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.

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.

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.

Coreference annotation and resolution in the Colorado Richly Annotated Full Text (CRAFT) corpus of biomedical journal articles.

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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

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.

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

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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.

An open annotation ontology for science on web 3.0.

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Ciccarese, Paolo; Ocana, Marco; Garcia Castro, Leyla Jael; Das, Sudeshna; Clark, Tim

2011-05-17

There is currently a gap between the rich and expressive collection of published biomedical ontologies, and the natural language expression of biomedical papers consumed on a daily basis by scientific researchers. The purpose of this paper is to provide an open, shareable structure for dynamic integration of biomedical domain ontologies with the scientific document, in the form of an Annotation Ontology (AO), thus closing this gap and enabling application of formal biomedical ontologies directly to the literature as it emerges. Initial requirements for AO were elicited by analysis of integration needs between biomedical web communities, and of needs for representing and integrating results of biomedical text mining. Analysis of strengths and weaknesses of previous efforts in this area was also performed. A series of increasingly refined annotation tools were then developed along with a metadata model in OWL, and deployed for feedback and additional requirements the ontology to users at a major pharmaceutical company and a major academic center. Further requirements and critiques of the model were also elicited through discussions with many colleagues and incorporated into the work. This paper presents Annotation Ontology (AO), an open ontology in OWL-DL for annotating scientific documents on the web. AO supports both human and algorithmic content annotation. It enables "stand-off" or independent metadata anchored to specific positions in a web document by any one of several methods. In AO, the document may be annotated but is not required to be under update control of the annotator. AO contains a provenance model to support versioning, and a set model for specifying groups and containers of annotation. AO is freely available under open source license at http://purl.org/ao/, and extensive documentation including screencasts is available on AO's Google Code page: http://code.google.com/p/annotation-ontology/ . The Annotation Ontology meets critical requirements for

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

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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.

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

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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

An Atlas of annotations of Hydra vulgaris transcriptome.

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Evangelista, Daniela; Tripathi, Kumar Parijat; Guarracino, Mario Rosario

2016-09-22

RNA sequencing takes advantage of the Next Generation Sequencing (NGS) technologies for analyzing RNA transcript counts with an excellent accuracy. Trying to interpret this huge amount of data in biological information is still a key issue, reason for which the creation of web-resources useful for their analysis is highly desiderable. Starting from a previous work, Transcriptator, we present the Atlas of Hydra's vulgaris, an extensible web tool in which its complete transcriptome is annotated. In order to provide to the users an advantageous resource that include the whole functional annotated transcriptome of Hydra vulgaris water polyp, we implemented the Atlas web-tool contains 31.988 accesible and downloadable transcripts of this non-reference model organism. Atlas, as a freely available resource, can be considered a valuable tool to rapidly retrieve functional annotation for transcripts differentially expressed in Hydra vulgaris exposed to the distinct experimental treatments. WEB RESOURCE URL: http://www-labgtp.na.icar.cnr.it/Atlas .

Graph-based sequence annotation using a data integration approach

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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.

BioCause: Annotating and analysing causality in the biomedical domain.

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Mihăilă, Claudiu; Ohta, Tomoko; Pyysalo, Sampo; Ananiadou, Sophia

2013-01-16

Biomedical corpora annotated with event-level information represent an important resource for domain-specific information extraction (IE) systems. However, bio-event annotation alone cannot cater for all the needs of biologists. Unlike work on relation and event extraction, most of which focusses on specific events and named entities, we aim to build a comprehensive resource, covering all statements of causal association present in discourse. Causality lies at the heart of biomedical knowledge, such as diagnosis, pathology or systems biology, and, thus, automatic causality recognition can greatly reduce the human workload by suggesting possible causal connections and aiding in the curation of pathway models. A biomedical text corpus annotated with such relations is, hence, crucial for developing and evaluating biomedical text mining. We have defined an annotation scheme for enriching biomedical domain corpora with causality relations. This schema has subsequently been used to annotate 851 causal relations to form BioCause, a collection of 19 open-access full-text biomedical journal articles belonging to the subdomain of infectious diseases. These documents have been pre-annotated with named entity and event information in the context of previous shared tasks. We report an inter-annotator agreement rate of over 60% for triggers and of over 80% for arguments using an exact match constraint. These increase significantly using a relaxed match setting. Moreover, we analyse and describe the causality relations in BioCause from various points of view. This information can then be leveraged for the training of automatic causality detection systems. Augmenting named entity and event annotations with information about causal discourse relations could benefit the development of more sophisticated IE systems. These will further influence the development of multiple tasks, such as enabling textual inference to detect entailments, discovering new facts and providing new

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

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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.

Use of Annotations for Component and Framework Interoperability

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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

Pipeline to upgrade the genome annotations

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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.

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/.

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.

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

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...

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

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...

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.

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

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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.

Chronological changes in microRNA expression in the developing human brain.

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Michael P Moreau

Full Text Available MicroRNAs (miRNAs are endogenously expressed noncoding RNA molecules that are believed to regulate multiple neurobiological processes. Expression studies have revealed distinct temporal expression patterns in the developing rodent and porcine brain, but comprehensive profiling in the developing human brain has not been previously reported.We performed microarray and TaqMan-based expression analysis of all annotated mature miRNAs (miRBase 10.0 as well as 373 novel, predicted miRNAs. Expression levels were measured in 48 post-mortem brain tissue samples, representing gestational ages 14-24 weeks, as well as early postnatal and adult time points.Expression levels of 312 miRNAs changed significantly between at least two of the broad age categories, defined as fetal, young, and adult.We have constructed a miRNA expression atlas of the developing human brain, and we propose a classification scheme to guide future studies of neurobiological function.

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

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.

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.

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.

Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer's disease.

Directory of Open Access Journals (Sweden)

Qiongshi Lu

2017-07-01

Full Text Available Continuing efforts from large international consortia have made genome-wide epigenomic and transcriptomic annotation data publicly available for a variety of cell and tissue types. However, synthesis of these datasets into effective summary metrics to characterize the functional non-coding genome remains a challenge. Here, we present GenoSkyline-Plus, an extension of our previous work through integration of an expanded set of epigenomic and transcriptomic annotations to produce high-resolution, single tissue annotations. After validating our annotations with a catalog of tissue-specific non-coding elements previously identified in the literature, we apply our method using data from 127 different cell and tissue types to present an atlas of heritability enrichment across 45 different GWAS traits. We show that broader organ system categories (e.g. immune system increase statistical power in identifying biologically relevant tissue types for complex diseases while annotations of individual cell types (e.g. monocytes or B-cells provide deeper insights into disease etiology. Additionally, we use our GenoSkyline-Plus annotations in an in-depth case study of late-onset Alzheimer's disease (LOAD. Our analyses suggest a strong connection between LOAD heritability and genetic variants contained in regions of the genome functional in monocytes. Furthermore, we show that LOAD shares a similar localization of SNPs to monocyte-functional regions with Parkinson's disease. Overall, we demonstrate that integrated genome annotations at the single tissue level provide a valuable tool for understanding the etiology of complex human diseases. Our GenoSkyline-Plus annotations are freely available at http://genocanyon.med.yale.edu/GenoSkyline.

Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer's disease.

Science.gov (United States)

Lu, Qiongshi; Powles, Ryan L; Abdallah, Sarah; Ou, Derek; Wang, Qian; Hu, Yiming; Lu, Yisi; Liu, Wei; Li, Boyang; Mukherjee, Shubhabrata; Crane, Paul K; Zhao, Hongyu

2017-07-01

Continuing efforts from large international consortia have made genome-wide epigenomic and transcriptomic annotation data publicly available for a variety of cell and tissue types. However, synthesis of these datasets into effective summary metrics to characterize the functional non-coding genome remains a challenge. Here, we present GenoSkyline-Plus, an extension of our previous work through integration of an expanded set of epigenomic and transcriptomic annotations to produce high-resolution, single tissue annotations. After validating our annotations with a catalog of tissue-specific non-coding elements previously identified in the literature, we apply our method using data from 127 different cell and tissue types to present an atlas of heritability enrichment across 45 different GWAS traits. We show that broader organ system categories (e.g. immune system) increase statistical power in identifying biologically relevant tissue types for complex diseases while annotations of individual cell types (e.g. monocytes or B-cells) provide deeper insights into disease etiology. Additionally, we use our GenoSkyline-Plus annotations in an in-depth case study of late-onset Alzheimer's disease (LOAD). Our analyses suggest a strong connection between LOAD heritability and genetic variants contained in regions of the genome functional in monocytes. Furthermore, we show that LOAD shares a similar localization of SNPs to monocyte-functional regions with Parkinson's disease. Overall, we demonstrate that integrated genome annotations at the single tissue level provide a valuable tool for understanding the etiology of complex human diseases. Our GenoSkyline-Plus annotations are freely available at http://genocanyon.med.yale.edu/GenoSkyline.

Annotating spatio-temporal datasets for meaningful analysis in the Web

Science.gov (United States)

Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

2014-05-01

More and more environmental datasets that vary in space and time are available in the Web. This comes along with an advantage of using the data for other purposes than originally foreseen, but also with the danger that users may apply inappropriate analysis procedures due to lack of important assumptions made during the data collection process. In order to guide towards a meaningful (statistical) analysis of spatio-temporal datasets available in the Web, we have developed a Higher-Order-Logic formalism that captures some relevant assumptions in our previous work [1]. It allows to proof on meaningful spatial prediction and aggregation in a semi-automated fashion. In this poster presentation, we will present a concept for annotating spatio-temporal datasets available in the Web with concepts defined in our formalism. Therefore, we have defined a subset of the formalism as a Web Ontology Language (OWL) pattern. It allows capturing the distinction between the different spatio-temporal variable types, i.e. point patterns, fields, lattices and trajectories, that in turn determine whether a particular dataset can be interpolated or aggregated in a meaningful way using a certain procedure. The actual annotations that link spatio-temporal datasets with the concepts in the ontology pattern are provided as Linked Data. In order to allow data producers to add the annotations to their datasets, we have implemented a Web portal that uses a triple store at the backend to store the annotations and to make them available in the Linked Data cloud. Furthermore, we have implemented functions in the statistical environment R to retrieve the RDF annotations and, based on these annotations, to support a stronger typing of spatio-temporal datatypes guiding towards a meaningful analysis in R. [1] Stasch, C., Scheider, S., Pebesma, E., Kuhn, W. (2014): "Meaningful spatial prediction and aggregation", Environmental Modelling & Software, 51, 149-165.

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.

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.

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

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.

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.

Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer’s disease

Science.gov (United States)

Abdallah, Sarah; Ou, Derek; Wang, Qian; Hu, Yiming; Lu, Yisi; Liu, Wei; Li, Boyang; Mukherjee, Shubhabrata; Crane, Paul K.; Zhao, Hongyu

2017-01-01

Continuing efforts from large international consortia have made genome-wide epigenomic and transcriptomic annotation data publicly available for a variety of cell and tissue types. However, synthesis of these datasets into effective summary metrics to characterize the functional non-coding genome remains a challenge. Here, we present GenoSkyline-Plus, an extension of our previous work through integration of an expanded set of epigenomic and transcriptomic annotations to produce high-resolution, single tissue annotations. After validating our annotations with a catalog of tissue-specific non-coding elements previously identified in the literature, we apply our method using data from 127 different cell and tissue types to present an atlas of heritability enrichment across 45 different GWAS traits. We show that broader organ system categories (e.g. immune system) increase statistical power in identifying biologically relevant tissue types for complex diseases while annotations of individual cell types (e.g. monocytes or B-cells) provide deeper insights into disease etiology. Additionally, we use our GenoSkyline-Plus annotations in an in-depth case study of late-onset Alzheimer’s disease (LOAD). Our analyses suggest a strong connection between LOAD heritability and genetic variants contained in regions of the genome functional in monocytes. Furthermore, we show that LOAD shares a similar localization of SNPs to monocyte-functional regions with Parkinson’s disease. Overall, we demonstrate that integrated genome annotations at the single tissue level provide a valuable tool for understanding the etiology of complex human diseases. Our GenoSkyline-Plus annotations are freely available at http://genocanyon.med.yale.edu/GenoSkyline. PMID:28742084

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.

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.

Physician evaluation and acceptance of remote transmission of CT, digital subtraction angiography, and US annotated images

International Nuclear Information System (INIS)

Haskin, M.E.; Robbins, C.; Kohn, M.; Laffey, P.A.; Haskin, P.H.; Teplick, J.G.; Teplick, S.K.; Peyster, R.G.

1986-01-01

The authors have found annotated images an effective way of communicating the results of imaging studies to referring physicians. Of particular value is the collation of representative images from several modalities. Previously, hard copy of this collation was sent to the referring physician as an integrated imaging report. Recently they developed a computer-based station that transmits annotated images to remote personal computer (PC) terminals via a telephone modem which requires 30 seconds to send each image. This annotated image report can be quickly accessed by the referring physician at the remote PC terminal The prototype system, utility, diagnostic fidelity, and potential of this remote system are described

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.

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.

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.

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/

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/ .

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.

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.

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.

Fast Arc-Annotated Subsequence Matching in Linear Space

DEFF Research Database (Denmark)

Bille, Philip; Gørtz, Inge Li

2010-01-01

is deleted any arc with an endpoint in that base is also deleted. Arc-annotated strings where the arcs are "nested" are a natural model of RNA molecules that captures both the primary and secondary structure of these. The arc-preserving subsequence problem for nested arc-annotated strings is basic primitive...... for investigating the function of RNA molecules. Gramm et al. [ACM Trans. Algorithms 2006] gave an algorithm for this problem using O(nm) time and space, where m and n are the lengths of P and Q, respectively. In this paper we present; a new algorithm using O(nm) time and O(n+m,) space, thereby matching...... the previous time bound while significantly reducing the space from a quadratic term to linear. This is essential to process large RNA molecules where the space is a likely to be a bottleneck. To obtain our result we introduce several novel ideas which may be of independent interest for related problems on arc...

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

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

Conservation and losses of non-coding RNAs in avian genomes.

Directory of Open Access Journals (Sweden)

Paul P Gardner

Full Text Available Here we present the results of a large-scale bioinformatics annotation of non-coding RNA loci in 48 avian genomes. Our approach uses probabilistic models of hand-curated families from the Rfam database to infer conserved RNA families within each avian genome. We supplement these annotations with predictions from the tRNA annotation tool, tRNAscan-SE and microRNAs from miRBase. We identify 34 lncRNA-associated loci that are conserved between birds and mammals and validate 12 of these in chicken. We report several intriguing cases where a reported mammalian lncRNA, but not its function, is conserved. We also demonstrate extensive conservation of classical ncRNAs (e.g., tRNAs and more recently discovered ncRNAs (e.g., snoRNAs and miRNAs in birds. Furthermore, we describe numerous "losses" of several RNA families, and attribute these to either genuine loss, divergence or missing data. In particular, we show that many of these losses are due to the challenges associated with assembling avian microchromosomes. These combined results illustrate the utility of applying homology-based methods for annotating novel vertebrate genomes.

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....

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

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

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.

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

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.

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…

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

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.

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.

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.

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.

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.

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

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.

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...

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".

Discovering gene annotations in biomedical text databases

Directory of Open Access Journals (Sweden)

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

AstroDAbis: Annotations and Cross-Matches for Remote Catalogues

Science.gov (United States)

Gray, N.; Mann, R. G.; Morris, D.; Holliman, M.; Noddle, K.

2012-09-01

Astronomers are good at sharing data, but poorer at sharing knowledge. Almost all astronomical data ends up in open archives, and access to these is being simplified by the development of the global Virtual Observatory (VO). This is a great advance, but the fundamental problem remains that these archives contain only basic observational data, whereas all the astrophysical interpretation of that data — which source is a quasar, which a low-mass star, and which an image artefact — is contained in journal papers, with very little linkage back from the literature to the original data archives. It is therefore currently impossible for an astronomer to pose a query like “give me all sources in this data archive that have been identified as quasars” and this limits the effective exploitation of these archives, as the user of an archive has no direct means of taking advantage of the knowledge derived by its previous users. The AstroDAbis service aims to address this, in a prototype service enabling astronomers to record annotations and cross-identifications in the AstroDAbis service, annotating objects in other catalogues. We have deployed two interfaces to the annotations, namely one astronomy-specific one using the TAP protocol (Dowler et al. 2011), and a second exploiting generic Linked Open Data (LOD) and RDF techniques.

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

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

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.

USI: a fast and accurate approach for conceptual document annotation.

Science.gov (United States)

Fiorini, Nicolas; Ranwez, Sylvie; Montmain, Jacky; Ranwez, Vincent

2015-03-14

Semantic approaches such as concept-based information retrieval rely on a corpus in which resources are indexed by concepts belonging to a domain ontology. In order to keep such applications up-to-date, new entities need to be frequently annotated to enrich the corpus. However, this task is time-consuming and requires a high-level of expertise in both the domain and the related ontology. Different strategies have thus been proposed to ease this indexing process, each one taking advantage from the features of the document. In this paper we present USI (User-oriented Semantic Indexer), a fast and intuitive method for indexing tasks. We introduce a solution to suggest a conceptual annotation for new entities based on related already indexed documents. Our results, compared to those obtained by previous authors using the MeSH thesaurus and a dataset of biomedical papers, show that the method surpasses text-specific methods in terms of both quality and speed. Evaluations are done via usual metrics and semantic similarity. By only relying on neighbor documents, the User-oriented Semantic Indexer does not need a representative learning set. Yet, it provides better results than the other approaches by giving a consistent annotation scored with a global criterion - instead of one score per concept.

