metabolic Transporters in Aspergillus oryzae: A Representative Case Study

    Directory of Open Access Journals (Sweden)

    Nachon Raethong

    2016-01-01

    Full Text Available Aspergillus oryzae is widely used for the industrial production of enzymes. In A. oryzae metabolism, transporters appear to play crucial roles in controlling the flux of molecules for energy generation, nutrients delivery, and waste elimination in the cell. While the A. oryzae genome sequence is available, transporter annotation remains limited and thus the connectivity of metabolic networks is incomplete. In this study, we developed a metabolic annotation strategy to understand the relationship between the sequence, structure, and function for annotation of A. oryzae metabolic transporters. Sequence-based analysis with manual curation showed that 58 genes of 12,096 total genes in the A. oryzae genome encoded metabolic transporters. Under consensus integrative databases, 55 unambiguous metabolic transporter genes were distributed into channels and pores (7 genes, electrochemical potential-driven transporters (33 genes, and primary active transporters (15 genes. To reveal the transporter functional role, a combination of homology modeling and molecular dynamics simulation was implemented to assess the relationship between sequence to structure and structure to function. As in the energy metabolism of A. oryzae, the H+-ATPase encoded by the AO090005000842 gene was selected as a representative case study of multilevel linkage annotation. Our developed strategy can be used for enhancing metabolic network reconstruction.

  2. Sequence- and Structure-Based Functional Annotation and Assessment of Metabolic Transporters in Aspergillus oryzae: A Representative Case Study.

    Science.gov (United States)

    Raethong, Nachon; Wong-Ekkabut, Jirasak; Laoteng, Kobkul; Vongsangnak, Wanwipa

    2016-01-01

    Aspergillus oryzae is widely used for the industrial production of enzymes. In A. oryzae metabolism, transporters appear to play crucial roles in controlling the flux of molecules for energy generation, nutrients delivery, and waste elimination in the cell. While the A. oryzae genome sequence is available, transporter annotation remains limited and thus the connectivity of metabolic networks is incomplete. In this study, we developed a metabolic annotation strategy to understand the relationship between the sequence, structure, and function for annotation of A. oryzae metabolic transporters. Sequence-based analysis with manual curation showed that 58 genes of 12,096 total genes in the A. oryzae genome encoded metabolic transporters. Under consensus integrative databases, 55 unambiguous metabolic transporter genes were distributed into channels and pores (7 genes), electrochemical potential-driven transporters (33 genes), and primary active transporters (15 genes). To reveal the transporter functional role, a combination of homology modeling and molecular dynamics simulation was implemented to assess the relationship between sequence to structure and structure to function. As in the energy metabolism of A. oryzae, the H(+)-ATPase encoded by the AO090005000842 gene was selected as a representative case study of multilevel linkage annotation. Our developed strategy can be used for enhancing metabolic network reconstruction.

  3. An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave.

    Science.gov (United States)

    Silva, Ikaro; Moody, George B

    The WaveForm DataBase (WFDB) Toolbox for MATLAB/Octave enables integrated access to PhysioNet's software and databases. Using the WFDB Toolbox for MATLAB/Octave, users have access to over 50 physiological databases in PhysioNet. The toolbox provides access over 4 TB of biomedical signals including ECG, EEG, EMG, and PLETH. Additionally, most signals are accompanied by metadata such as medical annotations of clinical events: arrhythmias, sleep stages, seizures, hypotensive episodes, etc. Users of this toolbox should easily be able to reproduce, validate, and compare results published based on PhysioNet's software and databases.

  4. A curated gluten protein sequence database to support development of proteomics methods for determination of gluten in gluten-free foods.

    Science.gov (United States)

    Bromilow, Sophie; Gethings, Lee A; Buckley, Mike; Bromley, Mike; Shewry, Peter R; Langridge, James I; Clare Mills, E N

    2017-06-23

    The unique physiochemical properties of wheat gluten enable a diverse range of food products to be manufactured. However, gluten triggers coeliac disease, a condition which is treated using a gluten-free diet. Analytical methods are required to confirm if foods are gluten-free, but current immunoassay-based methods can unreliable and proteomic methods offer an alternative but require comprehensive and well annotated sequence databases which are lacking for gluten. A manually a curated database (GluPro V1.0) of gluten proteins, comprising 630 discrete unique full length protein sequences has been compiled. It is representative of the different types of gliadin and glutenin components found in gluten. An in silico comparison of their coeliac toxicity was undertaken by analysing the distribution of coeliac toxic motifs. This demonstrated that whilst the α-gliadin proteins contained more toxic motifs, these were distributed across all gluten protein sub-types. Comparison of annotations observed using a discovery proteomics dataset acquired using ion mobility MS/MS showed that more reliable identifications were obtained using the GluPro V1.0 database compared to the complete reviewed Viridiplantae database. This highlights the value of a curated sequence database specifically designed to support the proteomic workflows and the development of methods to detect and quantify gluten. We have constructed the first manually curated open-source wheat gluten protein sequence database (GluPro V1.0) in a FASTA format to support the application of proteomic methods for gluten protein detection and quantification. We have also analysed the manually verified sequences to give the first comprehensive overview of the distribution of sequences able to elicit a reaction in coeliac disease, the prevalent form of gluten intolerance. Provision of this database will improve the reliability of gluten protein identification by proteomic analysis, and aid the development of targeted mass

  5. Using Nonexperts for Annotating Pharmacokinetic Drug-Drug Interaction Mentions in Product Labeling: A Feasibility Study.

    Science.gov (United States)

    Hochheiser, Harry; Ning, Yifan; Hernandez, Andres; Horn, John R; Jacobson, Rebecca; Boyce, Richard D

    2016-04-11

    Because vital details of potential pharmacokinetic drug-drug interactions are often described in free-text structured product labels, manual curation is a necessary but expensive step in the development of electronic drug-drug interaction information resources. The use of nonexperts to annotate potential drug-drug interaction (PDDI) mentions in drug product label annotation may be a means of lessening the burden of manual curation. Our goal was to explore the practicality of using nonexpert participants to annotate drug-drug interaction descriptions from structured product labels. By presenting annotation tasks to both pharmacy experts and relatively naïve participants, we hoped to demonstrate the feasibility of using nonexpert annotators for drug-drug information annotation. We were also interested in exploring whether and to what extent natural language processing (NLP) preannotation helped improve task completion time, accuracy, and subjective satisfaction. Two experts and 4 nonexperts were asked to annotate 208 structured product label sections under 4 conditions completed sequentially: (1) no NLP assistance, (2) preannotation of drug mentions, (3) preannotation of drug mentions and PDDIs, and (4) a repeat of the no-annotation condition. Results were evaluated within the 2 groups and relative to an existing gold standard. Participants were asked to provide reports on the time required to complete tasks and their perceptions of task difficulty. One of the experts and 3 of the nonexperts completed all tasks. Annotation results from the nonexpert group were relatively strong in every scenario and better than the performance of the NLP pipeline. The expert and 2 of the nonexperts were able to complete most tasks in less than 3 hours. Usability perceptions were generally positive (3.67 for expert, mean of 3.33 for nonexperts). The results suggest that nonexpert annotation might be a feasible option for comprehensive labeling of annotated PDDIs across a broader

  6. Desiderata for ontologies to be used in semantic annotation of biomedical documents.

    Science.gov (United States)

    Bada, Michael; Hunter, Lawrence

    2011-02-01

    A wealth of knowledge valuable to the translational research scientist is contained within the vast biomedical literature, but this knowledge is typically in the form of natural language. Sophisticated natural-language-processing systems are needed to translate text into unambiguous formal representations grounded in high-quality consensus ontologies, and these systems in turn rely on gold-standard corpora of annotated documents for training and testing. To this end, we are constructing the Colorado Richly Annotated Full-Text (CRAFT) Corpus, a collection of 97 full-text biomedical journal articles that are being manually annotated with the entire sets of terms from select vocabularies, predominantly from the Open Biomedical Ontologies (OBO) library. Our efforts in building this corpus has illuminated infelicities of these ontologies with respect to the semantic annotation of biomedical documents, and we propose desiderata whose implementation could substantially improve their utility in this task; these include the integration of overlapping terms across OBOs, the resolution of OBO-specific ambiguities, the integration of the BFO with the OBOs and the use of mid-level ontologies, the inclusion of noncanonical instances, and the expansion of relations and realizable entities. Copyright © 2010 Elsevier Inc. All rights reserved.

  7. Revised annotation of Plutella xylostella microRNAs and their genome-wide target identification.

    Science.gov (United States)

    Etebari, K; Asgari, S

    2016-12-01

    The diamondback moth, Plutella xylostella, is the most devastating pest of brassica crops worldwide. Although 128 mature microRNAs (miRNAs) have been annotated from this species in miRBase, there is a need to extend and correct the current P. xylostella miRNA repertoire as a result of its recently improved genome assembly and more available small RNA sequence data. We used our new ultra-deep sequence data and bioinformatics to re-annotate the P. xylostella genome for high confidence miRNAs with the correct 5p and 3p arm features. Furthermore, all the P. xylostella annotated genes were also screened to identify potential miRNA binding sites using three target-predicting algorithms. In total, 203 mature miRNAs were annotated, including 33 novel miRNAs. We identified 7691 highly confident binding sites for 160 pxy-miRNAs. The data provided here will facilitate future studies involving functional analyses of P. xylostella miRNAs as a platform to introduce novel approaches for sustainable management of this destructive pest. © 2016 The Royal Entomological Society.