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)

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,

Overcoming function annotation errors in the Gram-positive pathogen Streptococcus suis by a proteomics-driven approach

Directory of Open Access Journals (Sweden)

Bárcena José A

2008-12-01

Full Text Available Abstract Background Annotation of protein-coding genes is a key step in sequencing projects. Protein functions are mainly assigned on the basis of the amino acid sequence alone by searching of homologous proteins. However, fully automated annotation processes often lead to wrong prediction of protein functions, and therefore time-intensive manual curation is often essential. Here we describe a fast and reliable way to correct function annotation in sequencing projects, focusing on surface proteomes. We use a proteomics approach, previously proven to be very powerful for identifying new vaccine candidates against Gram-positive pathogens. It consists of shaving the surface of intact cells with two proteases, the specific cleavage-site trypsin and the unspecific proteinase K, followed by LC/MS/MS analysis of the resulting peptides. The identified proteins are contrasted by computational analysis and their sequences are inspected to correct possible errors in function prediction. Results When applied to the zoonotic pathogen Streptococcus suis, of which two strains have been recently sequenced and annotated, we identified a set of surface proteins without cytoplasmic contamination: all the proteins identified had exporting or retention signals towards the outside and/or the cell surface, and viability of protease-treated cells was not affected. The combination of both experimental evidences and computational methods allowed us to determine that two of these proteins are putative extracellular new adhesins that had been previously attributed a wrong cytoplasmic function. One of them is a putative component of the pilus of this bacterium. Conclusion We illustrate the complementary nature of laboratory-based and computational methods to examine in concert the localization of a set of proteins in the cell, and demonstrate the utility of this proteomics-based strategy to experimentally correct function annotation errors in sequencing projects. This

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.

Genome-wide Annotation, Identification, and Global Transcriptomic Analysis of Regulatory or Small RNA Gene Expression in Staphylococcus aureus.

Science.gov (United States)

Carroll, Ronan K; Weiss, Andy; Broach, William H; Wiemels, Richard E; Mogen, Austin B; Rice, Kelly C; Shaw, Lindsey N

2016-02-09

In Staphylococcus aureus, hundreds of small regulatory or small RNAs (sRNAs) have been identified, yet this class of molecule remains poorly understood and severely understudied. sRNA genes are typically absent from genome annotation files, and as a consequence, their existence is often overlooked, particularly in global transcriptomic studies. To facilitate improved detection and analysis of sRNAs in S. aureus, we generated updated GenBank files for three commonly used S. aureus strains (MRSA252, NCTC 8325, and USA300), in which we added annotations for >260 previously identified sRNAs. These files, the first to include genome-wide annotation of sRNAs in S. aureus, were then used as a foundation to identify novel sRNAs in the community-associated methicillin-resistant strain USA300. This analysis led to the discovery of 39 previously unidentified sRNAs. Investigating the genomic loci of the newly identified sRNAs revealed a surprising degree of inconsistency in genome annotation in S. aureus, which may be hindering the analysis and functional exploration of these elements. Finally, using our newly created annotation files as a reference, we perform a global analysis of sRNA gene expression in S. aureus and demonstrate that the newly identified tsr25 is the most highly upregulated sRNA in human serum. This study provides an invaluable resource to the S. aureus research community in the form of our newly generated annotation files, while at the same time presenting the first examination of differential sRNA expression in pathophysiologically relevant conditions. Despite a large number of studies identifying regulatory or small RNA (sRNA) genes in Staphylococcus aureus, their annotation is notably lacking in available genome files. In addition to this, there has been a considerable lack of cross-referencing in the wealth of studies identifying these elements, often leading to the same sRNA being identified multiple times and bearing multiple names. In this work

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.

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.

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.

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.

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%.

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...

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

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.

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....

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.

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...

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.

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).

Annotation of the Evaluative Language in a Dependency Treebank

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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.

The caBIG annotation and image Markup project.

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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.

Annotating activation/inhibition relationships to protein-protein interactions using gene ontology relations.

Science.gov (United States)

Yim, Soorin; Yu, Hasun; Jang, Dongjin; Lee, Doheon

2018-04-11

Signaling pathways can be reconstructed by identifying 'effect types' (i.e. activation/inhibition) of protein-protein interactions (PPIs). Effect types are composed of 'directions' (i.e. upstream/downstream) and 'signs' (i.e. positive/negative), thereby requiring directions as well as signs of PPIs to predict signaling events from PPI networks. Here, we propose a computational method for systemically annotating effect types to PPIs using relations between functional information of proteins. We used regulates, positively regulates, and negatively regulates relations in Gene Ontology (GO) to predict directions and signs of PPIs. These relations indicate both directions and signs between GO terms so that we can project directions and signs between relevant GO terms to PPIs. Independent test results showed that our method is effective for predicting both directions and signs of PPIs. Moreover, our method outperformed a previous GO-based method that did not consider the relations between GO terms. We annotated effect types to human PPIs and validated several highly confident effect types against literature. The annotated human PPIs are available in Additional file 2 to aid signaling pathway reconstruction and network biology research. We annotated effect types to PPIs by using regulates, positively regulates, and negatively regulates relations in GO. We demonstrated that those relations are effective for predicting not only signs, but also directions of PPIs. The usefulness of those relations suggests their potential applications to other types of interactions such as protein-DNA interactions.

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.

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.

Gene Ontology annotation of the rice blast fungus, Magnaporthe oryzae

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Deng Jixin

2009-02-01

Full Text Available Abstract Background Magnaporthe oryzae, the causal agent of blast disease of rice, is the most destructive disease of rice worldwide. The genome of this fungal pathogen has been sequenced and an automated annotation has recently been updated to Version 6 http://www.broad.mit.edu/annotation/genome/magnaporthe_grisea/MultiDownloads.html. However, a comprehensive manual curation remains to be performed. Gene Ontology (GO annotation is a valuable means of assigning functional information using standardized vocabulary. We report an overview of the GO annotation for Version 5 of M. oryzae genome assembly. Methods A similarity-based (i.e., computational GO annotation with manual review was conducted, which was then integrated with a literature-based GO annotation with computational assistance. For similarity-based GO annotation a stringent reciprocal best hits method was used to identify similarity between predicted proteins of M. oryzae and GO proteins from multiple organisms with published associations to GO terms. Significant alignment pairs were manually reviewed. Functional assignments were further cross-validated with manually reviewed data, conserved domains, or data determined by wet lab experiments. Additionally, biological appropriateness of the functional assignments was manually checked. Results In total, 6,286 proteins received GO term assignment via the homology-based annotation, including 2,870 hypothetical proteins. Literature-based experimental evidence, such as microarray, MPSS, T-DNA insertion mutation, or gene knockout mutation, resulted in 2,810 proteins being annotated with GO terms. Of these, 1,673 proteins were annotated with new terms developed for Plant-Associated Microbe Gene Ontology (PAMGO. In addition, 67 experiment-determined secreted proteins were annotated with PAMGO terms. Integration of the two data sets resulted in 7,412 proteins (57% being annotated with 1,957 distinct and specific GO terms. Unannotated proteins

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 .

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.

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.

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

Identification of Novel and Conserved microRNAs in Homalodisca vitripennis, the Glassy-Winged Sharpshooter by Expression Profiling.

Directory of Open Access Journals (Sweden)

Raja Sekhar Nandety

Full Text Available The glassy-winged sharpshooter (GWSS Homalodisca vitripennis (Hemiptera: Cicadellidae, is a xylem-feeding leafhopper and an important vector of the bacterium Xylella fastidiosa; the causal agent of Pierce's disease of grapevines. MicroRNAs are a class of small RNAs that play an important role in the functional development of various organisms including insects. In H. vitripennis, we identified microRNAs using high-throughput deep sequencing of adults followed by computational and manual annotation. A total of 14 novel microRNAs that are not found in the miRBase were identified from adult H. vitripennis. Conserved microRNAs were also found in our datasets. By comparison to our previously determined transcriptome sequence of H. vitripennis, we identified the potential targets of the microRNAs in the transcriptome. This microRNA profile information not only provides a more nuanced understanding of the biological and physiological mechanisms that govern gene expression in H. vitripennis, but may also lead to the identification of novel mechanisms for biorationally designed management strategies through the use of microRNAs.

[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.

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.

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....

Annotated bibliography

International Nuclear Information System (INIS)

1997-08-01

Under a cooperative agreement with the U.S. Department of Energy's Office of Science and Technology, Waste Policy Institute (WPI) is conducting a five-year research project to develop a research-based approach for integrating communication products in stakeholder involvement related to innovative technology. As part of the research, WPI developed this annotated bibliography which contains almost 100 citations of articles/books/resources involving topics related to communication and public involvement aspects of deploying innovative cleanup technology. To compile the bibliography, WPI performed on-line literature searches (e.g., Dialog, International Association of Business Communicators Public Relations Society of America, Chemical Manufacturers Association, etc.), consulted past years proceedings of major environmental waste cleanup conferences (e.g., Waste Management), networked with professional colleagues and DOE sites to gather reports or case studies, and received input during the August 1996 Research Design Team meeting held to discuss the project's research methodology. Articles were selected for annotation based upon their perceived usefulness to the broad range of public involvement and communication practitioners

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.

Quick Pad Tagger : An Efficient Graphical User Interface for Building Annotated Corpora with Multiple Annotation Layers

OpenAIRE

Marc Schreiber; Kai Barkschat; Bodo Kraft; Albert Zundorf

2015-01-01

More and more domain specific applications in the internet make use of Natural Language Processing (NLP) tools (e. g. Information Extraction systems). The output quality of these applications relies on the output quality of the used NLP tools. Often, the quality can be increased by annotating a domain specific corpus. However, annotating a corpus is a time consuming and exhaustive task. To reduce the annota tion time we present...

Supplementary Material for: BEACON: automated tool for Bacterial GEnome Annotation ComparisON

KAUST Repository

Kalkatawi, Manal M.; Alam, Intikhab; Bajic, Vladimir B.

2015-01-01

Abstract 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 BEACONâ 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/ .

Extending eScience Provenance with User-Submitted Semantic Annotations

Science.gov (United States)

Michaelis, J.; Zednik, S.; West, P.; Fox, P. A.; McGuinness, D. L.

2010-12-01

eScience based systems generate provenance of their data products, related to such things as: data processing, data collection conditions, expert evaluation, and data product quality. Recent advances in web-based technology offer users the possibility of making annotations to both data products and steps in accompanying provenance traces, thereby expanding the utility of such provenance for others. These contributing users may have varying backgrounds, ranging from system experts to outside domain experts to citizen scientists. Furthermore, such users may wish to make varying types of annotations - ranging from documenting the purpose of a provenance step to raising concerns about the quality of data dependencies. Semantic Web technologies allow for such kinds of rich annotations to be made to provenance through the use of ontology vocabularies for (i) organizing provenance, and (ii) organizing user/annotation classifications. Furthermore, through Linked Data practices, Semantic linkages may be made from provenance steps to external data of interest. A desire for Semantically-annotated provenance has been motivated by data management issues in the Mauna Loa Solar Observatory’s (MLSO) Advanced Coronal Observing System (ACOS). In ACOS, photomoeter-based readings are taken of solar activity and subsequently processed into final data products consumable by end users. At intermediate stages of ACOS processing, factors such as evaluations by human experts and weather conditions are logged, which could impact data product quality. If such factors are linked via user-submitted annotations to provenance, it could be significantly beneficial for other users. Likewise, the background of a user could impact the credibility of their annotations. For example, an annotation made by a citizen scientist describing the purpose of a provenance step may not be as reliable as a similar annotation made by an ACOS project member. For this work, we have developed a software package that

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…

Crowdsourcing and annotating NER for Twitter #drift

DEFF Research Database (Denmark)

Fromreide, Hege; Hovy, Dirk; Søgaard, Anders

2014-01-01

We present two new NER datasets for Twitter; a manually annotated set of 1,467 tweets (kappa=0.942) and a set of 2,975 expert-corrected, crowdsourced NER annotated tweets from the dataset described in Finin et al. (2010). In our experiments with these datasets, we observe two important points: (a......) language drift on Twitter is significant, and while off-the-shelf systems have been reported to perform well on in-sample data, they often perform poorly on new samples of tweets, (b) state-of-the-art performance across various datasets can beobtained from crowdsourced annotations, making it more feasible...

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.

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.

Annotating the protein-RNA interaction sites in proteins using evolutionary information and protein backbone structure.

Science.gov (United States)

Li, Tao; Li, Qian-Zhong

2012-11-07

RNA-protein interactions play important roles in various biological processes. The precise detection of RNA-protein interaction sites is very important for understanding essential biological processes and annotating the function of the proteins. In this study, based on various features from amino acid sequence and structure, including evolutionary information, solvent accessible surface area and torsion angles (φ, ψ) in the backbone structure of the polypeptide chain, a computational method for predicting RNA-binding sites in proteins is proposed. When the method is applied to predict RNA-binding sites in three datasets: RBP86 containing 86 protein chains, RBP107 containing 107 proteins chains and RBP109 containing 109 proteins chains, better sensitivities and specificities are obtained compared to previously published methods in five-fold cross-validation tests. In order to make further examination for the efficiency of our method, the RBP107 dataset is used as training set, RBP86 and RBP109 datasets are used as the independent test sets. In addition, as examples of our prediction, RNA-binding sites in a few proteins are presented. The annotated results are consistent with the PDB annotation. These results show that our method is useful for annotating RNA binding sites of novel proteins.

Creating Gaze Annotations in Head Mounted Displays

DEFF Research Database (Denmark)

Mardanbeigi, Diako; Qvarfordt, Pernilla

2015-01-01

To facilitate distributed communication in mobile settings, we developed GazeNote for creating and sharing gaze annotations in head mounted displays (HMDs). With gaze annotations it possible to point out objects of interest within an image and add a verbal description. To create an annota- tion...

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.

Challenges in Whole-Genome Annotation of Pyrosequenced Eukaryotic Genomes

Energy Technology Data Exchange (ETDEWEB)

Kuo, Alan; Grigoriev, Igor

2009-04-17

Pyrosequencing technologies such as 454/Roche and Solexa/Illumina vastly lower the cost of nucleotide sequencing compared to the traditional Sanger method, and thus promise to greatly expand the number of sequenced eukaryotic genomes. However, the new technologies also bring new challenges such as shorter reads and new kinds and higher rates of sequencing errors, which complicate genome assembly and gene prediction. At JGI we are deploying 454 technology for the sequencing and assembly of ever-larger eukaryotic genomes. Here we describe our first whole-genome annotation of a purely 454-sequenced fungal genome that is larger than a yeast (>30 Mbp). The pezizomycotine (filamentous ascomycote) Aspergillus carbonarius belongs to the Aspergillus section Nigri species complex, members of which are significant as platforms for bioenergy and bioindustrial technology, as members of soil microbial communities and players in the global carbon cycle, and as agricultural toxigens. Application of a modified version of the standard JGI Annotation Pipeline has so far predicted ~;;10k genes. ~;;12percent of these preliminary annotations suffer a potential frameshift error, which is somewhat higher than the ~;;9percent rate in the Sanger-sequenced and conventionally assembled and annotated genome of fellow Aspergillus section Nigri member A. niger. Also,>90percent of A. niger genes have potential homologs in the A. carbonarius preliminary annotation. Weconclude, and with further annotation and comparative analysis expect to confirm, that 454 sequencing strategies provide a promising substrate for annotation of modestly sized eukaryotic genomes. We will also present results of annotation of a number of other pyrosequenced fungal genomes of bioenergy interest.

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.

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

assess the usefulness of the tool. The proportion of individuals accurately identifying the presence of a specific advertisement was higher when provided with pictures of the product's logo and an example of the ad, and even higher when also provided the zoom tool (χ(2) 2=155.7, Pphotograph annotation and methodically assess the quality of raters' work. Overall, the combination of crowdsourcing technologies with tiered data flow and tools that enhance annotation quality represents a breakthrough solution to the problem of photograph annotation, vastly expanding opportunities for the use of photographs rich in public health and other data on a scale previously unimaginable.

Functional annotation of hierarchical modularity.

Directory of Open Access Journals (Sweden)

Kanchana Padmanabhan

Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

Fluid Annotations in a Open World

DEFF Research Database (Denmark)

Zellweger, Polle Trescott; Bouvin, Niels Olof; Jehøj, Henning

2001-01-01

Fluid Documents use animated typographical changes to provide a novel and appealing user experience for hypertext browsing and for viewing document annotations in context. This paper describes an effort to broaden the utility of Fluid Documents by using the open hypermedia Arakne Environment to l...... to layer fluid annotations and links on top of abitrary HTML pages on the World Wide Web. Changes to both Fluid Documents and Arakne are required....

Model and Interoperability using Meta Data Annotations

Science.gov (United States)

David, O.

2011-12-01

Software frameworks and architectures are in need for meta data to efficiently support model integration. Modelers have to know the context of a model, often stepping into modeling semantics and auxiliary information usually not provided in a concise structure and universal format, consumable by a range of (modeling) tools. XML often seems the obvious solution for capturing meta data, but its wide adoption to facilitate model interoperability is limited by XML schema fragmentation, complexity, and verbosity outside of a data-automation process. Ontologies seem to overcome those shortcomings, however the practical significance of their use remains to be demonstrated. OMS version 3 took a different approach for meta data representation. The fundamental building block of a modular model in OMS is a software component representing a single physical process, calibration method, or data access approach. Here, programing language features known as Annotations or Attributes were adopted. Within other (non-modeling) frameworks it has been observed that annotations lead to cleaner and leaner application code. Framework-supported model integration, traditionally accomplished using Application Programming Interfaces (API) calls is now achieved using descriptive code annotations. Fully annotated components for various hydrological and Ag-system models now provide information directly for (i) model assembly and building, (ii) data flow analysis for implicit multi-threading or visualization, (iii) automated and comprehensive model documentation of component dependencies, physical data properties, (iv) automated model and component testing, calibration, and optimization, and (v) automated audit-traceability to account for all model resources leading to a particular simulation result. Such a non-invasive methodology leads to models and modeling components with only minimal dependencies on the modeling framework but a strong reference to its originating code. Since models and

Black English Annotations for Elementary Reading Programs.

Science.gov (United States)

Prasad, Sandre

This report describes a program that uses annotations in the teacher's editions of existing reading programs to indicate the characteristics of black English that may interfere with the reading process of black children. The first part of the report provides a rationale for the annotation approach, explaining that the discrepancy between written…

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

Special Issue: Annotated Bibliography for Volumes XIX-XXXII.

Science.gov (United States)

Pullin, Richard A.

1998-01-01

This annotated bibliography lists 310 articles from the "Journal of Cooperative Education" from Volumes XIX-XXXII, 1983-1997. Annotations are presented in the order they appear in the journal; author and subject indexes are provided. (JOW)

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.

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.

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).

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

Improving Microbial Genome Annotations in an Integrated Database Context

Science.gov (United States)

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

Improving microbial genome annotations in an integrated database context.

Directory of Open Access Journals (Sweden)

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/.

BAT: An open-source, web-based audio events annotation tool

OpenAIRE

Blai Meléndez-Catalan, Emilio Molina, Emilia Gómez

2017-01-01

In this paper we present BAT (BMAT Annotation Tool), an open-source, web-based tool for the manual annotation of events in audio recordings developed at BMAT (Barcelona Music and Audio Technologies). The main feature of the tool is that it provides an easy way to annotate the salience of simultaneous sound sources. Additionally, it allows to define multiple ontologies to adapt to multiple tasks and offers the possibility to cross-annotate audio data. Moreover, it is easy to install and deploy...

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.

Collaborative Paper-Based Annotation of Lecture Slides

Science.gov (United States)

Steimle, Jurgen; Brdiczka, Oliver; Muhlhauser, Max

2009-01-01

In a study of notetaking in university courses, we found that the large majority of students prefer paper to computer-based media like Tablet PCs for taking notes and making annotations. Based on this finding, we developed CoScribe, a concept and system which supports students in making collaborative handwritten annotations on printed lecture…

Music journals in South Africa 1854-2010: an annotated bibliography

African Journals Online (AJOL)

Music journals in South Africa 1854-2010: an annotated bibliography. ... The article focuses on presenting an annotated bibliography of music journalism in South Africa from as early as 1854 until 2010. Most of ... Key words: annotated bibliography, electronic journals, music journals, periodicals, South African music history ...

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.

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

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.

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.

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.

Curated genome annotation of Oryza sativa ssp. japonica and comparative genome analysis with Arabidopsis thaliana

Science.gov (United States)

Itoh, Takeshi; Tanaka, Tsuyoshi; Barrero, Roberto A.; Yamasaki, Chisato; Fujii, Yasuyuki; Hilton, Phillip B.; Antonio, Baltazar A.; Aono, Hideo; Apweiler, Rolf; Bruskiewich, Richard; Bureau, Thomas; Burr, Frances; Costa de Oliveira, Antonio; Fuks, Galina; Habara, Takuya; Haberer, Georg; Han, Bin; Harada, Erimi; Hiraki, Aiko T.; Hirochika, Hirohiko; Hoen, Douglas; Hokari, Hiroki; Hosokawa, Satomi; Hsing, Yue; Ikawa, Hiroshi; Ikeo, Kazuho; Imanishi, Tadashi; Ito, Yukiyo; Jaiswal, Pankaj; Kanno, Masako; Kawahara, Yoshihiro; Kawamura, Toshiyuki; Kawashima, Hiroaki; Khurana, Jitendra P.; Kikuchi, Shoshi; Komatsu, Setsuko; Koyanagi, Kanako O.; Kubooka, Hiromi; Lieberherr, Damien; Lin, Yao-Cheng; Lonsdale, David; Matsumoto, Takashi; Matsuya, Akihiro; McCombie, W. Richard; Messing, Joachim; Miyao, Akio; Mulder, Nicola; Nagamura, Yoshiaki; Nam, Jongmin; Namiki, Nobukazu; Numa, Hisataka; Nurimoto, Shin; O’Donovan, Claire; Ohyanagi, Hajime; Okido, Toshihisa; OOta, Satoshi; Osato, Naoki; Palmer, Lance E.; Quetier, Francis; Raghuvanshi, Saurabh; Saichi, Naomi; Sakai, Hiroaki; Sakai, Yasumichi; Sakata, Katsumi; Sakurai, Tetsuya; Sato, Fumihiko; Sato, Yoshiharu; Schoof, Heiko; Seki, Motoaki; Shibata, Michie; Shimizu, Yuji; Shinozaki, Kazuo; Shinso, Yuji; Singh, Nagendra K.; Smith-White, Brian; Takeda, Jun-ichi; Tanino, Motohiko; Tatusova, Tatiana; Thongjuea, Supat; Todokoro, Fusano; Tsugane, Mika; Tyagi, Akhilesh K.; Vanavichit, Apichart; Wang, Aihui; Wing, Rod A.; Yamaguchi, Kaori; Yamamoto, Mayu; Yamamoto, Naoyuki; Yu, Yeisoo; Zhang, Hao; Zhao, Qiang; Higo, Kenichi; Burr, Benjamin; Gojobori, Takashi; Sasaki, Takuji

2007-01-01

We present here the annotation of the complete genome of rice Oryza sativa L. ssp. japonica cultivar Nipponbare. All functional annotations for proteins and non-protein-coding RNA (npRNA) candidates were manually curated. Functions were identified or inferred in 19,969 (70%) of the proteins, and 131 possible npRNAs (including 58 antisense transcripts) were found. Almost 5000 annotated protein-coding genes were found to be disrupted in insertional mutant lines, which will accelerate future experimental validation of the annotations. The rice loci were determined by using cDNA sequences obtained from rice and other representative cereals. Our conservative estimate based on these loci and an extrapolation suggested that the gene number of rice is ∼32,000, which is smaller than previous estimates. We conducted comparative analyses between rice and Arabidopsis thaliana and found that both genomes possessed several lineage-specific genes, which might account for the observed differences between these species, while they had similar sets of predicted functional domains among the protein sequences. A system to control translational efficiency seems to be conserved across large evolutionary distances. Moreover, the evolutionary process of protein-coding genes was examined. Our results suggest that natural selection may have played a role for duplicated genes in both species, so that duplication was suppressed or favored in a manner that depended on the function of a gene. PMID:17210932

Annotating Logical Forms for EHR Questions.

Science.gov (United States)

Roberts, Kirk; Demner-Fushman, Dina

2016-05-01

This paper discusses the creation of a semantically annotated corpus of questions about patient data in electronic health records (EHRs). The goal is to provide the training data necessary for semantic parsers to automatically convert EHR questions into a structured query. A layered annotation strategy is used which mirrors a typical natural language processing (NLP) pipeline. First, questions are syntactically analyzed to identify multi-part questions. Second, medical concepts are recognized and normalized to a clinical ontology. Finally, logical forms are created using a lambda calculus representation. We use a corpus of 446 questions asking for patient-specific information. From these, 468 specific questions are found containing 259 unique medical concepts and requiring 53 unique predicates to represent the logical forms. We further present detailed characteristics of the corpus, including inter-annotator agreement results, and describe the challenges automatic NLP systems will face on this task.

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.

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

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.

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.

Multiview Hessian regularization for image annotation.

Science.gov (United States)

Liu, Weifeng; Tao, Dacheng

2013-07-01

The rapid development of computer hardware and Internet technology makes large scale data dependent models computationally tractable, and opens a bright avenue for annotating images through innovative machine learning algorithms. Semisupervised learning (SSL) therefore received intensive attention in recent years and was successfully deployed in image annotation. One representative work in SSL is Laplacian regularization (LR), which smoothes the conditional distribution for classification along the manifold encoded in the graph Laplacian, however, it is observed that LR biases the classification function toward a constant function that possibly results in poor generalization. In addition, LR is developed to handle uniformly distributed data (or single-view data), although instances or objects, such as images and videos, are usually represented by multiview features, such as color, shape, and texture. In this paper, we present multiview Hessian regularization (mHR) to address the above two problems in LR-based image annotation. In particular, mHR optimally combines multiple HR, each of which is obtained from a particular view of instances, and steers the classification function that varies linearly along the data manifold. We apply mHR to kernel least squares and support vector machines as two examples for image annotation. Extensive experiments on the PASCAL VOC'07 dataset validate the effectiveness of mHR by comparing it with baseline algorithms, including LR and HR.

Ten steps to get started in Genome Assembly and Annotation

Science.gov (United States)

Dominguez Del Angel, Victoria; Hjerde, Erik; Sterck, Lieven; Capella-Gutierrez, Salvadors; Notredame, Cederic; Vinnere Pettersson, Olga; Amselem, Joelle; Bouri, Laurent; Bocs, Stephanie; Klopp, Christophe; Gibrat, Jean-Francois; Vlasova, Anna; Leskosek, Brane L.; Soler, Lucile; Binzer-Panchal, Mahesh; Lantz, Henrik

2018-01-01

As a part of the ELIXIR-EXCELERATE efforts in capacity building, we present here 10 steps to facilitate researchers getting started in genome assembly and genome annotation. The guidelines given are broadly applicable, intended to be stable over time, and cover all aspects from start to finish of a general assembly and annotation project. Intrinsic properties of genomes are discussed, as is the importance of using high quality DNA. Different sequencing technologies and generally applicable workflows for genome assembly are also detailed. We cover structural and functional annotation and encourage readers to also annotate transposable elements, something that is often omitted from annotation workflows. The importance of data management is stressed, and we give advice on where to submit data and how to make your results Findable, Accessible, Interoperable, and Reusable (FAIR). PMID:29568489

Sharing Map Annotations in Small Groups: X Marks the Spot

Science.gov (United States)

Congleton, Ben; Cerretani, Jacqueline; Newman, Mark W.; Ackerman, Mark S.

Advances in location-sensing technology, coupled with an increasingly pervasive wireless Internet, have made it possible (and increasingly easy) to access and share information with context of one’s geospatial location. We conducted a four-phase study, with 27 students, to explore the practices surrounding the creation, interpretation and sharing of map annotations in specific social contexts. We found that annotation authors consider multiple factors when deciding how to annotate maps, including the perceived utility to the audience and how their contributions will reflect on the image they project to others. Consumers of annotations value the novelty of information, but must be convinced of the author’s credibility. In this paper we describe our study, present the results, and discuss implications for the design of software for sharing map annotations.

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.

Roadmap for annotating transposable elements in eukaryote genomes.

Science.gov (United States)

Permal, Emmanuelle; Flutre, Timothée; Quesneville, Hadi

2012-01-01

Current high-throughput techniques have made it feasible to sequence even the genomes of non-model organisms. However, the annotation process now represents a bottleneck to genome analysis, especially when dealing with transposable elements (TE). Combined approaches, using both de novo and knowledge-based methods to detect TEs, are likely to produce reasonably comprehensive and sensitive results. This chapter provides a roadmap for researchers involved in genome projects to address this issue. At each step of the TE annotation process, from the identification of TE families to the annotation of TE copies, we outline the tools and good practices to be used.

Annotated Bibliography of Publications on Watershed Management and Ecological Studies at Coweeta Hydrologic Laboratory, 1934-1994

Science.gov (United States)

Patricia L. Stickney; Lloyd W. Swift; Wayne T. Swank

1994-01-01

This annotated bibliography spans over60 years of research at Coweeta from 1934 through part of 1994, and includes earlier papers onforest influenteswritten atthe Appalachian Station beforethe establishment of Coweeta. It is a modification and update of previous compilations of research results at Coweeta and contains aseparatesection listing theses and dissertations....

Geomicrobiology and its relevance to nuclear waste disposal - a further annotated bibliography

International Nuclear Information System (INIS)

West, J.M.; Arme, S.C.

1984-07-01

Scientific investigations into the disposal of high/intermediate level radioactive waste into deep geological formations includes work in the field of geomicrobiology. It has been shown that microbes exist in deep and shallow geological formations and that they could alter the geochemical environment of a waste repository and influence radionuclide migration. A preliminary literature survey indicated a lack of annotated material and an initial report (West, McKinley and Christofi, 1982) provided the first bibliography. This report is an updated annotated bibliography of relevant geomicrobiological research published since 1982 and should be used in conjunction with the previous report. Those without specific biological experience may find the glossary of common terms in the initial report of use. A major area of work which has not been referenced widely here is near surface disposal of both radioactive and conventional industrial waste. This vast topic can be accessed via some of the general reviews in this report. (author)

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.

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.

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.

LeARN: a platform for detecting, clustering and annotating non-coding RNAs

Directory of Open Access Journals (Sweden)

Schiex Thomas

2008-01-01

Full Text Available Abstract Background In the last decade, sequencing projects have led to the development of a number of annotation systems dedicated to the structural and functional annotation of protein-coding genes. These annotation systems manage the annotation of the non-protein coding genes (ncRNAs in a very crude way, allowing neither the edition of the secondary structures nor the clustering of ncRNA genes into families which are crucial for appropriate annotation of these molecules. Results LeARN is a flexible software package which handles the complete process of ncRNA annotation by integrating the layers of automatic detection and human curation. Conclusion This software provides the infrastructure to deal properly with ncRNAs in the framework of any annotation project. It fills the gap between existing prediction software, that detect independent ncRNA occurrences, and public ncRNA repositories, that do not offer the flexibility and interactivity required for annotation projects. The software is freely available from the download section of the website http://bioinfo.genopole-toulouse.prd.fr/LeARN

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

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

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.

ONEMercury: Towards Automatic Annotation of Earth Science Metadata

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Tuarob, S.; Pouchard, L. C.; Noy, N.; Horsburgh, J. S.; Palanisamy, G.

2012-12-01

Earth sciences have become more data-intensive, requiring access to heterogeneous data collected from multiple places, times, and thematic scales. For example, research on climate change may involve exploring and analyzing observational data such as the migration of animals and temperature shifts across the earth, as well as various model-observation inter-comparison studies. Recently, DataONE, a federated data network built to facilitate access to and preservation of environmental and ecological data, has come to exist. ONEMercury has recently been implemented as part of the DataONE project to serve as a portal for discovering and accessing environmental and observational data across the globe. ONEMercury harvests metadata from the data hosted by multiple data repositories and makes it searchable via a common search interface built upon cutting edge search engine technology, allowing users to interact with the system, intelligently filter the search results on the fly, and fetch the data from distributed data sources. Linking data from heterogeneous sources always has a cost. A problem that ONEMercury faces is the different levels of annotation in the harvested metadata records. Poorly annotated records tend to be missed during the search process as they lack meaningful keywords. Furthermore, such records would not be compatible with the advanced search functionality offered by ONEMercury as the interface requires a metadata record be semantically annotated. The explosion of the number of metadata records harvested from an increasing number of data repositories makes it impossible to annotate the harvested records manually, urging the need for a tool capable of automatically annotating poorly curated metadata records. In this paper, we propose a topic-model (TM) based approach for automatic metadata annotation. Our approach mines topics in the set of well annotated records and suggests keywords for poorly annotated records based on topic similarity. We utilize the

A Selected Annotated Bibliography on Work Time Options.

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Ivantcho, Barbara

This annotated bibliography is divided into three sections. Section I contains annotations of general publications on work time options. Section II presents resources on flexitime and the compressed work week. In Section III are found resources related to these reduced work time options: permanent part-time employment, job sharing, voluntary…

Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites.

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Mahieu, Nathaniel G; Patti, Gary J

2017-10-03

When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is now routine to detect tens of thousands of features from biological samples. Poor understanding of the data, however, has complicated interpretation and masked the number of unique metabolites actually being measured in an experiment. Here we place an upper bound on the number of unique metabolites detected in Escherichia coli samples analyzed with one untargeted metabolomics method. We first group multiple features arising from the same analyte, which we call "degenerate features", using a context-driven annotation approach. Surprisingly, this analysis revealed thousands of previously unreported degeneracies that reduced the number of unique analytes to ∼2961. We then applied an orthogonal approach to remove nonbiological features from the data using the 13 C-based credentialing technology. This further reduced the number of unique analytes to less than 1000. Our 90% reduction in data is 5-fold greater than previously published studies. On the basis of the results, we propose an alternative approach to untargeted metabolomics that relies on thoroughly annotated reference data sets. To this end, we introduce the creDBle database ( http://creDBle.wustl.edu ), which contains accurate mass, retention time, and MS/MS fragmentation data as well as annotations of all credentialed features.

High-throughput proteogenomics of Ruegeria pomeroyi: seeding a better genomic annotation for the whole marine Roseobacter clade

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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

Prepare-Participate-Connect: Active Learning with Video Annotation

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Colasante, Meg; Douglas, Kathy

2016-01-01

Annotation of video provides students with the opportunity to view and engage with audiovisual content in an interactive and participatory way rather than in passive-receptive mode. This article discusses research into the use of video annotation in four vocational programs at RMIT University in Melbourne, which allowed students to interact with…

Developing Annotation Solutions for Online Data Driven Learning

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Perez-Paredes, Pascual; Alcaraz-Calero, Jose M.

2009-01-01

Although "annotation" is a widely-researched topic in Corpus Linguistics (CL), its potential role in Data Driven Learning (DDL) has not been addressed in depth by Foreign Language Teaching (FLT) practitioners. Furthermore, most of the research in the use of DDL methods pays little attention to annotation in the design and implementation…

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

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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.

Comparison of concept recognizers for building the Open Biomedical Annotator

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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.

Monitoring of radioactivity in the UK environment: an annotated bibliography of current programmes

International Nuclear Information System (INIS)

Cotter, A.J.R.; Hunt, G.J.

1992-01-01

In the UK, many organisations carry out regular radioactivity monitoring programmes, and summaries of these programmes have been published in 1983 and 1988. The number of organisations carrying out radioactivity monitoring has increased rapidly in recent years, particularly in the local authority sector. The present report updates the previous summarises in the form of an annotated bibliography, giving synopses of all regular UK programmes whose results are published in report form. (author)

IntelliGO: a new vector-based semantic similarity measure including annotation origin

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Devignes Marie-Dominique

2010-12-01

previously published measures. Conclusions The IntelliGO similarity measure provides a customizable and comprehensive method for quantifying gene similarity based on GO annotations. It also displays a robust set-discriminating power which suggests it will be useful for functional clustering. Availability An on-line version of the IntelliGO similarity measure is available at: http://bioinfo.loria.fr/Members/benabdsi/intelligo_project/

A Set of Annotation Interfaces for Alignment of Parallel Corpora

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Singh Anil Kumar

2014-09-01

Full Text Available Annotation interfaces for parallel corpora which fit in well with other tools can be very useful. We describe a set of annotation interfaces which fulfill this criterion. This set includes a sentence alignment interface, two different word or word group alignment interfaces and an initial version of a parallel syntactic annotation alignment interface. These tools can be used for manual alignment, or they can be used to correct automatic alignments. Manual alignment can be performed in combination with certain kinds of linguistic annotation. Most of these interfaces use a representation called the Shakti Standard Format that has been found to be very robust and has been used for large and successful projects. It ties together the different interfaces, so that the data created by them is portable across all tools which support this representation. The existence of a query language for data stored in this representation makes it possible to build tools that allow easy search and modification of annotated parallel data.