  8. LRRML: a conformational database and an XML description of leucine-rich repeats (LRRs).

    Science.gov (United States)

    Wei, Tiandi; Gong, Jing; Jamitzky, Ferdinand; Heckl, Wolfgang M; Stark, Robert W; Rössle, Shaila C

    2008-11-05

    Leucine-rich repeats (LRRs) are present in more than 6000 proteins. They are found in organisms ranging from viruses to eukaryotes and play an important role in protein-ligand interactions. To date, more than one hundred crystal structures of LRR containing proteins have been determined. This knowledge has increased our ability to use the crystal structures as templates to model LRR proteins with unknown structures. Since the individual three-dimensional LRR structures are not directly available from the established databases and since there are only a few detailed annotations for them, a conformational LRR database useful for homology modeling of LRR proteins is desirable. We developed LRRML, a conformational database and an extensible markup language (XML) description of LRRs. The release 0.2 contains 1261 individual LRR structures, which were identified from 112 PDB structures and annotated manually. An XML structure was defined to exchange and store the LRRs. LRRML provides a source for homology modeling and structural analysis of LRR proteins. In order to demonstrate the capabilities of the database we modeled the mouse Toll-like receptor 3 (TLR3) by multiple templates homology modeling and compared the result with the crystal structure. LRRML is an information source for investigators involved in both theoretical and applied research on LRR proteins. It is available at http://zeus.krist.geo.uni-muenchen.de/~lrrml.

  9. LRRML: a conformational database and an XML description of leucine-rich repeats (LRRs

    Directory of Open Access Journals (Sweden)

    Stark Robert W

    2008-11-01

    Full Text Available Abstract Background Leucine-rich repeats (LRRs are present in more than 6000 proteins. They are found in organisms ranging from viruses to eukaryotes and play an important role in protein-ligand interactions. To date, more than one hundred crystal structures of LRR containing proteins have been determined. This knowledge has increased our ability to use the crystal structures as templates to model LRR proteins with unknown structures. Since the individual three-dimensional LRR structures are not directly available from the established databases and since there are only a few detailed annotations for them, a conformational LRR database useful for homology modeling of LRR proteins is desirable. Description We developed LRRML, a conformational database and an extensible markup language (XML description of LRRs. The release 0.2 contains 1261 individual LRR structures, which were identified from 112 PDB structures and annotated manually. An XML structure was defined to exchange and store the LRRs. LRRML provides a source for homology modeling and structural analysis of LRR proteins. In order to demonstrate the capabilities of the database we modeled the mouse Toll-like receptor 3 (TLR3 by multiple templates homology modeling and compared the result with the crystal structure. Conclusion LRRML is an information source for investigators involved in both theoretical and applied research on LRR proteins. It is available at http://zeus.krist.geo.uni-muenchen.de/~lrrml.

  10. High-throughput proteogenomics of Ruegeria pomeroyi: seeding a better genomic annotation for the whole marine Roseobacter clade

    Directory of Open Access Journals (Sweden)

    Christie-Oleza Joseph A

    2012-02-01

    Full Text Available Abstract Background The structural and functional annotation of genomes is now heavily based on data obtained using automated pipeline systems. The key for an accurate structural annotation consists of blending similarities between closely related genomes with biochemical evidence of the genome interpretation. In this work we applied high-throughput proteogenomics to Ruegeria pomeroyi, a member of the Roseobacter clade, an abundant group of marine bacteria, as a seed for the annotation of the whole clade. Results A large dataset of peptides from R. pomeroyi was obtained after searching over 1.1 million MS/MS spectra against a six-frame translated genome database. We identified 2006 polypeptides, of which thirty-four were encoded by open reading frames (ORFs that had not previously been annotated. From the pool of 'one-hit-wonders', i.e. those ORFs specified by only one peptide detected by tandem mass spectrometry, we could confirm the probable existence of five additional new genes after proving that the corresponding RNAs were transcribed. We also identified the most-N-terminal peptide of 486 polypeptides, of which sixty-four had originally been wrongly annotated. Conclusions By extending these re-annotations to the other thirty-six Roseobacter isolates sequenced to date (twenty different genera, we propose the correction of the assigned start codons of 1082 homologous genes in the clade. In addition, we also report the presence of novel genes within operons encoding determinants of the important tricarboxylic acid cycle, a feature that seems to be characteristic of some Roseobacter genomes. The detection of their corresponding products in large amounts raises the question of their function. Their discoveries point to a possible theory for protein evolution that will rely on high expression of orphans in bacteria: their putative poor efficiency could be counterbalanced by a higher level of expression. Our proteogenomic analysis will increase

  11. Cameras for Public Health Surveillance: A Methods Protocol for Crowdsourced Annotation of Point-of-Sale Photographs.

    Science.gov (United States)

    Ilakkuvan, Vinu; Tacelosky, Michael; Ivey, Keith C; Pearson, Jennifer L; Cantrell, Jennifer; Vallone, Donna M; Abrams, David B; Kirchner, Thomas R

    2014-04-09

    Photographs are an effective way to collect detailed and objective information about the environment, particularly for public health surveillance. However, accurately and reliably annotating (ie, extracting information from) photographs remains difficult, a critical bottleneck inhibiting the use of photographs for systematic surveillance. The advent of distributed human computation (ie, crowdsourcing) platforms represents a veritable breakthrough, making it possible for the first time to accurately, quickly, and repeatedly annotate photos at relatively low cost. This paper describes a methods protocol, using photographs from point-of-sale surveillance studies in the field of tobacco control to demonstrate the development and testing of custom-built tools that can greatly enhance the quality of crowdsourced annotation. Enhancing the quality of crowdsourced photo annotation requires a number of approaches and tools. The crowdsourced photo annotation process is greatly simplified by decomposing the overall process into smaller tasks, which improves accuracy and speed and enables adaptive processing, in which irrelevant data is filtered out and more difficult targets receive increased scrutiny. Additionally, zoom tools enable users to see details within photographs and crop tools highlight where within an image a specific object of interest is found, generating a set of photographs that answer specific questions. Beyond such tools, optimizing the number of raters (ie, crowd size) for accuracy and reliability is an important facet of crowdsourced photo annotation. This can be determined in a systematic manner based on the difficulty of the task and the desired level of accuracy, using receiver operating characteristic (ROC) analyses. Usability tests of the zoom and crop tool suggest that these tools significantly improve annotation accuracy. The tests asked raters to extract data from photographs, not for the purposes of assessing the quality of that data, but rather to

  12. Computerized comprehensive data analysis of Lung Imaging Database Consortium (LIDC)

    International Nuclear Information System (INIS)

    Tan Jun; Pu Jiantao; Zheng Bin; Wang Xingwei; Leader, Joseph K.

    2010-01-01

    Purpose: Lung Image Database Consortium (LIDC) is the largest public CT image database of lung nodules. In this study, the authors present a comprehensive and the most updated analysis of this dynamically growing database under the help of a computerized tool, aiming to assist researchers to optimally use this database for lung cancer related investigations. Methods: The authors developed a computer scheme to automatically match the nodule outlines marked manually by radiologists on CT images. A large variety of characteristics regarding the annotated nodules in the database including volume, spiculation level, elongation, interobserver variability, as well as the intersection of delineated nodule voxels and overlapping ratio between the same nodules marked by different radiologists are automatically calculated and summarized. The scheme was applied to analyze all 157 examinations with complete annotation data currently available in LIDC dataset. Results: The scheme summarizes the statistical distributions of the abovementioned geometric and diagnosis features. Among the 391 nodules, (1) 365 (93.35%) have principal axis length ≤20 mm; (2) 120, 75, 76, and 120 were marked by one, two, three, and four radiologists, respectively; and (3) 122 (32.48%) have the maximum volume overlapping ratios ≥80% for the delineations of two radiologists, while 198 (50.64%) have the maximum volume overlapping ratios <60%. The results also showed that 72.89% of the nodules were assessed with malignancy score between 2 and 4, and only 7.93% of these nodules were considered as severely malignant (malignancy ≥4). Conclusions: This study demonstrates that LIDC contains examinations covering a diverse distribution of nodule characteristics and it can be a useful resource to assess the performance of the nodule detection and/or segmentation schemes.

  13. MitoBamAnnotator: A web-based tool for detecting and annotating heteroplasmy in human mitochondrial DNA sequences.

    Science.gov (United States)

    Zhidkov, Ilia; Nagar, Tal; Mishmar, Dan; Rubin, Eitan

    2011-11-01

    The use of Next-Generation Sequencing of mitochondrial DNA is becoming widespread in biological and clinical research. This, in turn, creates a need for a convenient tool that detects and analyzes heteroplasmy. Here we present MitoBamAnnotator, a user friendly web-based tool that allows maximum flexibility and control in heteroplasmy research. MitoBamAnnotator provides the user with a comprehensively annotated overview of mitochondrial genetic variation, allowing for an in-depth analysis with no prior knowledge in programming. Copyright © 2011 Elsevier B.V. and Mitochondria Research Society. All rights reserved. All rights reserved.

  14. SeqHound: biological sequence and structure database as a platform for bioinformatics research

    Directory of Open Access Journals (Sweden)

    Dumontier Michel

    2002-10-01

    Full Text Available Abstract Background SeqHound has been developed as an integrated biological sequence, taxonomy, annotation and 3-D structure database system. It provides a high-performance server platform for bioinformatics research in a locally-hosted environment. Results SeqHound is based on the National Center for Biotechnology Information data model and programming tools. It offers daily updated contents of all Entrez sequence databases in addition to 3-D structural data and information about sequence redundancies, sequence neighbours, taxonomy, complete genomes, functional annotation including Gene Ontology terms and literature links to PubMed. SeqHound is accessible via a web server through a Perl, C or C++ remote API or an optimized local API. It provides functionality necessary to retrieve specialized subsets of sequences, structures and structural domains. Sequences may be retrieved in FASTA, GenBank, ASN.1 and XML formats. Structures are available in ASN.1, XML and PDB formats. Emphasis has been placed on complete genomes, taxonomy, domain and functional annotation as well as 3-D structural functionality in the API, while fielded text indexing functionality remains under development. SeqHound also offers a streamlined WWW interface for simple web-user queries. Conclusions The system has proven useful in several published bioinformatics projects such as the BIND database and offers a cost-effective infrastructure for research. SeqHound will continue to develop and be provided as a service of the Blueprint Initiative at the Samuel Lunenfeld Research Institute. The source code and examples are available under the terms of the GNU public license at the Sourceforge site http://sourceforge.net/projects/slritools/ in the SLRI Toolkit.