LocusTrack: Integrated visualization of GWAS results and genomic annotation.

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Cuellar-Partida, Gabriel; Renteria, Miguel E; MacGregor, Stuart

2015-01-01

Genome-wide association studies (GWAS) are an important tool for the mapping of complex traits and diseases. Visual inspection of genomic annotations may be used to generate insights into the biological mechanisms underlying GWAS-identified loci. We developed LocusTrack, a web-based application that annotates and creates plots of regional GWAS results and incorporates user-specified tracks that display annotations such as linkage disequilibrium (LD), phylogenetic conservation, chromatin state, and other genomic and regulatory elements. Currently, LocusTrack can integrate annotation tracks from the UCSC genome-browser as well as from any tracks provided by the user. LocusTrack is an easy-to-use application and can be accessed at the following URL: http://gump.qimr.edu.au/general/gabrieC/LocusTrack/. Users can upload and manage GWAS results and select from and/or provide annotation tracks using simple and intuitive menus. LocusTrack scripts and associated data can be downloaded from the website and run locally.

"Annotated Lectures": Student-Instructor Interaction in Large-Scale Global Education

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Roger Diehl

2009-10-01

Full Text Available We describe an "Annotated Lectures" system, which will be used in a global virtual teaching and student collaboration event on embodied intelligence presented by the University of Zurich. The lectures will be broadcasted via video-conference to lecture halls of different universities around the globe. Among other collaboration features, an "Annotated Lectures" system will be implemented in a 3D collaborative virtual environment and used by the participating students to make annotations to the video-recorded lectures, which will be sent to and answered by their supervisors, and forwarded to the lecturers in an aggregated way. The "Annotated Lectures" system aims to overcome the issues of limited studentinstructor interaction in large-scale education, and to foster an intercultural and multidisciplinary discourse among students who review the lectures in a group. After presenting the concept of the "Annotated Lectures" system, we discuss a prototype version including a description of the technical components and its expected benefit for large-scale global education.

Annotation an effective device for student feedback: a critical review of the literature.

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Ball, Elaine C

2010-05-01

The paper examines hand-written annotation, its many features, difficulties and strengths as a feedback tool. It extends and clarifies what modest evidence is in the public domain and offers an evaluation of how to use annotation effectively in the support of student feedback [Marshall, C.M., 1998a. The Future of Annotation in a Digital (paper) World. Presented at the 35th Annual GLSLIS Clinic: Successes and Failures of Digital Libraries, June 20-24, University of Illinois at Urbana-Champaign, March 24, pp. 1-20; Marshall, C.M., 1998b. Toward an ecology of hypertext annotation. Hypertext. In: Proceedings of the Ninth ACM Conference on Hypertext and Hypermedia, June 20-24, Pittsburgh Pennsylvania, US, pp. 40-49; Wolfe, J.L., Nuewirth, C.M., 2001. From the margins to the centre: the future of annotation. Journal of Business and Technical Communication, 15(3), 333-371; Diyanni, R., 2002. One Hundred Great Essays. Addison-Wesley, New York; Wolfe, J.L., 2002. Marginal pedagogy: how annotated texts affect writing-from-source texts. Written Communication, 19(2), 297-333; Liu, K., 2006. Annotation as an index to critical writing. Urban Education, 41, 192-207; Feito, A., Donahue, P., 2008. Minding the gap annotation as preparation for discussion. Arts and Humanities in Higher Education, 7(3), 295-307; Ball, E., 2009. A participatory action research study on handwritten annotation feedback and its impact on staff and students. Systemic Practice and Action Research, 22(2), 111-124; Ball, E., Franks, H., McGrath, M., Leigh, J., 2009. Annotation is a valuable tool to enhance learning and assessment in student essays. Nurse Education Today, 29(3), 284-291]. Although a significant number of studies examine annotation, this is largely related to on-line tools and computer mediated communication and not hand-written annotation as comment, phrase or sign written on the student essay to provide critique. Little systematic research has been conducted to consider how this latter form

Automatic Function Annotations for Hoare Logic

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Daniel Matichuk

2012-11-01

Full Text Available In systems verification we are often concerned with multiple, inter-dependent properties that a program must satisfy. To prove that a program satisfies a given property, the correctness of intermediate states of the program must be characterized. However, this intermediate reasoning is not always phrased such that it can be easily re-used in the proofs of subsequent properties. We introduce a function annotation logic that extends Hoare logic in two important ways: (1 when proving that a function satisfies a Hoare triple, intermediate reasoning is automatically stored as function annotations, and (2 these function annotations can be exploited in future Hoare logic proofs. This reduces duplication of reasoning between the proofs of different properties, whilst serving as a drop-in replacement for traditional Hoare logic to avoid the costly process of proof refactoring. We explain how this was implemented in Isabelle/HOL and applied to an experimental branch of the seL4 microkernel to significantly reduce the size and complexity of existing proofs.

Automatically Annotated Mapping for Indoor Mobile Robot Applications

DEFF Research Database (Denmark)

Özkil, Ali Gürcan; Howard, Thomas J.

2012-01-01

This paper presents a new and practical method for mapping and annotating indoor environments for mobile robot use. The method makes use of 2D occupancy grid maps for metric representation, and topology maps to indicate the connectivity of the ‘places-of-interests’ in the environment. Novel use...... localization and mapping in topology space, and fuses camera and robot pose estimations to build an automatically annotated global topo-metric map. It is developed as a framework for a hospital service robot and tested in a real hospital. Experiments show that the method is capable of producing globally...... consistent, automatically annotated hybrid metric-topological maps that is needed by mobile service robots....

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

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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.

An annotated corpus with nanomedicine and pharmacokinetic parameters

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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

Annotated Tsunami bibliography: 1962-1976

International Nuclear Information System (INIS)

Pararas-Carayannis, G.; Dong, B.; Farmer, R.

1982-08-01

This compilation contains annotated citations to nearly 3000 tsunami-related publications from 1962 to 1976 in English and several other languages. The foreign-language citations have English titles and abstracts

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.

Annotated genetic linkage maps of Pinus pinaster Ait. from a Central Spain population using microsatellite and gene based markers.

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de Miguel, Marina; de Maria, Nuria; Guevara, M Angeles; Diaz, Luis; Sáez-Laguna, Enrique; Sánchez-Gómez, David; Chancerel, Emilie; Aranda, Ismael; Collada, Carmen; Plomion, Christophe; Cabezas, José-Antonio; Cervera, María-Teresa

2012-10-04

Pinus pinaster Ait. is a major resin producing species in Spain. Genetic linkage mapping can facilitate marker-assisted selection (MAS) through the identification of Quantitative Trait Loci and selection of allelic variants of interest in breeding populations. In this study, we report annotated genetic linkage maps for two individuals (C14 and C15) belonging to a breeding program aiming to increase resin production. We use different types of DNA markers, including last-generation molecular markers. We obtained 13 and 14 linkage groups for C14 and C15 maps, respectively. A total of 211 and 215 markers were positioned on each map and estimated genome length was between 1,870 and 2,166 cM respectively, which represents near 65% of genome coverage. Comparative mapping with previously developed genetic linkage maps for P. pinaster based on about 60 common markers enabled aligning linkage groups to this reference map. The comparison of our annotated linkage maps and linkage maps reporting QTL information revealed 11 annotated SNPs in candidate genes that co-localized with previously reported QTLs for wood properties and water use efficiency. This study provides genetic linkage maps from a Spanish population that shows high levels of genetic divergence with French populations from which segregating progenies have been previously mapped. These genetic maps will be of interest to construct a reliable consensus linkage map for the species. The importance of developing functional genetic linkage maps is highlighted, especially when working with breeding populations for its future application in MAS for traits of interest.

Annotated genetic linkage maps of Pinus pinaster Ait. from a Central Spain population using microsatellite and gene based markers

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de Miguel Marina

2012-10-01

Full Text Available Abstract Background Pinus pinaster Ait. is a major resin producing species in Spain. Genetic linkage mapping can facilitate marker-assisted selection (MAS through the identification of Quantitative Trait Loci and selection of allelic variants of interest in breeding populations. In this study, we report annotated genetic linkage maps for two individuals (C14 and C15 belonging to a breeding program aiming to increase resin production. We use different types of DNA markers, including last-generation molecular markers. Results We obtained 13 and 14 linkage groups for C14 and C15 maps, respectively. A total of 211 and 215 markers were positioned on each map and estimated genome length was between 1,870 and 2,166 cM respectively, which represents near 65% of genome coverage. Comparative mapping with previously developed genetic linkage maps for P. pinaster based on about 60 common markers enabled aligning linkage groups to this reference map. The comparison of our annotated linkage maps and linkage maps reporting QTL information revealed 11 annotated SNPs in candidate genes that co-localized with previously reported QTLs for wood properties and water use efficiency. Conclusions This study provides genetic linkage maps from a Spanish population that shows high levels of genetic divergence with French populations from which segregating progenies have been previously mapped. These genetic maps will be of interest to construct a reliable consensus linkage map for the species. The importance of developing functional genetic linkage maps is highlighted, especially when working with breeding populations for its future application in MAS for traits of interest.

Inconsistencies of genome annotations in apicomplexan parasites revealed by 5'-end-one-pass and full-length sequences of oligo-capped cDNAs

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Sugano Sumio

2009-07-01

Full Text Available Abstract Background Apicomplexan parasites are causative agents of various diseases including malaria and have been targets of extensive genomic sequencing. We generated 5'-EST collections for six apicomplexa parasites using our full-length oligo-capping cDNA library method. To improve upon the current genome annotations, as well as to validate the importance for physical cDNA clone resources, we generated a large-scale collection of full-length cDNAs for several apicomplexa parasites. Results In this study, we used a total of 61,056 5'-end-single-pass cDNA sequences from Plasmodium falciparum, P. vivax, P. yoelii, P. berghei, Cryptosporidium parvum, and Toxoplasma gondii. We compared these partially sequenced cDNA sequences with the currently annotated gene models and observed significant inconsistencies between the two datasets. In particular, we found that on average 14% of the exons in the current gene models were not supported by any cDNA evidence, and that 16% of the current gene models may contain at least one mis-annotation and should be re-evaluated. We also identified a large number of transcripts that had been previously unidentified. For 732 cDNAs in T. gondii, the entire sequences were determined in order to evaluate the annotated gene models at the complete full-length transcript level. We found that 41% of the T. gondii gene models contained at least one inconsistency. We also identified and confirmed by RT-PCR 140 previously unidentified transcripts found in the intergenic regions of the current gene annotations. We show that the majority of these discrepancies are due to questionable predictions of one or two extra exons in the upstream or downstream regions of the genes. Conclusion Our data indicates that the current gene models are likely to still be incomplete and have much room for improvement. Our unique full-length cDNA information is especially useful for further refinement of the annotations for the genomes of

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...

Creating New Medical Ontologies for Image Annotation A Case Study

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Stanescu, Liana; Brezovan, Marius; Mihai, Cristian Gabriel

2012-01-01

Creating New Medical Ontologies for Image Annotation focuses on the problem of the medical images automatic annotation process, which is solved in an original manner by the authors. All the steps of this process are described in detail with algorithms, experiments and results. The original algorithms proposed by authors are compared with other efficient similar algorithms. In addition, the authors treat the problem of creating ontologies in an automatic way, starting from Medical Subject Headings (MESH). They have presented some efficient and relevant annotation models and also the basics of the annotation model used by the proposed system: Cross Media Relevance Models. Based on a text query the system will retrieve the images that contain objects described by the keywords.

Elucidating high-dimensional cancer hallmark annotation via enriched ontology.

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Yan, Shankai; Wong, Ka-Chun

2017-09-01

Cancer hallmark annotation is a promising technique that could discover novel knowledge about cancer from the biomedical literature. The automated annotation of cancer hallmarks could reveal relevant cancer transformation processes in the literature or extract the articles that correspond to the cancer hallmark of interest. It acts as a complementary approach that can retrieve knowledge from massive text information, advancing numerous focused studies in cancer research. Nonetheless, the high-dimensional nature of cancer hallmark annotation imposes a unique challenge. To address the curse of dimensionality, we compared multiple cancer hallmark annotation methods on 1580 PubMed abstracts. Based on the insights, a novel approach, UDT-RF, which makes use of ontological features is proposed. It expands the feature space via the Medical Subject Headings (MeSH) ontology graph and utilizes novel feature selections for elucidating the high-dimensional cancer hallmark annotation space. To demonstrate its effectiveness, state-of-the-art methods are compared and evaluated by a multitude of performance metrics, revealing the full performance spectrum on the full set of cancer hallmarks. Several case studies are conducted, demonstrating how the proposed approach could reveal novel insights into cancers. https://github.com/cskyan/chmannot. Copyright © 2017 Elsevier Inc. All rights reserved.

Rfam: annotating families of non-coding RNA sequences.

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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.

Intra-species sequence comparisons for annotating genomes

Energy Technology Data Exchange (ETDEWEB)

Boffelli, Dario; Weer, Claire V.; Weng, Li; Lewis, Keith D.; Shoukry, Malak I.; Pachter, Lior; Keys, David N.; Rubin, Edward M.

2004-07-15

Analysis of sequence variation among members of a single species offers a potential approach to identify functional DNA elements responsible for biological features unique to that species. Due to its high rate of allelic polymorphism and ease of genetic manipulability, we chose the sea squirt, Ciona intestinalis, to explore intra-species sequence comparisons for genome annotation. A large number of C. intestinalis specimens were collected from four continents and a set of genomic intervals amplified, resequenced and analyzed to determine the mutation rates at each nucleotide in the sequence. We found that regions with low mutation rates efficiently demarcated functionally constrained sequences: these include a set of noncoding elements, which we showed in C intestinalis transgenic assays to act as tissue-specific enhancers, as well as the location of coding sequences. This illustrates that comparisons of multiple members of a species can be used for genome annotation, suggesting a path for the annotation of the sequenced genomes of organisms occupying uncharacterized phylogenetic branches of the animal kingdom and raises the possibility that the resequencing of a large number of Homo sapiens individuals might be used to annotate the human genome and identify sequences defining traits unique to our species. The sequence data from this study has been submitted to GenBank under accession nos. AY667278-AY667407.

Annotation of two large contiguous regions from the Haemonchus contortus genome using RNA-seq and comparative analysis with Caenorhabditis elegans.

Directory of Open Access Journals (Sweden)

Roz Laing

Full Text Available The genomes of numerous parasitic nematodes are currently being sequenced, but their complexity and size, together with high levels of intra-specific sequence variation and a lack of reference genomes, makes their assembly and annotation a challenging task. Haemonchus contortus is an economically significant parasite of livestock that is widely used for basic research as well as for vaccine development and drug discovery. It is one of many medically and economically important parasites within the strongylid nematode group. This group of parasites has the closest phylogenetic relationship with the model organism Caenorhabditis elegans, making comparative analysis a potentially powerful tool for genome annotation and functional studies. To investigate this hypothesis, we sequenced two contiguous fragments from the H. contortus genome and undertook detailed annotation and comparative analysis with C. elegans. The adult H. contortus transcriptome was sequenced using an Illumina platform and RNA-seq was used to annotate a 409 kb overlapping BAC tiling path relating to the X chromosome and a 181 kb BAC insert relating to chromosome I. In total, 40 genes and 12 putative transposable elements were identified. 97.5% of the annotated genes had detectable homologues in C. elegans of which 60% had putative orthologues, significantly higher than previous analyses based on EST analysis. Gene density appears to be less in H. contortus than in C. elegans, with annotated H. contortus genes being an average of two-to-three times larger than their putative C. elegans orthologues due to a greater intron number and size. Synteny appears high but gene order is generally poorly conserved, although areas of conserved microsynteny are apparent. C. elegans operons appear to be partially conserved in H. contortus. Our findings suggest that a combination of RNA-seq and comparative analysis with C. elegans is a powerful approach for the annotation and analysis of strongylid

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

Directory of Open Access Journals (Sweden)

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

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.

Annotating risk factors for heart disease in clinical narratives for diabetic patients.

Science.gov (United States)

Stubbs, Amber; Uzuner, Özlem

2015-12-01

The 2014 i2b2/UTHealth natural language processing shared task featured a track focused on identifying risk factors for heart disease (specifically, Cardiac Artery Disease) in clinical narratives. For this track, we used a "light" annotation paradigm to annotate a set of 1304 longitudinal medical records describing 296 patients for risk factors and the times they were present. We designed the annotation task for this track with the goal of balancing annotation load and time with quality, so as to generate a gold standard corpus that can benefit a clinically-relevant task. We applied light annotation procedures and determined the gold standard using majority voting. On average, the agreement of annotators with the gold standard was above 0.95, indicating high reliability. The resulting document-level annotations generated for each record in each longitudinal EMR in this corpus provide information that can support studies of progression of heart disease risk factors in the included patients over time. These annotations were used in the Risk Factor track of the 2014 i2b2/UTHealth shared task. Participating systems achieved a mean micro-averaged F1 measure of 0.815 and a maximum F1 measure of 0.928 for identifying these risk factors in patient records. Copyright © 2015 Elsevier Inc. All rights reserved.

Annotating Emotions in Meetings

NARCIS (Netherlands)

Reidsma, Dennis; Heylen, Dirk K.J.; Ordelman, Roeland J.F.

We present the results of two trials testing procedures for the annotation of emotion and mental state of the AMI corpus. The first procedure is an adaptation of the FeelTrace method, focusing on a continuous labelling of emotion dimensions. The second method is centered around more discrete

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.

Consumer energy research: an annotated bibliography. Vol. 3

Energy Technology Data Exchange (ETDEWEB)

Anderson, D.C.; McDougall, G.H.G.

1983-04-01

This annotated bibliography attempts to provide a comprehensive package of existing information in consumer related energy research. A concentrated effort was made to collect unpublished material as well as material from journals and other sources, including governments, utilities research institutes and private firms. A deliberate effort was made to include agencies outside North America. For the most part the bibliography is limited to annotations of empiracal studies. However, it includes a number of descriptive reports which appear to make a significant contribution to understanding consumers and energy use. The format of the annotations displays the author, date of publication, title and source of the study. Annotations of empirical studies are divided into four parts: objectives, methods, variables and findings/implications. Care was taken to provide a reasonable amount of detail in the annotations to enable the reader to understand the methodology, the results and the degree to which the implications fo the study can be generalized to other situations. Studies are arranged alphabetically by author. The content of the studies reviewed is classified in a series of tables which are intended to provide a summary of sources, types and foci of the various studies. These tables are intended to aid researchers interested in specific topics to locate those studies most relevant to their work. The studies are categorized using a number of different classification criteria, for example, methodology used, type of energy form, type of policy initiative, and type of consumer activity. A general overview of the studies is also presented. 17 tabs.

Image annotation based on positive-negative instances learning

Science.gov (United States)

Zhang, Kai; Hu, Jiwei; Liu, Quan; Lou, Ping

2017-07-01

Automatic image annotation is now a tough task in computer vision, the main sense of this tech is to deal with managing the massive image on the Internet and assisting intelligent retrieval. This paper designs a new image annotation model based on visual bag of words, using the low level features like color and texture information as well as mid-level feature as SIFT, and mixture the pic2pic, label2pic and label2label correlation to measure the correlation degree of labels and images. We aim to prune the specific features for each single label and formalize the annotation task as a learning process base on Positive-Negative Instances Learning. Experiments are performed using the Corel5K Dataset, and provide a quite promising result when comparing with other existing methods.

An Annotated Dataset of 14 Meat Images

DEFF Research Database (Denmark)

Stegmann, Mikkel Bille

2002-01-01

This note describes a dataset consisting of 14 annotated images of meat. Points of correspondence are placed on each image. As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given.......This note describes a dataset consisting of 14 annotated images of meat. Points of correspondence are placed on each image. As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given....

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

Science.gov (United States)

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

An annotated checklist of Odonata (Insecta of Kanha Tiger Reserve and adjoining areas, central India

Directory of Open Access Journals (Sweden)

P.K. Sahoo

2013-01-01

Full Text Available Odonates were recorded from Kanha Tiger Reserve and its adjoining areas during January-December 2010. Thirty eight species were recorded belonging to seven families and 26 genera. Twelve species distribution is first time recorded from the reserve. With the addition of these newly recorded species with the previous records the species richness of the reserve increased up to 48 species, belonging to eight families. Among the collected Anisopterans Orthretum sabina sabina (Drury was the most abundant species. A detailed annotated checklist of recorded odonates with the previous records is presented in the Table.

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.

An efficient annotation and gene-expression derivation tool for Illumina Solexa datasets.

Science.gov (United States)

Hosseini, Parsa; Tremblay, Arianne; Matthews, Benjamin F; Alkharouf, Nadim W

2010-07-02

The data produced by an Illumina flow cell with all eight lanes occupied, produces well over a terabyte worth of images with gigabytes of reads following sequence alignment. The ability to translate such reads into meaningful annotation is therefore of great concern and importance. Very easily, one can get flooded with such a great volume of textual, unannotated data irrespective of read quality or size. CASAVA, a optional analysis tool for Illumina sequencing experiments, enables the ability to understand INDEL detection, SNP information, and allele calling. To not only extract from such analysis, a measure of gene expression in the form of tag-counts, but furthermore to annotate such reads is therefore of significant value. We developed TASE (Tag counting and Analysis of Solexa Experiments), a rapid tag-counting and annotation software tool specifically designed for Illumina CASAVA sequencing datasets. Developed in Java and deployed using jTDS JDBC driver and a SQL Server backend, TASE provides an extremely fast means of calculating gene expression through tag-counts while annotating sequenced reads with the gene's presumed function, from any given CASAVA-build. Such a build is generated for both DNA and RNA sequencing. Analysis is broken into two distinct components: DNA sequence or read concatenation, followed by tag-counting and annotation. The end result produces output containing the homology-based functional annotation and respective gene expression measure signifying how many times sequenced reads were found within the genomic ranges of functional annotations. TASE is a powerful tool to facilitate the process of annotating a given Illumina Solexa sequencing dataset. Our results indicate that both homology-based annotation and tag-count analysis are achieved in very efficient times, providing researchers to delve deep in a given CASAVA-build and maximize information extraction from a sequencing dataset. TASE is specially designed to translate sequence data

BEACON: automated tool for Bacterial GEnome Annotation ComparisON

KAUST Repository

Kalkatawi, Manal M.; Alam, Intikhab; Bajic, Vladimir B.

2015-01-01

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/

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

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

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.

Annotating the Function of the Human Genome with Gene Ontology and Disease Ontology.

Science.gov (United States)

Hu, Yang; Zhou, Wenyang; Ren, Jun; Dong, Lixiang; Wang, Yadong; Jin, Shuilin; Cheng, Liang

2016-01-01

Increasing evidences indicated that function annotation of human genome in molecular level and phenotype level is very important for systematic analysis of genes. In this study, we presented a framework named Gene2Function to annotate Gene Reference into Functions (GeneRIFs), in which each functional description of GeneRIFs could be annotated by a text mining tool Open Biomedical Annotator (OBA), and each Entrez gene could be mapped to Human Genome Organisation Gene Nomenclature Committee (HGNC) gene symbol. After annotating all the records about human genes of GeneRIFs, 288,869 associations between 13,148 mRNAs and 7,182 terms, 9,496 associations between 948 microRNAs and 533 terms, and 901 associations between 139 long noncoding RNAs (lncRNAs) and 297 terms were obtained as a comprehensive annotation resource of human genome. High consistency of term frequency of individual gene (Pearson correlation = 0.6401, p = 2.2e - 16) and gene frequency of individual term (Pearson correlation = 0.1298, p = 3.686e - 14) in GeneRIFs and GOA shows our annotation resource is very reliable.

Annotation: The Savant Syndrome

Science.gov (United States)

Heaton, Pamela; Wallace, Gregory L.

2004-01-01

Background: Whilst interest has focused on the origin and nature of the savant syndrome for over a century, it is only within the past two decades that empirical group studies have been carried out. Methods: The following annotation briefly reviews relevant research and also attempts to address outstanding issues in this research area.…

Analysis of LYSA-calculus with explicit confidentiality annotations

DEFF Research Database (Denmark)

Gao, Han; Nielson, Hanne Riis

2006-01-01

Recently there has been an increased research interest in applying process calculi in the verification of cryptographic protocols due to their ability to formally model protocols. This work presents LYSA with explicit confidentiality annotations for indicating the expected behavior of target...... malicious activities performed by attackers as specified by the confidentiality annotations. The proposed analysis approach is fully automatic without the need of human intervention and has been applied successfully to a number of protocols....

First generation annotations for the fathead minnow (Pimephales promelas) genome

Science.gov (United States)

Ab initio gene prediction and evidence alignment were used to produce the first annotations for the fathead minnow SOAPdenovo genome assembly. Additionally, a genome browser hosted at genome.setac.org provides simplified access to the annotation data in context with fathead minno...

Identification of neglected cestode Taenia multiceps microRNAs by illumina sequencing and bioinformatic analysis

Science.gov (United States)

2013-01-01

Background Worldwide, but especially in developing countries, coenurosis of sheep and other livestock is caused by Taenia multiceps larvae, and zoonotic infections occur in humans. Infections frequently lead to host death, resulting in huge socioeconomic losses. MicroRNAs (miRNAs) have important roles in the post-transcriptional regulation of a large number of animal genes by imperfectly binding target mRNAs. To date, there have been no reports of miRNAs in T. multiceps. Results In this study, we obtained 12.8 million high quality raw reads from adult T. multiceps small RNA library using Illumina sequencing technology. A total of 796 conserved miRNA families (containing 1,006 miRNAs) from 170,888 unique miRNAs were characterized using miRBase (Release 17.0). Here, we selected three conserved miRNA/miRNA* (antisense strand) duplexes at random and amplified their corresponding precursors using a PCR-based method. Furthermore, 20 candidate novel miRNA precursors were verified by genomic PCR. Among these, six corresponding T. multiceps miRNAs are considered specific for Taeniidae because no homologs were found in other species annotated in miRBase. In addition, 181,077 target sites within T. multiceps transcriptome were predicted for 20 candidate newly miRNAs. Conclusions Our large-scale investigation of miRNAs in adult T. multiceps provides a substantial platform for improving our understanding of the molecular regulation of T. multiceps and other cestodes development. PMID:23941076

Jannovar: a java library for exome annotation.

Science.gov (United States)

Jäger, Marten; Wang, Kai; Bauer, Sebastian; Smedley, Damian; Krawitz, Peter; Robinson, Peter N

2014-05-01

Transcript-based annotation and pedigree analysis are two basic steps in the computational analysis of whole-exome sequencing experiments in genetic diagnostics and disease-gene discovery projects. Here, we present Jannovar, a stand-alone Java application as well as a Java library designed to be used in larger software frameworks for exome and genome analysis. Jannovar uses an interval tree to identify all transcripts affected by a given variant, and provides Human Genome Variation Society-compliant annotations both for variants affecting coding sequences and splice junctions as well as untranslated regions and noncoding RNA transcripts. Jannovar can also perform family-based pedigree analysis with Variant Call Format (VCF) files with data from members of a family segregating a Mendelian disorder. Using a desktop computer, Jannovar requires a few seconds to annotate a typical VCF file with exome data. Jannovar is freely available under the BSD2 license. Source code as well as the Java application and library file can be downloaded from http://compbio.charite.de (with tutorial) and https://github.com/charite/jannovar. © 2014 WILEY PERIODICALS, INC.

Linking Disparate Datasets of the Earth Sciences with the SemantEco Annotator

Science.gov (United States)

Seyed, P.; Chastain, K.; McGuinness, D. L.

2013-12-01

Use of Semantic Web technologies for data management in the Earth sciences (and beyond) has great potential but is still in its early stages, since the challenges of translating data into a more explicit or semantic form for immediate use within applications has not been fully addressed. In this abstract we help address this challenge by introducing the SemantEco Annotator, which enables anyone, regardless of expertise, to semantically annotate tabular Earth Science data and translate it into linked data format, while applying the logic inherent in community-standard vocabularies to guide the process. The Annotator was conceived under a desire to unify dataset content from a variety of sources under common vocabularies, for use in semantically-enabled web applications. Our current use case employs linked data generated by the Annotator for use in the SemantEco environment, which utilizes semantics to help users explore, search, and visualize water or air quality measurement and species occurrence data through a map-based interface. The generated data can also be used immediately to facilitate discovery and search capabilities within 'big data' environments. The Annotator provides a method for taking information about a dataset, that may only be known to its maintainers, and making it explicit, in a uniform and machine-readable fashion, such that a person or information system can more easily interpret the underlying structure and meaning. Its primary mechanism is to enable a user to formally describe how columns of a tabular dataset relate and/or describe entities. For example, if a user identifies columns for latitude and longitude coordinates, we can infer the data refers to a point that can be plotted on a map. Further, it can be made explicit that measurements of 'nitrate' and 'NO3-' are of the same entity through vocabulary assignments, thus more easily utilizing data sets that use different nomenclatures. The Annotator provides an extensive and searchable

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.

Automated evaluation of annotators for museum collections using subjective login

NARCIS (Netherlands)

Ceolin, D.; Nottamkandath, A.; Fokkink, W.J.; Dimitrakos, Th.; Moona, R.; Patel, Dh.; Harrison McKnight, D.

2012-01-01

Museums are rapidly digitizing their collections, and face a huge challenge to annotate every digitized artifact in store. Therefore they are opening up their archives for receiving annotations from experts world-wide. This paper presents an architecture for choosing the most eligible set of

Annotation of the protein coding regions of the equine genome

DEFF Research Database (Denmark)

Hestand, Matthew S.; Kalbfleisch, Theodore S.; Coleman, Stephen J.

2015-01-01

Current gene annotation of the horse genome is largely derived from in silico predictions and cross-species alignments. Only a small number of genes are annotated based on equine EST and mRNA sequences. To expand the number of equine genes annotated from equine experimental evidence, we sequenced m...... and appear to be small errors in the equine reference genome, since they are also identified as homozygous variants by genomic DNA resequencing of the reference horse. Taken together, we provide a resource of equine mRNA structures and protein coding variants that will enhance equine and cross...

Genome Annotation and Transcriptomics of Oil-Producing Algae

Science.gov (United States)

2015-03-16

AFRL-OSR-VA-TR-2015-0103 GENOME ANNOTATION AND TRANSCRIPTOMICS OF OIL-PRODUCING ALGAE Sabeeha Merchant UNIVERSITY OF CALIFORNIA LOS ANGELES Final...2010 To 12-31-2014 4. TITLE AND SUBTITLE GENOME ANNOTATION AND TRANSCRIPTOMICS OF OIL-PRODUCING ALGAE 5a. CONTRACT NUMBER FA9550-10-1-0095 5b...NOTES 14. ABSTRACT Most algae accumulate triacylglycerols (TAGs) when they are starved for essential nutrients like N, S, P (or Si in the case of some

Estimating gene gain and loss rates in the presence of error in genome assembly and annotation using CAFE 3.

Science.gov (United States)

Han, Mira V; Thomas, Gregg W C; Lugo-Martinez, Jose; Hahn, Matthew W

2013-08-01

Current sequencing methods produce large amounts of data, but genome assemblies constructed from these data are often fragmented and incomplete. Incomplete and error-filled assemblies result in many annotation errors, especially in the number of genes present in a genome. This means that methods attempting to estimate rates of gene duplication and loss often will be misled by such errors and that rates of gene family evolution will be consistently overestimated. Here, we present a method that takes these errors into account, allowing one to accurately infer rates of gene gain and loss among genomes even with low assembly and annotation quality. The method is implemented in the newest version of the software package CAFE, along with several other novel features. We demonstrate the accuracy of the method with extensive simulations and reanalyze several previously published data sets. Our results show that errors in genome annotation do lead to higher inferred rates of gene gain and loss but that CAFE 3 sufficiently accounts for these errors to provide accurate estimates of important evolutionary parameters.

Annotating smart environment sensor data for activity learning.

Science.gov (United States)

Szewcyzk, S; Dwan, K; Minor, B; Swedlove, B; Cook, D

2009-01-01

The pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals experiencing difficulties living independently at home. In order to monitor the functional health of smart home residents, we need to design technologies that recognize and track the activities that people perform at home. Machine learning techniques can perform this task, but the software algorithms rely upon large amounts of sample data that is correctly labeled with the corresponding activity. Labeling, or annotating, sensor data with the corresponding activity can be time consuming, may require input from the smart home resident, and is often inaccurate. Therefore, in this paper we investigate four alternative mechanisms for annotating sensor data with a corresponding activity label. We evaluate the alternative methods along the dimensions of annotation time, resident burden, and accuracy using sensor data collected in a real smart apartment.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Software for computing and annotating genomic ranges.

Science.gov (United States)

Lawrence, Michael; Huber, Wolfgang; Pagès, Hervé; Aboyoun, Patrick; Carlson, Marc; Gentleman, Robert; Morgan, Martin T; Carey, Vincent J

2013-01-01

We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation.

Science.gov (United States)

Bolleman, Jerven T; Mungall, Christopher J; Strozzi, Francesco; Baran, Joachim; Dumontier, Michel; Bonnal, Raoul J P; Buels, Robert; Hoehndorf, Robert; Fujisawa, Takatomo; Katayama, Toshiaki; Cock, Peter J A

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. We have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned "omics" areas. Using the same data format to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe - and potentially merge - sequence annotations from multiple sources. Data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.

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.

Online Metacognitive Strategies, Hypermedia Annotations, and Motivation on Hypertext Comprehension

Science.gov (United States)

Shang, Hui-Fang

2016-01-01

This study examined the effect of online metacognitive strategies, hypermedia annotations, and motivation on reading comprehension in a Taiwanese hypertext environment. A path analysis model was proposed based on the assumption that if English as a foreign language learners frequently use online metacognitive strategies and hypermedia annotations,…

Annotating with Propp's Morphology of the Folktale: Reproducibility and Trainability

NARCIS (Netherlands)

Fisseni, B.; Kurji, A.; Löwe, B.

2014-01-01

We continue the study of the reproducibility of Propp’s annotations from Bod et al. (2012). We present four experiments in which test subjects were taught Propp’s annotation system; we conclude that Propp’s system needs a significant amount of training, but that with sufficient time investment, it

Annotation of nerve cord transcriptome in earthworm Eisenia fetida

Directory of Open Access Journals (Sweden)

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.

A topic modeling approach for web service annotation

Directory of Open Access Journals (Sweden)

Leandro Ordóñez-Ante

2014-06-01

Full Text Available The actual implementation of semantic-based mechanisms for service retrieval has been restricted, given the resource-intensive procedure involved in the formal specification of services, which generally comprises associating semantic annotations to their documentation sources. Typically, developer performs such a procedure by hand, requiring specialized knowledge on models for semantic description of services (e.g. OWL-S, WSMO, SAWSDL, as well as formal specifications of knowledge. Thus, this semantic-based service description procedure turns out to be a cumbersome and error-prone task. This paper introduces a proposal for service annotation, based on processing web service documentation for extracting information regarding its offered capabilities. By uncovering the hidden semantic structure of such information through statistical analysis techniques, we are able to associate meaningful annotations to the services operations/resources, while grouping those operations into non-exclusive semantic related categories. This research paper belongs to the TelComp 2.0 project, which Colciencas and University of Cauca founded in cooperation.