  15. Annotation of regular polysemy and underspecification

    DEFF Research Database (Denmark)

    Martínez Alonso, Héctor; Pedersen, Bolette Sandford; Bel, Núria

    2013-01-01

    We present the result of an annotation task on regular polysemy for a series of seman- tic classes or dot types in English, Dan- ish and Spanish. This article describes the annotation process, the results in terms of inter-encoder agreement, and the sense distributions obtained with two methods...

  16. Developmental gene discovery in a hemimetabolous insect: de novo assembly and annotation of a transcriptome for the cricket Gryllus bimaculatus.

    Directory of Open Access Journals (Sweden)

    Victor Zeng

    Full Text Available Most genomic resources available for insects represent the Holometabola, which are insects that undergo complete metamorphosis like beetles and flies. In contrast, the Hemimetabola (direct developing insects, representing the basal branches of the insect tree, have very few genomic resources. We have therefore created a large and publicly available transcriptome for the hemimetabolous insect Gryllus bimaculatus (cricket, a well-developed laboratory model organism whose potential for functional genetic experiments is currently limited by the absence of genomic resources. cDNA was prepared using mRNA obtained from adult ovaries containing all stages of oogenesis, and from embryo samples on each day of embryogenesis. Using 454 Titanium pyrosequencing, we sequenced over four million raw reads, and assembled them into 21,512 isotigs (predicted transcripts and 120,805 singletons with an average coverage per base pair of 51.3. We annotated the transcriptome manually for over 400 conserved genes involved in embryonic patterning, gametogenesis, and signaling pathways. BLAST comparison of the transcriptome against the NCBI non-redundant protein database (nr identified significant similarity to nr sequences for 55.5% of transcriptome sequences, and suggested that the transcriptome may contain 19,874 unique transcripts. For predicted transcripts without significant similarity to known sequences, we assessed their similarity to other orthopteran sequences, and determined that these transcripts contain recognizable protein domains, largely of unknown function. We created a searchable, web-based database to allow public access to all raw, assembled and annotated data. This database is to our knowledge the largest de novo assembled and annotated transcriptome resource available for any hemimetabolous insect. We therefore anticipate that these data will contribute significantly to more effective and higher-throughput deployment of molecular analysis tools in

  17. Rice DB: an Oryza Information Portal linking annotation, subcellular location, function, expression, regulation, and evolutionary information for rice and Arabidopsis.

    Science.gov (United States)

    Narsai, Reena; Devenish, James; Castleden, Ian; Narsai, Kabir; Xu, Lin; Shou, Huixia; Whelan, James

    2013-12-01

    Omics research in Oryza sativa (rice) relies on the use of multiple databases to obtain different types of information to define gene function. We present Rice DB, an Oryza information portal that is a functional genomics database, linking gene loci to comprehensive annotations, expression data and the subcellular location of encoded proteins. Rice DB has been designed to integrate the direct comparison of rice with Arabidopsis (Arabidopsis thaliana), based on orthology or 'expressology', thus using and combining available information from two pre-eminent plant models. To establish Rice DB, gene identifiers (more than 40 types) and annotations from a variety of sources were compiled, functional information based on large-scale and individual studies was manually collated, hundreds of microarrays were analysed to generate expression annotations, and the occurrences of potential functional regulatory motifs in promoter regions were calculated. A range of computational subcellular localization predictions were also run for all putative proteins encoded in the rice genome, and experimentally confirmed protein localizations have been collated, curated and linked to functional studies in rice. A single search box allows anything from gene identifiers (for rice and/or Arabidopsis), motif sequences, subcellular location, to keyword searches to be entered, with the capability of Boolean searches (such as AND/OR). To demonstrate the utility of Rice DB, several examples are presented including a rice mitochondrial proteome, which draws on a variety of sources for subcellular location data within Rice DB. Comparisons of subcellular location, functional annotations, as well as transcript expression in parallel with Arabidopsis reveals examples of conservation between rice and Arabidopsis, using Rice DB (http://ricedb.plantenergy.uwa.edu.au). © 2013 The Authors The Plant Journal © 2013 John Wiley & Sons Ltd.

  18. A semi-automatic annotation tool for cooking video

    Science.gov (United States)

    Bianco, Simone; Ciocca, Gianluigi; Napoletano, Paolo; Schettini, Raimondo; Margherita, Roberto; Marini, Gianluca; Gianforme, Giorgio; Pantaleo, Giuseppe

    2013-03-01

    In order to create a cooking assistant application to guide the users in the preparation of the dishes relevant to their profile diets and food preferences, it is necessary to accurately annotate the video recipes, identifying and tracking the foods of the cook. These videos present particular annotation challenges such as frequent occlusions, food appearance changes, etc. Manually annotate the videos is a time-consuming, tedious and error-prone task. Fully automatic tools that integrate computer vision algorithms to extract and identify the elements of interest are not error free, and false positive and false negative detections need to be corrected in a post-processing stage. We present an interactive, semi-automatic tool for the annotation of cooking videos that integrates computer vision techniques under the supervision of the user. The annotation accuracy is increased with respect to completely automatic tools and the human effort is reduced with respect to completely manual ones. The performance and usability of the proposed tool are evaluated on the basis of the time and effort required to annotate the same video sequences.

  19. ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

    Science.gov (United States)

    Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

    2008-08-12

    New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges

  20. Experiments with crowdsourced re-annotation of a POS tagging data set

    DEFF Research Database (Denmark)

    Hovy, Dirk; Plank, Barbara; Søgaard, Anders

    2014-01-01

    Crowdsourcing lets us collect multiple annotations for an item from several annotators. Typically, these are annotations for non-sequential classification tasks. While there has been some work on crowdsourcing named entity annotations, researchers have assumed that syntactic tasks such as part......-of-speech (POS) tagging cannot be crowdsourced. This paper shows that workers can actually annotate sequential data almost as well as experts. Further, we show that the models learned from crowdsourced annotations fare as well as the models learned from expert annotations in downstream tasks....

  1. MPEG-7 based video annotation and browsing

    Science.gov (United States)

    Hoeynck, Michael; Auweiler, Thorsten; Wellhausen, Jens

    2003-11-01

    The huge amount of multimedia data produced worldwide requires annotation in order to enable universal content access and to provide content-based search-and-retrieval functionalities. Since manual video annotation can be time consuming, automatic annotation systems are required. We review recent approaches to content-based indexing and annotation of videos for different kind of sports and describe our approach to automatic annotation of equestrian sports videos. We especially concentrate on MPEG-7 based feature extraction and content description, where we apply different visual descriptors for cut detection. Further, we extract the temporal positions of single obstacles on the course by analyzing MPEG-7 edge information. Having determined single shot positions as well as the visual highlights, the information is jointly stored with meta-textual information in an MPEG-7 description scheme. Based on this information, we generate content summaries which can be utilized in a user-interface in order to provide content-based access to the video stream, but further for media browsing on a streaming server.

  2. Structural and Functional Annotation of Hypothetical Proteins of O139

    Directory of Open Access Journals (Sweden)

    Md. Saiful Islam

    2015-06-01

    Full Text Available In developing countries threat of cholera is a significant health concern whenever water purification and sewage disposal systems are inadequate. Vibrio cholerae is one of the responsible bacteria involved in cholera disease. The complete genome sequence of V. cholerae deciphers the presence of various genes and hypothetical proteins whose function are not yet understood. Hence analyzing and annotating the structure and function of hypothetical proteins is important for understanding the V. cholerae. V. cholerae O139 is the most common and pathogenic bacterial strain among various V. cholerae strains. In this study sequence of six hypothetical proteins of V. cholerae O139 has been annotated from NCBI. Various computational tools and databases have been used to determine domain family, protein-protein interaction, solubility of protein, ligand binding sites etc. The three dimensional structure of two proteins were modeled and their ligand binding sites were identified. We have found domains and families of only one protein. The analysis revealed that these proteins might have antibiotic resistance activity, DNA breaking-rejoining activity, integrase enzyme activity, restriction endonuclease, etc. Structural prediction of these proteins and detection of binding sites from this study would indicate a potential target aiding docking studies for therapeutic designing against cholera.

  3. Training nuclei detection algorithms with simple annotations

    Directory of Open Access Journals (Sweden)

    Henning Kost

    2017-01-01

    Full Text Available Background: Generating good training datasets is essential for machine learning-based nuclei detection methods. However, creating exhaustive nuclei contour annotations, to derive optimal training data from, is often infeasible. Methods: We compared different approaches for training nuclei detection methods solely based on nucleus center markers. Such markers contain less accurate information, especially with regard to nuclear boundaries, but can be produced much easier and in greater quantities. The approaches use different automated sample extraction methods to derive image positions and class labels from nucleus center markers. In addition, the approaches use different automated sample selection methods to improve the detection quality of the classification algorithm and reduce the run time of the training process. We evaluated the approaches based on a previously published generic nuclei detection algorithm and a set of Ki-67-stained breast cancer images. Results: A Voronoi tessellation-based sample extraction method produced the best performing training sets. However, subsampling of the extracted training samples was crucial. Even simple class balancing improved the detection quality considerably. The incorporation of active learning led to a further increase in detection quality. Conclusions: With appropriate sample extraction and selection methods, nuclei detection algorithms trained on the basis of simple center marker annotations can produce comparable quality to algorithms trained on conventionally created training sets.