Tagging like Humans: Diverse and Distinct Image Annotation

KAUST Repository

Wu, Baoyuan

2018-03-31

In this work we propose a new automatic image annotation model, dubbed {\\\\bf diverse and distinct image annotation} (D2IA). The generative model D2IA is inspired by the ensemble of human annotations, which create semantically relevant, yet distinct and diverse tags. In D2IA, we generate a relevant and distinct tag subset, in which the tags are relevant to the image contents and semantically distinct to each other, using sequential sampling from a determinantal point process (DPP) model. Multiple such tag subsets that cover diverse semantic aspects or diverse semantic levels of the image contents are generated by randomly perturbing the DPP sampling process. We leverage a generative adversarial network (GAN) model to train D2IA. Extensive experiments including quantitative and qualitative comparisons, as well as human subject studies, on two benchmark datasets demonstrate that the proposed model can produce more diverse and distinct tags than the state-of-the-arts.

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)

2011-06-14

The following annotated bibliography was developed as part of the Geospatial Algorithm Veri cation and Validation (GSV) project for the Simulation, Algorithms and Modeling program of NA-22. Veri cation and Validation of geospatial image analysis algorithms covers a wide range of technologies. Papers in the bibliography are thus organized into the following ve 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.

The integration of a metadata generation framework in a music annotation workflow

OpenAIRE

Corthaut, Nik; Lippens, Stefaan; Govaerts, Sten; Duval, Erik; Martens, Jean-Pierre

2009-01-01

In the MuziK project we try to automate the typically hard task of annotating music files manually. This annotation is used for music recommendation and for automated playlist creation. The music experts of Aristo Music (http://www.aristomusic.com) defined the data fields. High quality annotations are required since the results, playlists, are used in commercial live settings and the cost of a wrong selection is high [1].

Automatic annotation of lecture videos for multimedia driven pedagogical platforms

Directory of Open Access Journals (Sweden)

Ali Shariq Imran

2016-12-01

Full Text Available Today’s eLearning websites are heavily loaded with multimedia contents, which are often unstructured, unedited, unsynchronized, and lack inter-links among different multimedia components. Hyperlinking different media modality may provide a solution for quick navigation and easy retrieval of pedagogical content in media driven eLearning websites. In addition, finding meta-data information to describe and annotate media content in eLearning platforms is challenging, laborious, prone to errors, and time-consuming task. Thus annotations for multimedia especially of lecture videos became an important part of video learning objects. To address this issue, this paper proposes three major contributions namely, automated video annotation, the 3-Dimensional (3D tag clouds, and the hyper interactive presenter (HIP eLearning platform. Combining existing state-of-the-art SIFT together with tag cloud, a novel approach for automatic lecture video annotation for the HIP is proposed. New video annotations are implemented automatically providing the needed random access in lecture videos within the platform, and a 3D tag cloud is proposed as a new way of user interaction mechanism. A preliminary study of the usefulness of the system has been carried out, and the initial results suggest that 70% of the students opted for using HIP as their preferred eLearning platform at Gjøvik University College (GUC.

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.

Combining rules, background knowledge and change patterns to maintain semantic annotations.

Science.gov (United States)

Cardoso, Silvio Domingos; Chantal, Reynaud-Delaître; Da Silveira, Marcos; Pruski, Cédric

2017-01-01

Knowledge Organization Systems (KOS) play a key role in enriching biomedical information in order to make it machine-understandable and shareable. This is done by annotating medical documents, or more specifically, associating concept labels from KOS with pieces of digital information, e.g., images or texts. However, the dynamic nature of KOS may impact the annotations, thus creating a mismatch between the evolved concept and the associated information. To solve this problem, methods to maintain the quality of the annotations are required. In this paper, we define a framework based on rules, background knowledge and change patterns to drive the annotation adaption process. We evaluate experimentally the proposed approach in realistic cases-studies and demonstrate the overall performance of our approach in different KOS considering the precision, recall, F1-score and AUC value of the system.

Phylogenetic molecular function annotation

International Nuclear Information System (INIS)

Engelhardt, Barbara E; Jordan, Michael I; Repo, Susanna T; Brenner, Steven E

2009-01-01

It is now easier to discover thousands of protein sequences in a new microbial genome than it is to biochemically characterize the specific activity of a single protein of unknown function. The molecular functions of protein sequences have typically been predicted using homology-based computational methods, which rely on the principle that homologous proteins share a similar function. However, some protein families include groups of proteins with different molecular functions. A phylogenetic approach for predicting molecular function (sometimes called 'phylogenomics') is an effective means to predict protein molecular function. These methods incorporate functional evidence from all members of a family that have functional characterizations using the evolutionary history of the protein family to make robust predictions for the uncharacterized proteins. However, they are often difficult to apply on a genome-wide scale because of the time-consuming step of reconstructing the phylogenies of each protein to be annotated. Our automated approach for function annotation using phylogeny, the SIFTER (Statistical Inference of Function Through Evolutionary Relationships) methodology, uses a statistical graphical model to compute the probabilities of molecular functions for unannotated proteins. Our benchmark tests showed that SIFTER provides accurate functional predictions on various protein families, outperforming other available methods.

Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization

Science.gov (United States)

Misirli, Goksel; Cavaliere, Matteo; Waites, William; Pocock, Matthew; Madsen, Curtis; Gilfellon, Owen; Honorato-Zimmer, Ricardo; Zuliani, Paolo; Danos, Vincent; Wipat, Anil

2016-01-01

Motivation: Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. Results: We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general. Availability and implementation: The annotation ontology for rule-based models can be found at http

Protein Annotators' Assistant: A Novel Application of Information Retrieval Techniques.

Science.gov (United States)

Wise, Michael J.

2000-01-01

Protein Annotators' Assistant (PAA) is a software system which assists protein annotators in assigning functions to newly sequenced proteins. PAA employs a number of information retrieval techniques in a novel setting and is thus related to text categorization, where multiple categories may be suggested, except that in this case none of the…

Crowdsourcing Twitter annotations to identify first-hand experiences of prescription drug use.

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Alvaro, Nestor; Conway, Mike; Doan, Son; Lofi, Christoph; Overington, John; Collier, Nigel

2015-12-01

Self-reported patient data has been shown to be a valuable knowledge source for post-market pharmacovigilance. In this paper we propose using the popular micro-blogging service Twitter to gather evidence about adverse drug reactions (ADRs) after firstly having identified micro-blog messages (also know as "tweets") that report first-hand experience. In order to achieve this goal we explore machine learning with data crowdsourced from laymen annotators. With the help of lay annotators recruited from CrowdFlower we manually annotated 1548 tweets containing keywords related to two kinds of drugs: SSRIs (eg. Paroxetine), and cognitive enhancers (eg. Ritalin). Our results show that inter-annotator agreement (Fleiss' kappa) for crowdsourcing ranks in moderate agreement with a pair of experienced annotators (Spearman's Rho=0.471). We utilized the gold standard annotations from CrowdFlower for automatically training a range of supervised machine learning models to recognize first-hand experience. F-Score values are reported for 6 of these techniques with the Bayesian Generalized Linear Model being the best (F-Score=0.64 and Informedness=0.43) when combined with a selected set of features obtained by using information gain criteria. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Multi-Label Classification Based on Low Rank Representation for Image Annotation

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Qiaoyu Tan

2017-01-01

Full Text Available Annotating remote sensing images is a challenging task for its labor demanding annotation process and requirement of expert knowledge, especially when images can be annotated with multiple semantic concepts (or labels. To automatically annotate these multi-label images, we introduce an approach called Multi-Label Classification based on Low Rank Representation (MLC-LRR. MLC-LRR firstly utilizes low rank representation in the feature space of images to compute the low rank constrained coefficient matrix, then it adapts the coefficient matrix to define a feature-based graph and to capture the global relationships between images. Next, it utilizes low rank representation in the label space of labeled images to construct a semantic graph. Finally, these two graphs are exploited to train a graph-based multi-label classifier. To validate the performance of MLC-LRR against other related graph-based multi-label methods in annotating images, we conduct experiments on a public available multi-label remote sensing images (Land Cover. We perform additional experiments on five real-world multi-label image datasets to further investigate the performance of MLC-LRR. Empirical study demonstrates that MLC-LRR achieves better performance on annotating images than these comparing methods across various evaluation criteria; it also can effectively exploit global structure and label correlations of multi-label images.

Software for computing and annotating genomic ranges.

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Michael Lawrence

Full Text Available We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.

Consumer energy research: an annotated bibliography

Energy Technology Data Exchange (ETDEWEB)

Anderson, C.D.; McDougall, G.H.G.

1980-01-01

This document is an updated and expanded version of an earlier annotated bibliography by Dr. C. Dennis Anderson and Carman Cullen (A Review and Annotation of Energy Research on Consumers, March 1978). It is the final draft of the major report that will be published in English and French and made publicly available through the Consumer Research and Evaluation Branch of Consumer and Corporate Affairs, Canada. Two agencies granting permission to include some of their energy abstracts are the Rand Corporation and the DOE Technical Information Center. The bibliography consists mainly of empirical studies, including surveys and experiments. It also includes a number of descriptive and econometric studies that utilize secondary data. Many of the studies provide summaries of research is specific areas, and point out directions for future research efforts. 14 tables.

Public Relations: Selected, Annotated Bibliography.

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Demo, Penny

Designed for students and practitioners of public relations (PR), this annotated bibliography focuses on recent journal articles and ERIC documents. The 34 citations include the following: (1) surveys of public relations professionals on career-related education; (2) literature reviews of research on measurement and evaluation of PR and…

Persuasion: A Selected, Annotated Bibliography.

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McDermott, Steven T.

Designed to reflect the diversity of approaches to persuasion, this annotated bibliography cites materials selected for their contribution to that diversity as well as for being relatively current and/or especially significant representatives of particular approaches. The bibliography starts with a list of 17 general textbooks on approaches to…

Automatic Annotation Method on Learners' Opinions in Case Method Discussion

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Samejima, Masaki; Hisakane, Daichi; Komoda, Norihisa

2015-01-01

Purpose: The purpose of this paper is to annotate an attribute of a problem, a solution or no annotation on learners' opinions automatically for supporting the learners' discussion without a facilitator. The case method aims at discussing problems and solutions in a target case. However, the learners miss discussing some of problems and solutions.…

High-performance web services for querying gene and variant annotation.

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Xin, Jiwen; Mark, Adam; Afrasiabi, Cyrus; Tsueng, Ginger; Juchler, Moritz; Gopal, Nikhil; Stupp, Gregory S; Putman, Timothy E; Ainscough, Benjamin J; Griffith, Obi L; Torkamani, Ali; Whetzel, Patricia L; Mungall, Christopher J; Mooney, Sean D; Su, Andrew I; Wu, Chunlei

2016-05-06

Efficient tools for data management and integration are essential for many aspects of high-throughput biology. In particular, annotations of genes and human genetic variants are commonly used but highly fragmented across many resources. Here, we describe MyGene.info and MyVariant.info, high-performance web services for querying gene and variant annotation information. These web services are currently accessed more than three million times permonth. They also demonstrate a generalizable cloud-based model for organizing and querying biological annotation information. MyGene.info and MyVariant.info are provided as high-performance web services, accessible at http://mygene.info and http://myvariant.info . Both are offered free of charge to the research community.

Modeling multiple time series annotations as noisy distortions of the ground truth: An Expectation-Maximization approach.

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Gupta, Rahul; Audhkhasi, Kartik; Jacokes, Zach; Rozga, Agata; Narayanan, Shrikanth

2018-01-01

Studies of time-continuous human behavioral phenomena often rely on ratings from multiple annotators. Since the ground truth of the target construct is often latent, the standard practice is to use ad-hoc metrics (such as averaging annotator ratings). Despite being easy to compute, such metrics may not provide accurate representations of the underlying construct. In this paper, we present a novel method for modeling multiple time series annotations over a continuous variable that computes the ground truth by modeling annotator specific distortions. We condition the ground truth on a set of features extracted from the data and further assume that the annotators provide their ratings as modification of the ground truth, with each annotator having specific distortion tendencies. We train the model using an Expectation-Maximization based algorithm and evaluate it on a study involving natural interaction between a child and a psychologist, to predict confidence ratings of the children's smiles. We compare and analyze the model against two baselines where: (i) the ground truth in considered to be framewise mean of ratings from various annotators and, (ii) each annotator is assumed to bear a distinct time delay in annotation and their annotations are aligned before computing the framewise mean.

AUTHOR’S ANNOTATION AS A MANIFESTATION OF THE COMPOSER’S CREATIVE CONCEPTION

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CIOBANU GHENADIE

2015-06-01

Full Text Available Annotation to his own musical works is considered by the author as a form of analysis of these opuses. Designed to provide answers about works, these comments facilitate the perception of contemporary music by performers and the audience. The composer examines various forms of annotations basing himself on their goals and the context of use, and compares them to other genres with informative function, such as the interview, analytical essay, memoirs, personal diary, etc. The article illustrated some possible forms of annotations. Besides a purely informative character of the annotation, the author notes in the conclusions the value of genuine professional analysis, providing a wide circle of listeners and experts with a brief exegetical approach to his musical works.

Annotated Bibliography of MMPI Research Among College Populations: 1962-1970.

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Cornish, Richard D.

The MMPI continues to be the focus of a large quantity of research. This article offers an aid to persons working with college student populations by annotating recent MMPI research relating to college populations. A total of 49 articles (each categorized in terms of content into one of 10 sections or subsections) were annotated. The Validity of…

ePNK Applications and Annotations

DEFF Research Database (Denmark)

Kindler, Ekkart

2017-01-01

newapplicationsfor the ePNK and, in particular, visualizing the result of an application in the graphical editor of the ePNK by singannotations, and interacting with the end user using these annotations. In this paper, we give an overview of the concepts of ePNK applications by discussing the implementation...

miRMaid: a unified programming interface for microRNA data resources

DEFF Research Database (Denmark)

Jacobsen, Anders; Krogh, Anders; Kauppinen, Sakari

2010-01-01

miRBase data as inter-connected web services. Third-party miRNA data resources can be modularly integrated as miRMaid plugins or they can loosely couple with miRMaid as individual entities in the World Wide Web. miRMaid is available as a public web service but is also easily installed as a local...... here as miRMaid, with the goal of integrating miRNA data resources in a uniform web service interface that can be accessed and queried by researchers and, most importantly, by computers. miRMaid is built around data from miRBase and is designed to follow the official miRBase data releases. It exposes...

Experimental Polish-Lithuanian Corpus with the Semantic Annotation Elements

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Danuta Roszko

2015-06-01

Full Text Available Experimental Polish-Lithuanian Corpus with the Semantic Annotation Elements In the article the authors present the experimental Polish-Lithuanian corpus (ECorpPL-LT formed for the idea of Polish-Lithuanian theoretical contrastive studies, a Polish-Lithuanian electronic dictionary, and as help for a sworn translator. The semantic annotation being brought into ECorpPL-LT is extremely useful in Polish-Lithuanian contrastive studies, and also proves helpful in translation work.

A Novel Quality Measure and Correction Procedure for the Annotation of Microbial Translation Initiation Sites.

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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.

Using Nonexperts for Annotating Pharmacokinetic Drug-Drug Interaction Mentions in Product Labeling: A Feasibility Study.

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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

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

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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.

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

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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.

An Informally Annotated Bibliography of Sociolinguistics.

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Tannen, Deborah

This annotated bibliography of sociolinguistics is divided into the following sections: speech events, ethnography of speaking and anthropological approaches to analysis of conversation; discourse analysis (including analysis of conversation and narrative), ethnomethodology and nonverbal communication; sociolinguistics; pragmatics (including…

The use of semantic similarity measures for optimally integrating heterogeneous Gene Ontology data from large scale annotation pipelines

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Gaston K Mazandu

2014-08-01

Full Text Available With the advancement of new high throughput sequencing technologies, there has been an increase in the number of genome sequencing projects worldwide, which has yielded complete genome sequences of human, animals and plants. Subsequently, several labs have focused on genome annotation, consisting of assigning functions to gene products, mostly using Gene Ontology (GO terms. As a consequence, there is an increased heterogeneity in annotations across genomes due to different approaches used by different pipelines to infer these annotations and also due to the nature of the GO structure itself. This makes a curator's task difficult, even if they adhere to the established guidelines for assessing these protein annotations. Here we develop a genome-scale approach for integrating GO annotations from different pipelines using semantic similarity measures. We used this approach to identify inconsistencies and similarities in functional annotations between orthologs of human and Drosophila melanogaster, to assess the quality of GO annotations derived from InterPro2GO mappings compared to manually annotated GO annotations for the Drosophila melanogaster proteome from a FlyBase dataset and human, and to filter GO annotation data for these proteomes. Results obtained indicate that an efficient integration of GO annotations eliminates redundancy up to 27.08 and 22.32% in the Drosophila melanogaster and human GO annotation datasets, respectively. Furthermore, we identified lack of and missing annotations for some orthologs, and annotation mismatches between InterPro2GO and manual pipelines in these two proteomes, thus requiring further curation. This simplifies and facilitates tasks of curators in assessing protein annotations, reduces redundancy and eliminates inconsistencies in large annotation datasets for ease of comparative functional genomics.