  4. Ground Truth Annotation in T Analyst

    DEFF Research Database (Denmark)

    2015-01-01

    This video shows how to annotate the ground truth tracks in the thermal videos. The ground truth tracks are produced to be able to compare them to tracks obtained from a Computer Vision tracking approach. The program used for annotation is T-Analyst, which is developed by Aliaksei Laureshyn, Ph...

  5. BioWarehouse: a bioinformatics database warehouse toolkit.

    Science.gov (United States)

    Lee, Thomas J; Pouliot, Yannick; Wagner, Valerie; Gupta, Priyanka; Stringer-Calvert, David W J; Tenenbaum, Jessica D; Karp, Peter D

    2006-03-23

    This article addresses the problem of interoperation of heterogeneous bioinformatics databases. We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. BioWarehouse embodies significant progress on the database integration problem for bioinformatics.

  6. Gene calling and bacterial genome annotation with BG7.

    Science.gov (United States)

    Tobes, Raquel; Pareja-Tobes, Pablo; Manrique, Marina; Pareja-Tobes, Eduardo; Kovach, Evdokim; Alekhin, Alexey; Pareja, Eduardo

    2015-01-01

    New massive sequencing technologies are providing many bacterial genome sequences from diverse taxa but a refined annotation of these genomes is crucial for obtaining scientific findings and new knowledge. Thus, bacterial genome annotation has emerged as a key point to investigate in bacteria. Any efficient tool designed specifically to annotate bacterial genomes sequenced with massively parallel technologies has to consider the specific features of bacterial genomes (absence of introns and scarcity of nonprotein-coding sequence) and of next-generation sequencing (NGS) technologies (presence of errors and not perfectly assembled genomes). These features make it convenient to focus on coding regions and, hence, on protein sequences that are the elements directly related with biological functions. In this chapter we describe how to annotate bacterial genomes with BG7, an open-source tool based on a protein-centered gene calling/annotation paradigm. BG7 is specifically designed for the annotation of bacterial genomes sequenced with NGS. This tool is sequence error tolerant maintaining their capabilities for the annotation of highly fragmented genomes or for annotating mixed sequences coming from several genomes (as those obtained through metagenomics samples). BG7 has been designed with scalability as a requirement, with a computing infrastructure completely based on cloud computing (Amazon Web Services).

  7. PATRIC, the bacterial bioinformatics database and analysis resource.

    Science.gov (United States)

    Wattam, Alice R; Abraham, David; Dalay, Oral; Disz, Terry L; Driscoll, Timothy; Gabbard, Joseph L; Gillespie, Joseph J; Gough, Roger; Hix, Deborah; Kenyon, Ronald; Machi, Dustin; Mao, Chunhong; Nordberg, Eric K; Olson, Robert; Overbeek, Ross; Pusch, Gordon D; Shukla, Maulik; Schulman, Julie; Stevens, Rick L; Sullivan, Daniel E; Vonstein, Veronika; Warren, Andrew; Will, Rebecca; Wilson, Meredith J C; Yoo, Hyun Seung; Zhang, Chengdong; Zhang, Yan; Sobral, Bruno W

    2014-01-01

    The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10,000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issue.

  8. Annotation of the Evaluative Language in a Dependency Treebank

    Directory of Open Access Journals (Sweden)

    Šindlerová Jana

    2017-12-01

    Full Text Available In the paper, we present our efforts to annotate evaluative language in the Prague Dependency Treebank 2.0. The project is a follow-up of the series of annotations of small plaintext corpora. It uses automatic identification of potentially evaluative nodes through mapping a Czech subjectivity lexicon to syntactically annotated data. These nodes are then manually checked by an annotator and either dismissed as standing in a non-evaluative context, or confirmed as evaluative. In the latter case, information about the polarity orientation, the source and target of evaluation is added by the annotator. The annotations unveiled several advantages and disadvantages of the chosen framework. The advantages involve more structured and easy-to-handle environment for the annotator, visibility of syntactic patterning of the evaluative state, effective solving of discontinuous structures or a new perspective on the influence of good/bad news. The disadvantages include little capability of treating cases with evaluation spread among more syntactically connected nodes at once, little capability of treating metaphorical expressions, or disregarding the effects of negation and intensification in the current scheme.

  9. Image annotation by deep neural networks with attention shaping

    Science.gov (United States)

    Zheng, Kexin; Lv, Shaohe; Ma, Fang; Chen, Fei; Jin, Chi; Dou, Yong

    2017-07-01

    Image annotation is a task of assigning semantic labels to an image. Recently, deep neural networks with visual attention have been utilized successfully in many computer vision tasks. In this paper, we show that conventional attention mechanism is easily misled by the salient class, i.e., the attended region always contains part of the image area describing the content of salient class at different attention iterations. To this end, we propose a novel attention shaping mechanism, which aims to maximize the non-overlapping area between consecutive attention processes by taking into account the history of previous attention vectors. Several weighting polices are studied to utilize the history information in different manners. In two benchmark datasets, i.e., PASCAL VOC2012 and MIRFlickr-25k, the average precision is improved by up to 10% in comparison with the state-of-the-art annotation methods.

  10. An application of a relational database system for high-throughput prediction of elemental compositions from accurate mass values.

    Science.gov (United States)

    Sakurai, Nozomu; Ara, Takeshi; Kanaya, Shigehiko; Nakamura, Yukiko; Iijima, Yoko; Enomoto, Mitsuo; Motegi, Takeshi; Aoki, Koh; Suzuki, Hideyuki; Shibata, Daisuke

    2013-01-15

    High-accuracy mass values detected by high-resolution mass spectrometry analysis enable prediction of elemental compositions, and thus are used for metabolite annotations in metabolomic studies. Here, we report an application of a relational database to significantly improve the rate of elemental composition predictions. By searching a database of pre-calculated elemental compositions with fixed kinds and numbers of atoms, the approach eliminates redundant evaluations of the same formula that occur in repeated calculations with other tools. When our approach is compared with HR2, which is one of the fastest tools available, our database search times were at least 109 times shorter than those of HR2. When a solid-state drive (SSD) was applied, the search time was 488 times shorter at 5 ppm mass tolerance and 1833 times at 0.1 ppm. Even if the search by HR2 was performed with 8 threads in a high-spec Windows 7 PC, the database search times were at least 26 and 115 times shorter without and with the SSD. These improvements were enhanced in a low spec Windows XP PC. We constructed a web service 'MFSearcher' to query the database in a RESTful manner. Available for free at http://webs2.kazusa.or.jp/mfsearcher. The web service is implemented in Java, MySQL, Apache and Tomcat, with all major browsers supported. sakurai@kazusa.or.jp Supplementary data are available at Bioinformatics online.

  11. Optimization of de novo transcriptome assembly from high-throughput short read sequencing data improves functional annotation for non-model organisms

    Directory of Open Access Journals (Sweden)

    Haznedaroglu Berat Z

    2012-07-01

    Full Text Available Abstract Background The k-mer hash length is a key factor affecting the output of de novo transcriptome assembly packages using de Bruijn graph algorithms. Assemblies constructed with varying single k-mer choices might result in the loss of unique contiguous sequences (contigs and relevant biological information. A common solution to this problem is the clustering of single k-mer assemblies. Even though annotation is one of the primary goals of a transcriptome assembly, the success of assembly strategies does not consider the impact of k-mer selection on the annotation output. This study provides an in-depth k-mer selection analysis that is focused on the degree of functional annotation achieved for a non-model organism where no reference genome information is available. Individual k-mers and clustered assemblies (CA were considered using three representative software packages. Pair-wise comparison analyses (between individual k-mers and CAs were produced to reveal missing Kyoto Encyclopedia of Genes and Genomes (KEGG ortholog identifiers (KOIs, and to determine a strategy that maximizes the recovery of biological information in a de novo transcriptome assembly. Results Analyses of single k-mer assemblies resulted in the generation of various quantities of contigs and functional annotations within the selection window of k-mers (k-19 to k-63. For each k-mer in this window, generated assemblies contained certain unique contigs and KOIs that were not present in the other k-mer assemblies. Producing a non-redundant CA of k-mers 19 to 63 resulted in a more complete functional annotation than any single k-mer assembly. However, a fraction of unique annotations remained (~0.19 to 0.27% of total KOIs in the assemblies of individual k-mers (k-19 to k-63 that were not present in the non-redundant CA. A workflow to recover these unique annotations is presented. Conclusions This study demonstrated that different k-mer choices result in various quantities

  12. The caBIG annotation and image Markup project.

    Science.gov (United States)

    Channin, David S; Mongkolwat, Pattanasak; Kleper, Vladimir; Sepukar, Kastubh; Rubin, Daniel L

    2010-04-01

    Image annotation and markup are at the core of medical interpretation in both the clinical and the research setting. Digital medical images are managed with the DICOM standard format. While DICOM contains a large amount of meta-data about whom, where, and how the image was acquired, DICOM says little about the content or meaning of the pixel data. An image annotation is the explanatory or descriptive information about the pixel data of an image that is generated by a human or machine observer. An image markup is the graphical symbols placed over the image to depict an annotation. While DICOM is the standard for medical image acquisition, manipulation, transmission, storage, and display, there are no standards for image annotation and markup. Many systems expect annotation to be reported verbally, while markups are stored in graphical overlays or proprietary formats. This makes it difficult to extract and compute with both of them. The goal of the Annotation and Image Markup (AIM) project is to develop a mechanism, for modeling, capturing, and serializing image annotation and markup data that can be adopted as a standard by the medical imaging community. The AIM project produces both human- and machine-readable artifacts. This paper describes the AIM information model, schemas, software libraries, and tools so as to prepare researchers and developers for their use of AIM.

  13. Interoperable Multimedia Annotation and Retrieval for the Tourism Sector

    NARCIS (Netherlands)

    Chatzitoulousis, Antonios; Efraimidis, Pavlos S.; Athanasiadis, I.N.

    2015-01-01

    The Atlas Metadata System (AMS) employs semantic web annotation techniques in order to create an interoperable information annotation and retrieval platform for the tourism sector. AMS adopts state-of-the-art metadata vocabularies, annotation techniques and semantic web technologies.

  14. Coreference annotation and resolution in the Colorado Richly Annotated Full Text (CRAFT) corpus of biomedical journal articles.

    Science.gov (United States)

    Cohen, K Bretonnel; Lanfranchi, Arrick; Choi, Miji Joo-Young; Bada, Michael; Baumgartner, William A; Panteleyeva, Natalya; Verspoor, Karin; Palmer, Martha; Hunter, Lawrence E

    2017-08-17

    Coreference resolution is the task of finding strings in text that have the same referent as other strings. Failures of coreference resolution are a common cause of false negatives in information extraction from the scientific literature. In order to better understand the nature of the phenomenon of coreference in biomedical publications and to increase performance on the task, we annotated the Colorado Richly Annotated Full Text (CRAFT) corpus with coreference relations. The corpus was manually annotated with coreference relations, including identity and appositives for all coreferring base noun phrases. The OntoNotes annotation guidelines, with minor adaptations, were used. Interannotator agreement ranges from 0.480 (entity-based CEAF) to 0.858 (Class-B3), depending on the metric that is used to assess it. The resulting corpus adds nearly 30,000 annotations to the previous release of the CRAFT corpus. Differences from related projects include a much broader definition of markables, connection to extensive annotation of several domain-relevant semantic classes, and connection to complete syntactic annotation. Tool performance was benchmarked on the data. A publicly available out-of-the-box, general-domain coreference resolution system achieved an F-measure of 0.14 (B3), while a simple domain-adapted rule-based system achieved an F-measure of 0.42. An ensemble of the two reached F of 0.46. Following the IDENTITY chains in the data would add 106,263 additional named entities in the full 97-paper corpus, for an increase of 76% percent in the semantic classes of the eight ontologies that have been annotated in earlier versions of the CRAFT corpus. The project produced a large data set for further investigation of coreference and coreference resolution in the scientific literature. The work raised issues in the phenomenon of reference in this domain and genre, and the paper proposes that many mentions that would be considered generic in the general domain are not

  15. A Novel Approach to Semantic and Coreference Annotation at LLNL

    Energy Technology Data Exchange (ETDEWEB)

    Firpo, M

    2005-02-04

    A case is made for the importance of high quality semantic and coreference annotation. The challenges of providing such annotation are described. Asperger's Syndrome is introduced, and the connections are drawn between the needs of text annotation and the abilities of persons with Asperger's Syndrome to meet those needs. Finally, a pilot program is recommended wherein semantic annotation is performed by people with Asperger's Syndrome. The primary points embodied in this paper are as follows: (1) Document annotation is essential to the Natural Language Processing (NLP) projects at Lawrence Livermore National Laboratory (LLNL); (2) LLNL does not currently have a system in place to meet its need for text annotation; (3) Text annotation is challenging for a variety of reasons, many related to its very rote nature; (4) Persons with Asperger's Syndrome are particularly skilled at rote verbal tasks, and behavioral experts agree that they would excel at text annotation; and (6) A pilot study is recommend in which two to three people with Asperger's Syndrome annotate documents and then the quality and throughput of their work is evaluated relative to that of their neuro-typical peers.

  16. An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave

    Directory of Open Access Journals (Sweden)

    Ikaro Silva

    2014-09-01

    Full Text Available The WaveForm DataBase (WFDB Toolbox for MATLAB/Octave enables  integrated access to PhysioNet's software and databases. Using the WFDB Toolbox for MATLAB/Octave, users have access to over 50 physiological databases in PhysioNet. The toolbox allows direct loading into MATLAB/Octave's workspace of over 4 TB of biomedical signals including ECG, EEG, EMG, and PLETH. Additionally, most signals are accompanied by meta data such as medical annotations of clinical events: arrhythmias, sleep stages, seizures, hypotensive episodes, etc. Users of this toolbox should easily be able to reproduce, validate, and compare results published based on PhysioNet's software and databases.

  17. xHMMER3x2: Utilizing HMMER3's speed and HMMER2's sensitivity and specificity in the glocal alignment mode for improved large-scale protein domain annotation.

    Science.gov (United States)

    Yap, Choon-Kong; Eisenhaber, Birgit; Eisenhaber, Frank; Wong, Wing-Cheong

    2016-11-29

    While the local-mode HMMER3 is notable for its massive speed improvement, the slower glocal-mode HMMER2 is more exact for domain annotation by enforcing full domain-to-sequence alignments. Since a unit of domain necessarily implies a unit of function, local-mode HMMER3 alone remains insufficient for precise function annotation tasks. In addition, the incomparable E-values for the same domain model by different HMMER builds create difficulty when checking for domain annotation consistency on a large-scale basis. In this work, both the speed of HMMER3 and glocal-mode alignment of HMMER2 are combined within the xHMMER3x2 framework for tackling the large-scale domain annotation task. Briefly, HMMER3 is utilized for initial domain detection so that HMMER2 can subsequently perform the glocal-mode, sequence-to-full-domain alignments for the detected HMMER3 hits. An E-value calibration procedure is required to ensure that the search space by HMMER2 is sufficiently replicated by HMMER3. We find that the latter is straightforwardly possible for ~80% of the models in the Pfam domain library (release 29). However in the case of the remaining ~20% of HMMER3 domain models, the respective HMMER2 counterparts are more sensitive. Thus, HMMER3 searches alone are insufficient to ensure sensitivity and a HMMER2-based search needs to be initiated. When tested on the set of UniProt human sequences, xHMMER3x2 can be configured to be between 7× and 201× faster than HMMER2, but with descending domain detection sensitivity from 99.8 to 95.7% with respect to HMMER2 alone; HMMER3's sensitivity was 95.7%. At extremes, xHMMER3x2 is either the slow glocal-mode HMMER2 or the fast HMMER3 with glocal-mode. Finally, the E-values to false-positive rates (FPR) mapping by xHMMER3x2 allows E-values of different model builds to be compared, so that any annotation discrepancies in a large-scale annotation exercise can be flagged for further examination by dissectHMMER. The xHMMER3x2 workflow allows

  18. HRGFish: A database of hypoxia responsive genes in fishes

    Science.gov (United States)

    Rashid, Iliyas; Nagpure, Naresh Sahebrao; Srivastava, Prachi; Kumar, Ravindra; Pathak, Ajey Kumar; Singh, Mahender; Kushwaha, Basdeo

    2017-02-01

    Several studies have highlighted the changes in the gene expression due to the hypoxia response in fishes, but the systematic organization of the information and the analytical platform for such genes are lacking. In the present study, an attempt was made to develop a database of hypoxia responsive genes in fishes (HRGFish), integrated with analytical tools, using LAMPP technology. Genes reported in hypoxia response for fishes were compiled through literature survey and the database presently covers 818 gene sequences and 35 gene types from 38 fishes. The upstream fragments (3,000 bp), covered in this database, enables to compute CG dinucleotides frequencies, motif finding of the hypoxia response element, identification of CpG island and mapping with the reference promoter of zebrafish. The database also includes functional annotation of genes and provides tools for analyzing sequences and designing primers for selected gene fragments. This may be the first database on the hypoxia response genes in fishes that provides a workbench to the scientific community involved in studying the evolution and ecological adaptation of the fish species in relation to hypoxia.

  19. YMDB: the Yeast Metabolome Database

    Science.gov (United States)

    Jewison, Timothy; Knox, Craig; Neveu, Vanessa; Djoumbou, Yannick; Guo, An Chi; Lee, Jacqueline; Liu, Philip; Mandal, Rupasri; Krishnamurthy, Ram; Sinelnikov, Igor; Wilson, Michael; Wishart, David S.

    2012-01-01

    The Yeast Metabolome Database (YMDB, http://www.ymdb.ca) is a richly annotated ‘metabolomic’ database containing detailed information about the metabolome of Saccharomyces cerevisiae. Modeled closely after the Human Metabolome Database, the YMDB contains >2000 metabolites with links to 995 different genes/proteins, including enzymes and transporters. The information in YMDB has been gathered from hundreds of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the YMDB also contains an extensive collection of experimental intracellular and extracellular metabolite concentration data compiled from detailed Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR) metabolomic analyses performed in our lab. This is further supplemented with thousands of NMR and MS spectra collected on pure, reference yeast metabolites. Each metabolite entry in the YMDB contains an average of 80 separate data fields including comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, intracellular/extracellular concentrations, growth conditions and substrates, pathway information, enzyme data, gene/protein sequence data, as well as numerous hyperlinks to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided that support text, chemical structure, spectral, molecular weight and gene/protein sequence queries. Because of S. cervesiae's importance as a model organism for biologists and as a biofactory for industry, we believe this kind of database could have considerable appeal not only to metabolomics researchers, but also to yeast biologists, systems biologists, the industrial fermentation industry, as well as the beer, wine and spirit industry. PMID:22064855

  20. Visual Interpretation with Three-Dimensional Annotations (VITA): three-dimensional image interpretation tool for radiological reporting.