Automatic extraction of gene ontology annotation and its correlation with clusters in protein networks

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Mazo Ilya

2007-07-01

Full Text Available Abstract Background Uncovering cellular roles of a protein is a task of tremendous importance and complexity that requires dedicated experimental work as well as often sophisticated data mining and processing tools. Protein functions, often referred to as its annotations, are believed to manifest themselves through topology of the networks of inter-proteins interactions. In particular, there is a growing body of evidence that proteins performing the same function are more likely to interact with each other than with proteins with other functions. However, since functional annotation and protein network topology are often studied separately, the direct relationship between them has not been comprehensively demonstrated. In addition to having the general biological significance, such demonstration would further validate the data extraction and processing methods used to compose protein annotation and protein-protein interactions datasets. Results We developed a method for automatic extraction of protein functional annotation from scientific text based on the Natural Language Processing (NLP technology. For the protein annotation extracted from the entire PubMed, we evaluated the precision and recall rates, and compared the performance of the automatic extraction technology to that of manual curation used in public Gene Ontology (GO annotation. In the second part of our presentation, we reported a large-scale investigation into the correspondence between communities in the literature-based protein networks and GO annotation groups of functionally related proteins. We found a comprehensive two-way match: proteins within biological annotation groups form significantly denser linked network clusters than expected by chance and, conversely, densely linked network communities exhibit a pronounced non-random overlap with GO groups. We also expanded the publicly available GO biological process annotation using the relations extracted by our NLP technology

Recognition of Learner's Personality Traits through Digital Annotations in Distance Learning

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Omheni, Nizar; Kalboussi, Anis; Mazhoud, Omar; Kacem, Ahmed Hadj

2017-01-01

Researchers in distance education are interested in observing and modelling of learner's personality profile, and adapting their learning experiences accordingly. When learners read and interact with their reading materials, they do unselfconscious activities like annotation which may be a key feature of their personalities. Annotation activity…

Metab2MeSH: annotating compounds with medical subject headings.

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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.

Annotating breast cancer microarray samples using ontologies

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Liu, Hongfang; Li, Xin; Yoon, Victoria; Clarke, Robert

2008-01-01

As the most common cancer among women, breast cancer results from the accumulation of mutations in essential genes. Recent advance in high-throughput gene expression microarray technology has inspired researchers to use the technology to assist breast cancer diagnosis, prognosis, and treatment prediction. However, the high dimensionality of microarray experiments and public access of data from many experiments have caused inconsistencies which initiated the development of controlled terminologies and ontologies for annotating microarray experiments, such as the standard microarray Gene Expression Data (MGED) ontology (MO). In this paper, we developed BCM-CO, an ontology tailored specifically for indexing clinical annotations of breast cancer microarray samples from the NCI Thesaurus. Our research showed that the coverage of NCI Thesaurus is very limited with respect to i) terms used by researchers to describe breast cancer histology (covering 22 out of 48 histology terms); ii) breast cancer cell lines (covering one out of 12 cell lines); and iii) classes corresponding to the breast cancer grading and staging. By incorporating a wider range of those terms into BCM-CO, we were able to indexed breast cancer microarray samples from GEO using BCM-CO and MGED ontology and developed a prototype system with web interface that allows the retrieval of microarray data based on the ontology annotations. PMID:18999108

Annotated bibliography of the Russian languages literature on glaciology for 2015

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V. M. Kotlyakov

2017-01-01

Full Text Available The proposed annual bibliography continues annotated lists of the Russian‑language literature on glaciology that were regularly published in the past. It includes 245 references grouped into the following ten sections: 1  general issues of glaciology; 2  physics and chemistry of ice; 3  atmospheric ice; 4  snow cover; 5  ava‑ lanches and glacial mudflows; 6 sea ice; 7 river and lake ice; 8 icings and ground ice; 9 the glaciers and ice caps; 10 palaeoglaciology. In addition to the works of the current year, some works of earlier years are added, that, for various reasons, were not included in previous bibliographies.

Watch-and-Comment as an Approach to Collaboratively Annotate Points of Interest in Video and Interactive-TV Programs

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Pimentel, Maria Da Graça C.; Cattelan, Renan G.; Melo, Erick L.; Freitas, Giliard B.; Teixeira, Cesar A.

In earlier work we proposed the Watch-and-Comment (WaC) paradigm as the seamless capture of multimodal comments made by one or more users while watching a video, resulting in the automatic generation of multimedia documents specifying annotated interactive videos. The aim is to allow services to be offered by applying document engineering techniques to the multimedia document generated automatically. The WaC paradigm was demonstrated with a WaCTool prototype application which supports multimodal annotation over video frames and segments, producing a corresponding interactive video. In this chapter, we extend the WaC paradigm to consider contexts in which several viewers may use their own mobile devices while watching and commenting on an interactive-TV program. We first review our previous work. Next, we discuss scenarios in which mobile users can collaborate via the WaC paradigm. We then present a new prototype application which allows users to employ their mobile devices to collaboratively annotate points of interest in video and interactive-TV programs. We also detail the current software infrastructure which supports our new prototype; the infrastructure extends the Ginga middleware for the Brazilian Digital TV with an implementation of the UPnP protocol - the aim is to provide the seamless integration of the users' mobile devices into the TV environment. As a result, the work reported in this chapter defines the WaC paradigm for the mobile-user as an approach to allow the collaborative annotation of the points of interest in video and interactive-TV programs.

Combining gene prediction methods to improve metagenomic gene annotation

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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.

NegGOA: negative GO annotations selection using ontology structure.

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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.

Guidelines for visualizing and annotating rule-based models†

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Chylek, Lily A.; Hu, Bin; Blinov, Michael L.; Emonet, Thierry; Faeder, James R.; Goldstein, Byron; Gutenkunst, Ryan N.; Haugh, Jason M.; Lipniacki, Tomasz; Posner, Richard G.; Yang, Jin; Hlavacek, William S.

2011-01-01

Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models. PMID:21647530

Guidelines for visualizing and annotating rule-based models.

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Chylek, Lily A; Hu, Bin; Blinov, Michael L; Emonet, Thierry; Faeder, James R; Goldstein, Byron; Gutenkunst, Ryan N; Haugh, Jason M; Lipniacki, Tomasz; Posner, Richard G; Yang, Jin; Hlavacek, William S

2011-10-01

Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models.

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.

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...

Feeling Expression Using Avatars and Its Consistency for Subjective Annotation

Science.gov (United States)

Ito, Fuyuko; Sasaki, Yasunari; Hiroyasu, Tomoyuki; Miki, Mitsunori

Consumer Generated Media(CGM) is growing rapidly and the amount of content is increasing. However, it is often difficult for users to extract important contents and the existence of contents recording their experiences can easily be forgotten. As there are no methods or systems to indicate the subjective value of the contents or ways to reuse them, subjective annotation appending subjectivity, such as feelings and intentions, to contents is needed. Representation of subjectivity depends on not only verbal expression, but also nonverbal expression. Linguistically expressed annotation, typified by collaborative tagging in social bookmarking systems, has come into widespread use, but there is no system of nonverbally expressed annotation on the web. We propose the utilization of controllable avatars as a means of nonverbal expression of subjectivity, and confirmed the consistency of feelings elicited by avatars over time for an individual and in a group. In addition, we compared the expressiveness and ease of subjective annotation between collaborative tagging and controllable avatars. The result indicates that the feelings evoked by avatars are consistent in both cases, and using controllable avatars is easier than collaborative tagging for representing feelings elicited by contents that do not express meaning, such as photos.

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

ANNOTATION SUPPORTED OCCLUDED OBJECT TRACKING

Directory of Open Access Journals (Sweden)

Devinder Kumar

2012-08-01

Full Text Available Tracking occluded objects at different depths has become as extremely important component of study for any video sequence having wide applications in object tracking, scene recognition, coding, editing the videos and mosaicking. The paper studies the ability of annotation to track the occluded object based on pyramids with variation in depth further establishing a threshold at which the ability of the system to track the occluded object fails. Image annotation is applied on 3 similar video sequences varying in depth. In the experiment, one bike occludes the other at a depth of 60cm, 80cm and 100cm respectively. Another experiment is performed on tracking humans with similar depth to authenticate the results. The paper also computes the frame by frame error incurred by the system, supported by detailed simulations. This system can be effectively used to analyze the error in motion tracking and further correcting the error leading to flawless tracking. This can be of great interest to computer scientists while designing surveillance systems etc.

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

Laughter annotations in conversational speech corpora - possibilities and limitations for phonetic analysis

NARCIS (Netherlands)

Truong, Khiet Phuong; Trouvain, Jürgen

Existing laughter annotations provided with several publicly available conversational speech corpora (both multiparty and dyadic conversations) were investigated and compared. We discuss the possibilities and limitations of these rather coarse and shallow laughter annotations. There are definition

BIOCAT: a pattern recognition platform for customizable biological image classification and annotation.

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Zhou, Jie; Lamichhane, Santosh; Sterne, Gabriella; Ye, Bing; Peng, Hanchuan

2013-10-04

Pattern recognition algorithms are useful in bioimage informatics applications such as quantifying cellular and subcellular objects, annotating gene expressions, and classifying phenotypes. To provide effective and efficient image classification and annotation for the ever-increasing microscopic images, it is desirable to have tools that can combine and compare various algorithms, and build customizable solution for different biological problems. However, current tools often offer a limited solution in generating user-friendly and extensible tools for annotating higher dimensional images that correspond to multiple complicated categories. We develop the BIOimage Classification and Annotation Tool (BIOCAT). It is able to apply pattern recognition algorithms to two- and three-dimensional biological image sets as well as regions of interest (ROIs) in individual images for automatic classification and annotation. We also propose a 3D anisotropic wavelet feature extractor for extracting textural features from 3D images with xy-z resolution disparity. The extractor is one of the about 20 built-in algorithms of feature extractors, selectors and classifiers in BIOCAT. The algorithms are modularized so that they can be "chained" in a customizable way to form adaptive solution for various problems, and the plugin-based extensibility gives the tool an open architecture to incorporate future algorithms. We have applied BIOCAT to classification and annotation of images and ROIs of different properties with applications in cell biology and neuroscience. BIOCAT provides a user-friendly, portable platform for pattern recognition based biological image classification of two- and three- dimensional images and ROIs. We show, via diverse case studies, that different algorithms and their combinations have different suitability for various problems. The customizability of BIOCAT is thus expected to be useful for providing effective and efficient solutions for a variety of biological

PANDA: pathway and annotation explorer for visualizing and interpreting gene-centric data.

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Hart, Steven N; Moore, Raymond M; Zimmermann, Michael T; Oliver, Gavin R; Egan, Jan B; Bryce, Alan H; Kocher, Jean-Pierre A

2015-01-01

Objective. Bringing together genomics, transcriptomics, proteomics, and other -omics technologies is an important step towards developing highly personalized medicine. However, instrumentation has advances far beyond expectations and now we are able to generate data faster than it can be interpreted. Materials and Methods. We have developed PANDA (Pathway AND Annotation) Explorer, a visualization tool that integrates gene-level annotation in the context of biological pathways to help interpret complex data from disparate sources. PANDA is a web-based application that displays data in the context of well-studied pathways like KEGG, BioCarta, and PharmGKB. PANDA represents data/annotations as icons in the graph while maintaining the other data elements (i.e., other columns for the table of annotations). Custom pathways from underrepresented diseases can be imported when existing data sources are inadequate. PANDA also allows sharing annotations among collaborators. Results. In our first use case, we show how easy it is to view supplemental data from a manuscript in the context of a user's own data. Another use-case is provided describing how PANDA was leveraged to design a treatment strategy from the somatic variants found in the tumor of a patient with metastatic sarcomatoid renal cell carcinoma. Conclusion. PANDA facilitates the interpretation of gene-centric annotations by visually integrating this information with context of biological pathways. The application can be downloaded or used directly from our website: http://bioinformaticstools.mayo.edu/research/panda-viewer/.

Application of whole slide image markup and annotation for pathologist knowledge capture.

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Campbell, Walter S; Foster, Kirk W; Hinrichs, Steven H

2013-01-01

The ability to transfer image markup and annotation data from one scanned image of a slide to a newly acquired image of the same slide within a single vendor platform was investigated. The goal was to study the ability to use image markup and annotation data files as a mechanism to capture and retain pathologist knowledge without retaining the entire whole slide image (WSI) file. Accepted mathematical principles were investigated as a method to overcome variations in scans of the same glass slide and to accurately associate image markup and annotation data across different WSI of the same glass slide. Trilateration was used to link fixed points within the image and slide to the placement of markups and annotations of the image in a metadata file. Variation in markup and annotation placement between WSI of the same glass slide was reduced from over 80 μ to less than 4 μ in the x-axis and from 17 μ to 6 μ in the y-axis (P < 0.025). This methodology allows for the creation of a highly reproducible image library of histopathology images and interpretations for educational and research use.

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.

Sensor Control And Film Annotation For Long Range, Standoff Reconnaissance

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Schmidt, Thomas G.; Peters, Owen L.; Post, Lawrence H.

1984-12-01

This paper describes a Reconnaissance Data Annotation System that incorporates off-the-shelf technology and system designs providing a high degree of adaptability and interoperability to satisfy future reconnaissance data requirements. The history of data annotation for reconnaissance is reviewed in order to provide the base from which future developments can be assessed and technical risks minimized. The system described will accommodate new developments in recording head assemblies and the incorporation of advanced cameras of both the film and electro-optical type. Use of microprocessor control and digital bus inter-face form the central design philosophy. For long range, high altitude, standoff missions, the Data Annotation System computes the projected latitude and longitude of central target position from aircraft position and attitude. This complements the use of longer ranges and high altitudes for reconnaissance missions.

Integrating UIMA annotators in a web-based text processing framework.

Science.gov (United States)

Chen, Xiang; Arnold, Corey W

2013-01-01

The Unstructured Information Management Architecture (UIMA) [1] framework is a growing platform for natural language processing (NLP) applications. However, such applications may be difficult for non-technical users deploy. This project presents a web-based framework that wraps UIMA-based annotator systems into a graphical user interface for researchers and clinicians, and a web service for developers. An annotator that extracts data elements from lung cancer radiology reports is presented to illustrate the use of the system. Annotation results from the web system can be exported to multiple formats for users to utilize in other aspects of their research and workflow. This project demonstrates the benefits of a lay-user interface for complex NLP applications. Efforts such as this can lead to increased interest and support for NLP work in the clinical domain.

Processing sequence annotation data using the Lua programming language.

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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/.

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

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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,…

Assessment of disease named entity recognition on a corpus of annotated sentences.

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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

AIGO: Towards a unified framework for the Analysis and the Inter-comparison of GO functional annotations

Directory of Open Access Journals (Sweden)

Defoin-Platel Michael

2011-11-01

Full Text Available Abstract Background In response to the rapid growth of available genome sequences, efforts have been made to develop automatic inference methods to functionally characterize them. Pipelines that infer functional annotation are now routinely used to produce new annotations at a genome scale and for a broad variety of species. These pipelines differ widely in their inference algorithms, confidence thresholds and data sources for reasoning. This heterogeneity makes a comparison of the relative merits of each approach extremely complex. The evaluation of the quality of the resultant annotations is also challenging given there is often no existing gold-standard against which to evaluate precision and recall. Results In this paper, we present a pragmatic approach to the study of functional annotations. An ensemble of 12 metrics, describing various aspects of functional annotations, is defined and implemented in a unified framework, which facilitates their systematic analysis and inter-comparison. The use of this framework is demonstrated on three illustrative examples: analysing the outputs of state-of-the-art inference pipelines, comparing electronic versus manual annotation methods, and monitoring the evolution of publicly available functional annotations. The framework is part of the AIGO library (http://code.google.com/p/aigo for the Analysis and the Inter-comparison of the products of Gene Ontology (GO annotation pipelines. The AIGO library also provides functionalities to easily load, analyse, manipulate and compare functional annotations and also to plot and export the results of the analysis in various formats. Conclusions This work is a step toward developing a unified framework for the systematic study of GO functional annotations. This framework has been designed so that new metrics on GO functional annotations can be added in a very straightforward way.

Saint: a lightweight integration environment for model annotation.

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Lister, Allyson L; Pocock, Matthew; Taschuk, Morgan; Wipat, Anil

2009-11-15

Saint is a web application which provides a lightweight annotation integration environment for quantitative biological models. The system enables modellers to rapidly mark up models with biological information derived from a range of data sources. Saint is freely available for use on the web at http://www.cisban.ac.uk/saint. The web application is implemented in Google Web Toolkit and Tomcat, with all major browsers supported. The Java source code is freely available for download at http://saint-annotate.sourceforge.net. The Saint web server requires an installation of libSBML and has been tested on Linux (32-bit Ubuntu 8.10 and 9.04).

Generation of silver standard concept annotations from biomedical texts with special relevance to phenotypes.

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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

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

How Viral Poems are Annotated : On ‘OCD’ by Neil Hilborn

NARCIS (Netherlands)

van der Starre, K.A.

2015-01-01

In How Viral Poems are Annotated: On ‘OCD’ by Neil Hilborn Kila van der Starre explores how, where and by whom viral poems are annotated. The article focuses on the performance of the poem ‘OCD’ by Neil Hilborn that went viral in the summer of 2013 and has been viewed more than 10 million times on

Current trend of annotating single nucleotide variation in humans--A case study on SNVrap.

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Li, Mulin Jun; Wang, Junwen

2015-06-01

As high throughput methods, such as whole genome genotyping arrays, whole exome sequencing (WES) and whole genome sequencing (WGS), have detected huge amounts of genetic variants associated with human diseases, function annotation of these variants is an indispensable step in understanding disease etiology. Large-scale functional genomics projects, such as The ENCODE Project and Roadmap Epigenomics Project, provide genome-wide profiling of functional elements across different human cell types and tissues. With the urgent demands for identification of disease-causal variants, comprehensive and easy-to-use annotation tool is highly in demand. Here we review and discuss current progress and trend of the variant annotation field. Furthermore, we introduce a comprehensive web portal for annotating human genetic variants. We use gene-based features and the latest functional genomics datasets to annotate single nucleotide variation (SNVs) in human, at whole genome scale. We further apply several function prediction algorithms to annotate SNVs that might affect different biological processes, including transcriptional gene regulation, alternative splicing, post-transcriptional regulation, translation and post-translational modifications. The SNVrap web portal is freely available at http://jjwanglab.org/snvrap. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

Legal Information Sources: An Annotated Bibliography.

Science.gov (United States)

Conner, Ronald C.