    Science.gov (United States)

    Roy, Sharmili; Brown, Michael S; Shih, George L

    2014-02-01

    This paper introduces a software framework called Visual Interpretation with Three-Dimensional Annotations (VITA) that is able to automatically generate three-dimensional (3D) visual summaries based on radiological annotations made during routine exam reporting. VITA summaries are in the form of rotating 3D volumes where radiological annotations are highlighted to place important clinical observations into a 3D context. The rendered volume is produced as a Digital Imaging and Communications in Medicine (DICOM) object and is automatically added to the study for archival in Picture Archiving and Communication System (PACS). In addition, a video summary (e.g., MPEG4) can be generated for sharing with patients and for situations where DICOM viewers are not readily available to referring physicians. The current version of VITA is compatible with ClearCanvas; however, VITA can work with any PACS workstation that has a structured annotation implementation (e.g., Extendible Markup Language, Health Level 7, Annotation and Image Markup) and is able to seamlessly integrate into the existing reporting workflow. In a survey with referring physicians, the vast majority strongly agreed that 3D visual summaries improve the communication of the radiologists' reports and aid communication with patients.

  1. Generation of silver standard concept annotations from biomedical texts with special relevance to phenotypes.

    Science.gov (United States)

    Oellrich, Anika; Collier, Nigel; Smedley, Damian; Groza, Tudor

    2015-01-01

    Electronic health records and scientific articles possess differing linguistic characteristics that may impact the performance of natural language processing tools developed for one or the other. In this paper, we investigate the performance of four extant concept recognition tools: the clinical Text Analysis and Knowledge Extraction System (cTAKES), the National Center for Biomedical Ontology (NCBO) Annotator, the Biomedical Concept Annotation System (BeCAS) and MetaMap. Each of the four concept recognition systems is applied to four different corpora: the i2b2 corpus of clinical documents, a PubMed corpus of Medline abstracts, a clinical trails corpus and the ShARe/CLEF corpus. In addition, we assess the individual system performances with respect to one gold standard annotation set, available for the ShARe/CLEF corpus. Furthermore, we built a silver standard annotation set from the individual systems' output and assess the quality as well as the contribution of individual systems to the quality of the silver standard. Our results demonstrate that mainly the NCBO annotator and cTAKES contribute to the silver standard corpora (F1-measures in the range of 21% to 74%) and their quality (best F1-measure of 33%), independent from the type of text investigated. While BeCAS and MetaMap can contribute to the precision of silver standard annotations (precision of up to 42%), the F1-measure drops when combined with NCBO Annotator and cTAKES due to a low recall. In conclusion, the performances of individual systems need to be improved independently from the text types, and the leveraging strategies to best take advantage of individual systems' annotations need to be revised. The textual content of the PubMed corpus, accession numbers for the clinical trials corpus, and assigned annotations of the four concept recognition systems as well as the generated silver standard annotation sets are available from http://purl.org/phenotype/resources. The textual content of the Sh

  2. Generation of silver standard concept annotations from biomedical texts with special relevance to phenotypes.

    Directory of Open Access Journals (Sweden)

    Anika Oellrich

    Full Text Available Electronic health records and scientific articles possess differing linguistic characteristics that may impact the performance of natural language processing tools developed for one or the other. In this paper, we investigate the performance of four extant concept recognition tools: the clinical Text Analysis and Knowledge Extraction System (cTAKES, the National Center for Biomedical Ontology (NCBO Annotator, the Biomedical Concept Annotation System (BeCAS and MetaMap. Each of the four concept recognition systems is applied to four different corpora: the i2b2 corpus of clinical documents, a PubMed corpus of Medline abstracts, a clinical trails corpus and the ShARe/CLEF corpus. In addition, we assess the individual system performances with respect to one gold standard annotation set, available for the ShARe/CLEF corpus. Furthermore, we built a silver standard annotation set from the individual systems' output and assess the quality as well as the contribution of individual systems to the quality of the silver standard. Our results demonstrate that mainly the NCBO annotator and cTAKES contribute to the silver standard corpora (F1-measures in the range of 21% to 74% and their quality (best F1-measure of 33%, independent from the type of text investigated. While BeCAS and MetaMap can contribute to the precision of silver standard annotations (precision of up to 42%, the F1-measure drops when combined with NCBO Annotator and cTAKES due to a low recall. In conclusion, the performances of individual systems need to be improved independently from the text types, and the leveraging strategies to best take advantage of individual systems' annotations need to be revised. The textual content of the PubMed corpus, accession numbers for the clinical trials corpus, and assigned annotations of the four concept recognition systems as well as the generated silver standard annotation sets are available from http://purl.org/phenotype/resources. The textual content

  3. Candidate gene database and transcript map for peach, a model species for fruit trees.

    Science.gov (United States)

    Horn, Renate; Lecouls, Anne-Claire; Callahan, Ann; Dandekar, Abhaya; Garay, Lilibeth; McCord, Per; Howad, Werner; Chan, Helen; Verde, Ignazio; Main, Doreen; Jung, Sook; Georgi, Laura; Forrest, Sam; Mook, Jennifer; Zhebentyayeva, Tatyana; Yu, Yeisoo; Kim, Hye Ran; Jesudurai, Christopher; Sosinski, Bryon; Arús, Pere; Baird, Vance; Parfitt, Dan; Reighard, Gregory; Scorza, Ralph; Tomkins, Jeffrey; Wing, Rod; Abbott, Albert Glenn

    2005-05-01

    Peach (Prunus persica) is a model species for the Rosaceae, which includes a number of economically important fruit tree species. To develop an extensive Prunus expressed sequence tag (EST) database for identifying and cloning the genes important to fruit and tree development, we generated 9,984 high-quality ESTs from a peach cDNA library of developing fruit mesocarp. After assembly and annotation, a putative peach unigene set consisting of 3,842 ESTs was defined. Gene ontology (GO) classification was assigned based on the annotation of the single "best hit" match against the Swiss-Prot database. No significant homology could be found in the GenBank nr databases for 24.3% of the sequences. Using core markers from the general Prunus genetic map, we anchored bacterial artificial chromosome (BAC) clones on the genetic map, thereby providing a framework for the construction of a physical and transcript map. A transcript map was developed by hybridizing 1,236 ESTs from the putative peach unigene set and an additional 68 peach cDNA clones against the peach BAC library. Hybridizing ESTs to genetically anchored BACs immediately localized 11.2% of the ESTs on the genetic map. ESTs showed a clustering of expressed genes in defined regions of the linkage groups. [The data were built into a regularly updated Genome Database for Rosaceae (GDR), available at (http://www.genome.clemson.edu/gdr/).].

  4. Evidence-based gene models for structural and functional annotations of the oil palm genome.

    Science.gov (United States)

    Chan, Kuang-Lim; Tatarinova, Tatiana V; Rosli, Rozana; Amiruddin, Nadzirah; Azizi, Norazah; Halim, Mohd Amin Ab; Sanusi, Nik Shazana Nik Mohd; Jayanthi, Nagappan; Ponomarenko, Petr; Triska, Martin; Solovyev, Victor; Firdaus-Raih, Mohd; Sambanthamurthi, Ravigadevi; Murphy, Denis; Low, Eng-Ti Leslie

    2017-09-08

    Oil palm is an important source of edible oil. The importance of the crop, as well as its long breeding cycle (10-12 years) has led to the sequencing of its genome in 2013 to pave the way for genomics-guided breeding. Nevertheless, the first set of gene predictions, although useful, had many fragmented genes. Classification and characterization of genes associated with traits of interest, such as those for fatty acid biosynthesis and disease resistance, were also limited. Lipid-, especially fatty acid (FA)-related genes are of particular interest for the oil palm as they specify oil yields and quality. This paper presents the characterization of the oil palm genome using different gene prediction methods and comparative genomics analysis, identification of FA biosynthesis and disease resistance genes, and the development of an annotation database and bioinformatics tools. Using two independent gene-prediction pipelines, Fgenesh++ and Seqping, 26,059 oil palm genes with transcriptome and RefSeq support were identified from the oil palm genome. These coding regions of the genome have a characteristic broad distribution of GC 3 (fraction of cytosine and guanine in the third position of a codon) with over half the GC 3 -rich genes (GC 3  ≥ 0.75286) being intronless. In comparison, only one-seventh of the oil palm genes identified are intronless. Using comparative genomics analysis, characterization of conserved domains and active sites, and expression analysis, 42 key genes involved in FA biosynthesis in oil palm were identified. For three of them, namely EgFABF, EgFABH and EgFAD3, segmental duplication events were detected. Our analysis also identified 210 candidate resistance genes in six classes, grouped by their protein domain structures. We present an accurate and comprehensive annotation of the oil palm genome, focusing on analysis of important categories of genes (GC 3 -rich and intronless), as well as those associated with important functions, such as FA

  5. Combined evidence annotation of transposable elements in genome sequences.

    Directory of Open Access Journals (Sweden)

    Hadi Quesneville

    2005-07-01

    Full Text Available Transposable elements (TEs are mobile, repetitive sequences that make up significant fractions of metazoan genomes. Despite their near ubiquity and importance in genome and chromosome biology, most efforts to annotate TEs in genome sequences rely on the results of a single computational program, RepeatMasker. In contrast, recent advances in gene annotation indicate that high-quality gene models can be produced from combining multiple independent sources of computational evidence. To elevate the quality of TE annotations to a level comparable to that of gene models, we have developed a combined evidence-model TE annotation pipeline, analogous to systems used for gene annotation, by integrating results from multiple homology-based and de novo TE identification methods. As proof of principle, we have annotated "TE models" in Drosophila melanogaster Release 4 genomic sequences using the combined computational evidence derived from RepeatMasker, BLASTER, TBLASTX, all-by-all BLASTN, RECON, TE-HMM and the previous Release 3.1 annotation. Our system is designed for use with the Apollo genome annotation tool, allowing automatic results to be curated manually to produce reliable annotations. The euchromatic TE fraction of D. melanogaster is now estimated at 5.3% (cf. 3.86% in Release 3.1, and we found a substantially higher number of TEs (n = 6,013 than previously identified (n = 1,572. Most of the new TEs derive from small fragments of a few hundred nucleotides long and highly abundant families not previously annotated (e.g., INE-1. We also estimated that 518 TE copies (8.6% are inserted into at least one other TE, forming a nest of elements. The pipeline allows rapid and thorough annotation of even the most complex TE models, including highly deleted and/or nested elements such as those often found in heterochromatic sequences. Our pipeline can be easily adapted to other genome sequences, such as those of the D. melanogaster heterochromatin or other

  6. Crowdsourcing RNA structural alignments with an online computer game.

    Science.gov (United States)

    Waldispühl, Jérôme; Kam, Arthur; Gardner, Paul P

    2015-01-01

    The annotation and classification of ncRNAs is essential to decipher molecular mechanisms of gene regulation in normal and disease states. A database such as Rfam maintains alignments, consensus secondary structures, and corresponding annotations for RNA families. Its primary purpose is the automated, accurate annotation of non-coding RNAs in genomic sequences. However, the alignment of RNAs is computationally challenging, and the data stored in this database are often subject to improvements. Here, we design and evaluate Ribo, a human-computing game that aims to improve the accuracy of RNA alignments already stored in Rfam. We demonstrate the potential of our techniques and discuss the feasibility of large scale collaborative annotation and classification of RNA families.

  7. Semantator: annotating clinical narratives with semantic web ontologies.

    Science.gov (United States)

    Song, Dezhao; Chute, Christopher G; Tao, Cui

    2012-01-01

    To facilitate clinical research, clinical data needs to be stored in a machine processable and understandable way. Manual annotating clinical data is time consuming. Automatic approaches (e.g., Natural Language Processing systems) have been adopted to convert such data into structured formats; however, the quality of such automatically extracted data may not always be satisfying. In this paper, we propose Semantator, a semi-automatic tool for document annotation with Semantic Web ontologies. With a loaded free text document and an ontology, Semantator supports the creation/deletion of ontology instances for any document fragment, linking/disconnecting instances with the properties in the ontology, and also enables automatic annotation by connecting to the NCBO annotator and cTAKES. By representing annotations in Semantic Web standards, Semantator supports reasoning based upon the underlying semantics of the owl:disjointWith and owl:equivalentClass predicates. We present discussions based on user experiences of using Semantator.

  8. BrEPS: a flexible and automatic protocol to compute enzyme-specific sequence profiles for functional annotation

    Directory of Open Access Journals (Sweden)

    Schomburg D

    2010-12-01

    Full Text Available Abstract Background Models for the simulation of metabolic networks require the accurate prediction of enzyme function. Based on a genomic sequence, enzymatic functions of gene products are today mainly predicted by sequence database searching and operon analysis. Other methods can support these techniques: We have developed an automatic method "BrEPS" that creates highly specific sequence patterns for the functional annotation of enzymes. Results The enzymes in the UniprotKB are identified and their sequences compared against each other with BLAST. The enzymes are then clustered into a number of trees, where each tree node is associated with a set of EC-numbers. The enzyme sequences in the tree nodes are aligned with ClustalW. The conserved columns of the resulting multiple alignments are used to construct sequence patterns. In the last step, we verify the quality of the patterns by computing their specificity. Patterns with low specificity are omitted and recomputed further down in the tree. The final high-quality patterns can be used for functional annotation. We ran our protocol on a recent Swiss-Prot release and show statistics, as well as a comparison to PRIAM, a probabilistic method that is also specialized on the functional annotation of enzymes. We determine the amount of true positive annotations for five common microorganisms with data from BRENDA and AMENDA serving as standard of truth. BrEPS is almost on par with PRIAM, a fact which we discuss in the context of five manually investigated cases. Conclusions Our protocol computes highly specific sequence patterns that can be used to support the functional annotation of enzymes. The main advantages of our method are that it is automatic and unsupervised, and quite fast once the patterns are evaluated. The results show that BrEPS can be a valuable addition to the reconstruction of metabolic networks.

  9. RNA-seq analysis of Quercus pubescens Leaves: de novo transcriptome assembly, annotation and functional markers development.

    Directory of Open Access Journals (Sweden)

    Sara Torre

    Full Text Available Quercus pubescens Willd., a species distributed from Spain to southwest Asia, ranks high for drought tolerance among European oaks. Q. pubescens performs a role of outstanding significance in most Mediterranean forest ecosystems, but few mechanistic studies have been conducted to explore its response to environmental constrains, due to the lack of genomic resources. In our study, we performed a deep transcriptomic sequencing in Q. pubescens leaves, including de novo assembly, functional annotation and the identification of new molecular markers. Our results are a pre-requisite for undertaking molecular functional studies, and may give support in population and association genetic studies. 254,265,700 clean reads were generated by the Illumina HiSeq 2000 platform, with an average length of 98 bp. De novo assembly, using CLC Genomics, produced 96,006 contigs, having a mean length of 618 bp. Sequence similarity analyses against seven public databases (Uniprot, NR, RefSeq and KOGs at NCBI, Pfam, InterPro and KEGG resulted in 83,065 transcripts annotated with gene descriptions, conserved protein domains, or gene ontology terms. These annotations and local BLAST allowed identify genes specifically associated with mechanisms of drought avoidance. Finally, 14,202 microsatellite markers and 18,425 single nucleotide polymorphisms (SNPs were, in silico, discovered in assembled and annotated sequences. We completed a successful global analysis of the Q. pubescens leaf transcriptome using RNA-seq. The assembled and annotated sequences together with newly discovered molecular markers provide genomic information for functional genomic studies in Q. pubescens, with special emphasis to response mechanisms to severe constrain of the Mediterranean climate. Our tools enable comparative genomics studies on other Quercus species taking advantage of large intra-specific ecophysiological differences.

  10. SwePep, a database designed for endogenous peptides and mass spectrometry.

    Science.gov (United States)

    Fälth, Maria; Sköld, Karl; Norrman, Mathias; Svensson, Marcus; Fenyö, David; Andren, Per E

    2006-06-01

    A new database, SwePep, specifically designed for endogenous peptides, has been constructed to significantly speed up the identification process from complex tissue samples utilizing mass spectrometry. In the identification process the experimental peptide masses are compared with the peptide masses stored in the database both with and without possible post-translational modifications. This intermediate identification step is fast and singles out peptides that are potential endogenous peptides and can later be confirmed with tandem mass spectrometry data. Successful applications of this methodology are presented. The SwePep database is a relational database developed using MySql and Java. The database contains 4180 annotated endogenous peptides from different tissues originating from 394 different species as well as 50 novel peptides from brain tissue identified in our laboratory. Information about the peptides, including mass, isoelectric point, sequence, and precursor protein, is also stored in the database. This new approach holds great potential for removing the bottleneck that occurs during the identification process in the field of peptidomics. The SwePep database is available to the public.

  11. MEETING: Chlamydomonas Annotation Jamboree - October 2003

    Energy Technology Data Exchange (ETDEWEB)

    Grossman, Arthur R

    2007-04-13

    Shotgun sequencing of the nuclear genome of Chlamydomonas reinhardtii (Chlamydomonas throughout) was performed at an approximate 10X coverage by JGI. Roughly half of the genome is now contained on 26 scaffolds, all of which are at least 1.6 Mb, and the coverage of the genome is ~95%. There are now over 200,000 cDNA sequence reads that we have generated as part of the Chlamydomonas genome project (Grossman, 2003; Shrager et al., 2003; Grossman et al. 2007; Merchant et al., 2007); other sequences have also been generated by the Kasuza sequence group (Asamizu et al., 1999; Asamizu et al., 2000) or individual laboratories that have focused on specific genes. Shrager et al. (2003) placed the reads into distinct contigs (an assemblage of reads with overlapping nucleotide sequences), and contigs that group together as part of the same genes have been designated ACEs (assembly of contigs generated from EST information). All of the reads have also been mapped to the Chlamydomonas nuclear genome and the cDNAs and their corresponding genomic sequences have been reassembled, and the resulting assemblage is called an ACEG (an Assembly of contiguous EST sequences supported by genomic sequence) (Jain et al., 2007). Most of the unique genes or ACEGs are also represented by gene models that have been generated by the Joint Genome Institute (JGI, Walnut Creek, CA). These gene models have been placed onto the DNA scaffolds and are presented as a track on the Chlamydomonas genome browser associated with the genome portal (http://genome.jgi-psf.org/Chlre3/Chlre3.home.html). Ultimately, the meeting grant awarded by DOE has helped enormously in the development of an annotation pipeline (a set of guidelines used in the annotation of genes) and resulted in high quality annotation of over 4,000 genes; the annotators were from both Europe and the USA. Some of the people who led the annotation initiative were Arthur Grossman, Olivier Vallon, and Sabeeha Merchant (with many individual

  12. Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden

    Directory of Open Access Journals (Sweden)

    Kessy Abarenkov

    2016-09-01

    Full Text Available Recent molecular studies have identified substantial fungal diversity in indoor environments. Fungi and fungal particles have been linked to a range of potentially unwanted effects in the built environment, including asthma, decay of building materials, and food spoilage. The study of the built mycobiome is hampered by a number of constraints, one of which is the poor state of the metadata annotation of fungal DNA sequences from the built environment in public databases. In order to enable precise interrogation of such data – for example, “retrieve all fungal sequences recovered from bathrooms” – a workshop was organized at the University of Gothenburg (May 23-24, 2016 to annotate public fungal barcode (ITS sequences according to the MIxS-Built Environment annotation standard (http://gensc.org/mixs/. The 36 participants assembled a total of 45,488 data points from the published literature, including the addition of 8,430 instances of countries of collection from a total of 83 countries, 5,801 instances of building types, and 3,876 instances of surface-air contaminants. The results were implemented in the UNITE database for molecular identification of fungi (http://unite.ut.ee and were shared with other online resources. Data obtained from human/animal pathogenic fungi will furthermore be verified on culture based metadata for subsequent inclusion in the ISHAM-ITS database (http://its.mycologylab.org.

  13. Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

    Energy Technology Data Exchange (ETDEWEB)

    Ansong, Charles; Tolic, Nikola; Purvine, Samuel O.; Porwollik, Steffen; Jones, Marcus B.; Yoon, Hyunjin; Payne, Samuel H.; Martin, Jessica L.; Burnet, Meagan C.; Monroe, Matthew E.; Venepally, Pratap; Smith, Richard D.; Peterson, Scott; Heffron, Fred; Mcclelland, Michael; Adkins, Joshua N.

    2011-08-25

    Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. For example systems biology-oriented genome scale modeling efforts greatly benefit from accurate annotation of protein-coding genes to develop proper functioning models. However, determining protein-coding genes for most new genomes is almost completely performed by inference, using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. With the ability to directly measure peptides arising from expressed proteins, mass spectrometry-based proteomics approaches can be used to augment and verify coding regions of a genomic sequence and importantly detect post-translational processing events. In this study we utilized “shotgun” proteomics to guide accurate primary genome annotation of the bacterial pathogen Salmonella Typhimurium 14028 to facilitate a systems-level understanding of Salmonella biology. The data provides protein-level experimental confirmation for 44% of predicted protein-coding genes, suggests revisions to 48 genes assigned incorrect translational start sites, and uncovers 13 non-annotated genes missed by gene prediction programs. We also present a comprehensive analysis of post-translational processing events in Salmonella, revealing a wide range of complex chemical modifications (70 distinct modifications) and confirming more than 130 signal peptide and N-terminal methionine cleavage events in Salmonella. This study highlights several ways in which proteomics data applied during the primary stages of annotation can improve the quality of genome annotations, especially with regards to the annotation of mature protein products.

  14. [Prescription annotations in Welfare Pharmacy].

    Science.gov (United States)

    Han, Yi

    2018-03-01

    Welfare Pharmacy contains medical formulas documented by the government and official prescriptions used by the official pharmacy in the pharmaceutical process. In the last years of Southern Song Dynasty, anonyms gave a lot of prescription annotations, made textual researches for the name, source, composition and origin of the prescriptions, and supplemented important historical data of medical cases and researched historical facts. The annotations of Welfare Pharmacy gathered the essence of medical theory, and can be used as precious materials to correctly understand the syndrome differentiation, compatibility regularity and clinical application of prescriptions. This article deeply investigated the style and form of the prescription annotations in Welfare Pharmacy, the name of prescriptions and the evolution of terminology, the major functions of the prescriptions, processing methods, instructions for taking medicine and taboos of prescriptions, the medical cases and clinical efficacy of prescriptions, the backgrounds, sources, composition and cultural meanings of prescriptions, proposed that the prescription annotations played an active role in the textual dissemination, patent medicine production and clinical diagnosis and treatment of Welfare Pharmacy. This not only helps understand the changes in the names and terms of traditional Chinese medicines in Welfare Pharmacy, but also provides the basis for understanding the knowledge sources, compatibility regularity, important drug innovations and clinical medications of prescriptions in Welfare Pharmacy. Copyright© by the Chinese Pharmaceutical Association.

  15. PAMDB: a comprehensive Pseudomonas aeruginosa metabolome database.

    Science.gov (United States)

    Huang, Weiliang; Brewer, Luke K; Jones, Jace W; Nguyen, Angela T; Marcu, Ana; Wishart, David S; Oglesby-Sherrouse, Amanda G; Kane, Maureen A; Wilks, Angela

    2018-01-04

    The Pseudomonas aeruginosaMetabolome Database (PAMDB, http://pseudomonas.umaryland.edu) is a searchable, richly annotated metabolite database specific to P. aeruginosa. P. aeruginosa is a soil organism and significant opportunistic pathogen that adapts to its environment through a versatile energy metabolism network. Furthermore, P. aeruginosa is a model organism for the study of biofilm formation, quorum sensing, and bioremediation processes, each of which are dependent on unique pathways and metabolites. The PAMDB is modelled on the Escherichia coli (ECMDB), yeast (YMDB) and human (HMDB) metabolome databases and contains >4370 metabolites and 938 pathways with links to over 1260 genes and proteins. The database information was compiled from electronic databases, journal articles and mass spectrometry (MS) metabolomic data obtained in our laboratories. For each metabolite entered, we provide detailed compound descriptions, names and synonyms, structural and physiochemical information, nuclear magnetic resonance (NMR) and MS spectra, enzymes and pathway information, as well as gene and protein sequences. The database allows extensive searching via chemical names, structure and molecular weight, together with gene, protein and pathway relationships. The PAMBD and its future iterations will provide a valuable resource to biologists, natural product chemists and clinicians in identifying active compounds, potential biomarkers and clinical diagnostics. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. GiSAO.db: a database for ageing research

    Directory of Open Access Journals (Sweden)

    Grillari Johannes

    2011-05-01

    Full Text Available Abstract Background Age-related gene expression patterns of Homo sapiens as well as of model organisms such as Mus musculus, Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster are a basis for understanding the genetic mechanisms of ageing. For an effective analysis and interpretation of expression profiles it is necessary to store and manage huge amounts of data in an organized way, so that these data can be accessed and processed easily. Description GiSAO.db (Genes involved in senescence, apoptosis and oxidative stress database is a web-based database system for storing and retrieving ageing-related experimental data. Expression data of genes and miRNAs, annotation data like gene identifiers and GO terms, orthologs data and data of follow-up experiments are stored in the database. A user-friendly web application provides access to the stored data. KEGG pathways were incorporated and links to external databases augment the information in GiSAO.db. Search functions facilitate retrieval of data which can also be exported for further processing. Conclusions We have developed a centralized database that is very well suited for the management of data for ageing research. The database can be accessed at https://gisao.genome.tugraz.at and all the stored data can be viewed with a guest account.

  17. REDfly: a Regulatory Element Database for Drosophila.

    Science.gov (United States)

    Gallo, Steven M; Li, Long; Hu, Zihua; Halfon, Marc S

    2006-02-01

    Bioinformatics studies of transcriptional regulation in the metazoa are significantly hindered by the absence of readily available data on large numbers of transcriptional cis-regulatory modules (CRMs). Even the richly annotated Drosophila melanogaster genome lacks extensive CRM information. We therefore present here a database of Drosophila CRMs curated from the literature complete with both DNA sequence and a searchable description of the gene expression pattern regulated by each CRM. This resource should greatly facilitate the development of computational approaches to CRM discovery as well as bioinformatics analyses of regulatory sequence properties and evolution.

  18. New tools and improvements in the Exoplanet Transit Database

    Directory of Open Access Journals (Sweden)

    Pejcha O.

    2011-02-01

    Full Text Available Comprehensive collection of the available light curves, prediction possibilities and the online model fitting procedure, that are available via Exoplanet Transit Database became very popular in the community. In this paper we summarized the changes, that we made in the ETD during last year (including the Kepler candidates into the prediction section, modeling of an unknown planet in the model-fit section and some other small improvements. All this new tools cannot be found in the main ETD paper.

  19. Annotating abstract pronominal anaphora in the DAD project

    DEFF Research Database (Denmark)

    Navarretta, Costanza; Olsen, Sussi Anni

    2008-01-01

    n this paper we present an extension of the MATE/GNOME annotation scheme for anaphora (Poesio 2004) which accounts for abstract anaphora in Danish and Italian. By abstract anaphora it is here meant pronouns whose linguistic antecedents are verbal phrases, clauses and discourse segments. The exten......n this paper we present an extension of the MATE/GNOME annotation scheme for anaphora (Poesio 2004) which accounts for abstract anaphora in Danish and Italian. By abstract anaphora it is here meant pronouns whose linguistic antecedents are verbal phrases, clauses and discourse segments....... The extended scheme, which we call the DAD annotation scheme, allows to annotate information about abstract anaphora which is important to investigate their use, see Webber (1988), Gundel et al. (2003), Navarretta (2004) and which can influence their automatic treatment. Intercoder agreement scores obtained...... by applying the DAD annotation scheme on texts and dialogues in the two languages are given and show that th information proposed in the scheme can be recognised in a reliable way....

  20. Improvement of the Oracle setup and database design at the Heidelberg ion therapy center

    International Nuclear Information System (INIS)

    Hoeppner, K.; Haberer, T.; Mosthaf, J.M.; Peters, A.; Thomas, M.; Welde, A.; Froehlich, G.; Juelicher, S.; Schaa, V. R.W.; Schiebel, W.; Steinmetz, S.

    2012-01-01

    The HIT (Heidelberg Ion Therapy) center is an accelerator facility for cancer therapy using both carbon ions and protons, located at the university hospital in Heidelberg. It provides three therapy treatment rooms: two with fixed beam exit (both in clinical use), and a unique gantry with a rotating beam head, currently under commissioning. The backbone of the proprietary accelerator control system consists of an Oracle database running on a Windows server, storing and delivering data of beam cycles, error logging, measured values, and the device parameters and beam settings for about 100,000 combinations of energy, beam size and particle rate used in treatment plans. Since going operational, we found some performance problems with the current database setup. Thus, we started an analysis that focused on the following topics: hardware resources of the database server, configuration of the Oracle instance, and a review of the database design that underwent several changes since its original design. The analysis revealed issues on all fields. The outdated server will be replaced by a state-of-the-art machine soon. We will present improvements of the Oracle configuration, the optimization of SQL statements, and the performance tuning of database design by adding new indexes which proved directly visible in accelerator operation, while data integrity was improved by additional foreign key constraints. (authors)