This 25-page annotated bibliography describes the legal reference materials in the special collection of a medium-sized public library. Sources are listed in 12 categories: cases, dictionaries, directories, encyclopedias, forms, references for the lay person, general, indexes, laws and legislation, legal research aids, periodicals, and specialized…

Just-in-time : on strategy annotations

NARCIS (Netherlands)

J.C. van de Pol (Jaco)

2001-01-01

textabstractA simple kind of strategy annotations is investigated, giving rise to a class of strategies, including leftmost-innermost. It is shown that under certain restrictions, an interpreter can be written which computes the normal form of a term in a bottom-up traversal. The main contribution

Snap: an integrated SNP annotation platform

DEFF Research Database (Denmark)

Li, Shengting; Ma, Lijia; Li, Heng

2007-01-01

Snap (Single Nucleotide Polymorphism Annotation Platform) is a server designed to comprehensively analyze single genes and relationships between genes basing on SNPs in the human genome. The aim of the platform is to facilitate the study of SNP finding and analysis within the framework of medical...

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...

Supporting Listening Comprehension and Vocabulary Acquisition with Multimedia Annotations: The Students' Voice.

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Jones, Linda C.

2003-01-01

Extends Mayer's (1997, 2001) generative theory of multimedia learning and investigates under what conditions multimedia annotations can support listening comprehension in a second language. Highlights students' views on the effectiveness of multimedia annotations (visual and verbal) in assisting them in their comprehension and acquisition of…

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...

GRADUATE AND PROFESSIONAL EDUCATION, AN ANNOTATED BIBLIOGRAPHY.

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HEISS, ANN M.; AND OTHERS

THIS ANNOTATED BIBLIOGRAPHY CONTAINS REFERENCES TO GENERAL GRADUATE EDUCATION AND TO EDUCATION FOR THE FOLLOWING PROFESSIONAL FIELDS--ARCHITECTURE, BUSINESS, CLINICAL PSYCHOLOGY, DENTISTRY, ENGINEERING, LAW, LIBRARY SCIENCE, MEDICINE, NURSING, SOCIAL WORK, TEACHING, AND THEOLOGY. (HW)

AnnoLnc: a web server for systematically annotating novel human lncRNAs.

Science.gov (United States)

Hou, Mei; Tang, Xing; Tian, Feng; Shi, Fangyuan; Liu, Fenglin; Gao, Ge

2016-11-16

Long noncoding RNAs (lncRNAs) have been shown to play essential roles in almost every important biological process through multiple mechanisms. Although the repertoire of human lncRNAs has rapidly expanded, their biological function and regulation remain largely elusive, calling for a systematic and integrative annotation tool. Here we present AnnoLnc ( http://annolnc.cbi.pku.edu.cn ), a one-stop portal for systematically annotating novel human lncRNAs. Based on more than 700 data sources and various tool chains, AnnoLnc enables a systematic annotation covering genomic location, secondary structure, expression patterns, transcriptional regulation, miRNA interaction, protein interaction, genetic association and evolution. An intuitive web interface is available for interactive analysis through both desktops and mobile devices, and programmers can further integrate AnnoLnc into their pipeline through standard JSON-based Web Service APIs. To the best of our knowledge, AnnoLnc is the only web server to provide on-the-fly and systematic annotation for newly identified human lncRNAs. Compared with similar tools, the annotation generated by AnnoLnc covers a much wider spectrum with intuitive visualization. Case studies demonstrate the power of AnnoLnc in not only rediscovering known functions of human lncRNAs but also inspiring novel hypotheses.

Crowdsourcing image annotation for nucleus detection and segmentation in computational pathology: evaluating experts, automated methods, and the crowd.

Science.gov (United States)

Irshad, H; Montaser-Kouhsari, L; Waltz, G; Bucur, O; Nowak, J A; Dong, F; Knoblauch, N W; Beck, A H

2015-01-01

The development of tools in computational pathology to assist physicians and biomedical scientists in the diagnosis of disease requires access to high-quality annotated images for algorithm learning and evaluation. Generating high-quality expert-derived annotations is time-consuming and expensive. We explore the use of crowdsourcing for rapidly obtaining annotations for two core tasks in com- putational pathology: nucleus detection and nucleus segmentation. We designed and implemented crowdsourcing experiments using the CrowdFlower platform, which provides access to a large set of labor channel partners that accesses and manages millions of contributors worldwide. We obtained annotations from four types of annotators and compared concordance across these groups. We obtained: crowdsourced annotations for nucleus detection and segmentation on a total of 810 images; annotations using automated methods on 810 images; annotations from research fellows for detection and segmentation on 477 and 455 images, respectively; and expert pathologist-derived annotations for detection and segmentation on 80 and 63 images, respectively. For the crowdsourced annotations, we evaluated performance across a range of contributor skill levels (1, 2, or 3). The crowdsourced annotations (4,860 images in total) were completed in only a fraction of the time and cost required for obtaining annotations using traditional methods. For the nucleus detection task, the research fellow-derived annotations showed the strongest concordance with the expert pathologist- derived annotations (F-M =93.68%), followed by the crowd-sourced contributor levels 1,2, and 3 and the automated method, which showed relatively similar performance (F-M = 87.84%, 88.49%, 87.26%, and 86.99%, respectively). For the nucleus segmentation task, the crowdsourced contributor level 3-derived annotations, research fellow-derived annotations, and automated method showed the strongest concordance with the expert pathologist

Gene expression and functional annotation of the human and mouse choroid plexus epithelium.

Directory of Open Access Journals (Sweden)

Sarah F Janssen

Full Text Available BACKGROUND: The choroid plexus epithelium (CPE is a lobed neuro-epithelial structure that forms the outer blood-brain barrier. The CPE protrudes into the brain ventricles and produces the cerebrospinal fluid (CSF, which is crucial for brain homeostasis. Malfunction of the CPE is possibly implicated in disorders like Alzheimer disease, hydrocephalus or glaucoma. To study human genetic diseases and potential new therapies, mouse models are widely used. This requires a detailed knowledge of similarities and differences in gene expression and functional annotation between the species. The aim of this study is to analyze and compare gene expression and functional annotation of healthy human and mouse CPE. METHODS: We performed 44k Agilent microarray hybridizations with RNA derived from laser dissected healthy human and mouse CPE cells. We functionally annotated and compared the gene expression data of human and mouse CPE using the knowledge database Ingenuity. We searched for common and species specific gene expression patterns and function between human and mouse CPE. We also made a comparison with previously published CPE human and mouse gene expression data. RESULTS: Overall, the human and mouse CPE transcriptomes are very similar. Their major functionalities included epithelial junctions, transport, energy production, neuro-endocrine signaling, as well as immunological, neurological and hematological functions and disorders. The mouse CPE presented two additional functions not found in the human CPE: carbohydrate metabolism and a more extensive list of (neural developmental functions. We found three genes specifically expressed in the mouse CPE compared to human CPE, being ACE, PON1 and TRIM3 and no human specifically expressed CPE genes compared to mouse CPE. CONCLUSION: Human and mouse CPE transcriptomes are very similar, and display many common functionalities. Nonetheless, we also identified a few genes and pathways which suggest that the CPE

nGASP - the nematode genome annotation assessment project

Energy Technology Data Exchange (ETDEWEB)

Coghlan, A; Fiedler, T J; McKay, S J; Flicek, P; Harris, T W; Blasiar, D; Allen, J; Stein, L D

2008-12-19

While the C. elegans genome is extensively annotated, relatively little information is available for other Caenorhabditis species. The nematode genome annotation assessment project (nGASP) was launched to objectively assess the accuracy of protein-coding gene prediction software in C. elegans, and to apply this knowledge to the annotation of the genomes of four additional Caenorhabditis species and other nematodes. Seventeen groups worldwide participated in nGASP, and submitted 47 prediction sets for 10 Mb of the C. elegans genome. Predictions were compared to reference gene sets consisting of confirmed or manually curated gene models from WormBase. The most accurate gene-finders were 'combiner' algorithms, which made use of transcript- and protein-alignments and multi-genome alignments, as well as gene predictions from other gene-finders. Gene-finders that used alignments of ESTs, mRNAs and proteins came in second place. There was a tie for third place between gene-finders that used multi-genome alignments and ab initio gene-finders. The median gene level sensitivity of combiners was 78% and their specificity was 42%, which is nearly the same accuracy as reported for combiners in the human genome. C. elegans genes with exons of unusual hexamer content, as well as those with many exons, short exons, long introns, a weak translation start signal, weak splice sites, or poorly conserved orthologs were the most challenging for gene-finders. While the C. elegans genome is extensively annotated, relatively little information is available for other Caenorhabditis species. The nematode genome annotation assessment project (nGASP) was launched to objectively assess the accuracy of protein-coding gene prediction software in C. elegans, and to apply this knowledge to the annotation of the genomes of four additional Caenorhabditis species and other nematodes. Seventeen groups worldwide participated in nGASP, and submitted 47 prediction sets for 10 Mb of the C

The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4).

Science.gov (United States)

Huntemann, Marcel; Ivanova, Natalia N; Mavromatis, Konstantinos; Tripp, H James; Paez-Espino, David; Palaniappan, Krishnaveni; Szeto, Ernest; Pillay, Manoj; Chen, I-Min A; Pati, Amrita; Nielsen, Torben; Markowitz, Victor M; Kyrpides, Nikos C

2015-01-01

The DOE-JGI Microbial Genome Annotation Pipeline performs structural and functional annotation of microbial genomes that are further included into the Integrated Microbial Genome comparative analysis system. MGAP is applied to assembled nucleotide sequence datasets that are provided via the IMG submission site. Dataset submission for annotation first requires project and associated metadata description in GOLD. The MGAP sequence data processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNA features, as well as CRISPR elements. Structural annotation is followed by assignment of protein product names and functions.

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

Interpretation of Heliophysics wave data requires specialized knowledge of wave phenomena. Users of the virtual wave observatory (VWO) will greatly benefit from a data annotation service that will allow querying of data by phenomenon type, thus helping accomplish the VWO goal to make Heliophysics wave data searchable, understandable, and usable by the scientific community. Individual annotations can be sorted by phenomenon type and reduced into event lists (catalogs). However, in contrast to the event lists, annotation records allow a greater flexibility of collaborative management by more easily admitting operations of addition, revision, or deletion. They can therefore become the building blocks for an interactive Annotation Service with a suitable graphic user interface to the VWO middleware. The VWO Annotation Service vision is an interactive, collaborative sharing of domain expert knowledge with fellow scientists and students alike. An effective prototype of the VWO Annotation Service has been in operation at the University of Massachusetts Lowell since 2001. An expert rating system (ERS) was developed for annotating the IMAGE radio plasma imager (RPI) active sounding data containing 1.2 million plasmagrams. The RPI data analysts can use ERS to submit expert ratings of plasmagram features, such as presence of echo traces resulted from reflected RPI signals from distant plasma structures. Since its inception in 2001, the RPI ERS has accumulated 7351 expert plasmagram ratings in 16 phenomenon categories, together with free-text descriptions and other metadata. In addition to human expert ratings, the system holds 225,125 ratings submitted by the CORPRAL data prospecting software that employs a model of the human pre-attentive vision to select images potentially containing interesting features. The annotation records proved to be instrumental in a number of investigations where manual data exploration would have been prohibitively tedious and expensive

Skin Cancer Education Materials: Selected Annotations.

Science.gov (United States)

National Cancer Inst. (NIH), Bethesda, MD.

This annotated bibliography presents 85 entries on a variety of approaches to cancer education. The entries are grouped under three broad headings, two of which contain smaller sub-divisions. The first heading, Public Education, contains prevention and general information, and non-print materials. The second heading, Professional Education,…

Ten steps to get started in Genome Assembly and Annotation [version 1; referees: 2 approved

Directory of Open Access Journals (Sweden)

Victoria Dominguez Del Angel

2018-02-01

Full Text Available As a part of the ELIXIR-EXCELERATE efforts in capacity building, we present here 10 steps to facilitate researchers getting started in genome assembly and genome annotation. The guidelines given are broadly applicable, intended to be stable over time, and cover all aspects from start to finish of a general assembly and annotation project. Intrinsic properties of genomes are discussed, as is the importance of using high quality DNA. Different sequencing technologies and generally applicable workflows for genome assembly are also detailed. We cover structural and functional annotation and encourage readers to also annotate transposable elements, something that is often omitted from annotation workflows. The importance of data management is stressed, and we give advice on where to submit data and how to make your results Findable, Accessible, Interoperable, and Reusable (FAIR.

Annotated bibliography of cultural resources literature for the Nevada Nuclear Waste Storage Investigations

International Nuclear Information System (INIS)

1983-11-01

This annotated bibliography of the cultural resources literature pertinent for the Nevada Nuclear Waste Storage Investigations was assembled in order to (1) identify and evaluate the prehistoric and historic properties previously recorded in the Nevada Nuclear Waste Storage Investigations Project Area of southern Nye County, Nevada, (2) identify and develop research problems that have been and/or could be addressed by the cultural resources of this area, (3) isolate factors that might be important in the selection of a potential locality for a high level nuclear waste repository in the project area, and (4) critically evaluate the adequacy and current status of cultural resources knowledge in the project area. 195 references

Small molecule annotation for the Protein Data Bank.

Science.gov (United States)

Sen, Sanchayita; Young, Jasmine; Berrisford, John M; Chen, Minyu; Conroy, Matthew J; Dutta, Shuchismita; Di Costanzo, Luigi; Gao, Guanghua; Ghosh, Sutapa; Hudson, Brian P; Igarashi, Reiko; Kengaku, Yumiko; Liang, Yuhe; Peisach, Ezra; Persikova, Irina; Mukhopadhyay, Abhik; Narayanan, Buvaneswari Coimbatore; Sahni, Gaurav; Sato, Junko; Sekharan, Monica; Shao, Chenghua; Tan, Lihua; Zhuravleva, Marina A

2014-01-01

The Protein Data Bank (PDB) is the single global repository for three-dimensional structures of biological macromolecules and their complexes, and its more than 100,000 structures contain more than 20,000 distinct ligands or small molecules bound to proteins and nucleic acids. Information about these small molecules and their interactions with proteins and nucleic acids is crucial for our understanding of biochemical processes and vital for structure-based drug design. Small molecules present in a deposited structure may be attached to a polymer or may occur as a separate, non-covalently linked ligand. During curation of a newly deposited structure by wwPDB annotation staff, each molecule is cross-referenced to the PDB Chemical Component Dictionary (CCD). If the molecule is new to the PDB, a dictionary description is created for it. The information about all small molecule components found in the PDB is distributed via the ftp archive as an external reference file. Small molecule annotation in the PDB also includes information about ligand-binding sites and about covalent and other linkages between ligands and macromolecules. During the remediation of the peptide-like antibiotics and inhibitors present in the PDB archive in 2011, it became clear that additional annotation was required for consistent representation of these molecules, which are quite often composed of several sequential subcomponents including modified amino acids and other chemical groups. The connectivity information of the modified amino acids is necessary for correct representation of these biologically interesting molecules. The combined information is made available via a new resource called the Biologically Interesting molecules Reference Dictionary, which is complementary to the CCD and is now routinely used for annotation of peptide-like antibiotics and inhibitors. © The Author(s) 2014. Published by Oxford University Press.

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).

Functional Annotation of Ion Channel Structures by Molecular Simulation.

Science.gov (United States)

Trick, Jemma L; Chelvaniththilan, Sivapalan; Klesse, Gianni; Aryal, Prafulla; Wallace, E Jayne; Tucker, Stephen J; Sansom, Mark S P

2016-12-06

Ion channels play key roles in cell membranes, and recent advances are yielding an increasing number of structures. However, their functional relevance is often unclear and better tools are required for their functional annotation. In sub-nanometer pores such as ion channels, hydrophobic gating has been shown to promote dewetting to produce a functionally closed (i.e., non-conductive) state. Using the serotonin receptor (5-HT 3 R) structure as an example, we demonstrate the use of molecular dynamics to aid the functional annotation of channel structures via simulation of the behavior of water within the pore. Three increasingly complex simulation analyses are described: water equilibrium densities; single-ion free-energy profiles; and computational electrophysiology. All three approaches correctly predict the 5-HT 3 R crystal structure to represent a functionally closed (i.e., non-conductive) state. We also illustrate the application of water equilibrium density simulations to annotate different conformational states of a glycine receptor. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

iPad: Semantic annotation and markup of radiological images.

Science.gov (United States)

Rubin, Daniel L; Rodriguez, Cesar; Shah, Priyanka; Beaulieu, Chris

2008-11-06

Radiological images contain a wealth of information,such as anatomy and pathology, which is often not explicit and computationally accessible. Information schemes are being developed to describe the semantic content of images, but such schemes can be unwieldy to operationalize because there are few tools to enable users to capture structured information easily as part of the routine research workflow. We have created iPad, an open source tool enabling researchers and clinicians to create semantic annotations on radiological images. iPad hides the complexity of the underlying image annotation information model from users, permitting them to describe images and image regions using a graphical interface that maps their descriptions to structured ontologies semi-automatically. Image annotations are saved in a variety of formats,enabling interoperability among medical records systems, image archives in hospitals, and the Semantic Web. Tools such as iPad can help reduce the burden of collecting structured information from images, and it could ultimately enable researchers and physicians to exploit images on a very large scale and glean the biological and physiological significance of image content.

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.

A Machine Learning Based Analytical Framework for Semantic Annotation Requirements

OpenAIRE

Hamed Hassanzadeh; MohammadReza Keyvanpour

2011-01-01

The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable form. Therefore, semantic level information is one of the cornerstones of the Semantic Web. The process of adding semantic metadata to web resources is called Semantic Annotation. There are many obstacles against the Semantic Annotation, such as ...

The influence of annotation in graphical organizers

NARCIS (Netherlands)

Bezdan, Eniko; Kester, Liesbeth; Kirschner, Paul A.

2013-01-01

Bezdan, E., Kester, L., & Kirschner, P. A. (2012, 29-31 August). The influence of annotation in graphical organizers. Poster presented at the biannual meeting of the EARLI Special Interest Group Comprehension of Text and Graphics, Grenoble, France.

Annotation of mammalian primary microRNAs

Directory of Open Access Journals (Sweden)

Enright Anton J

2008-11-01

Full Text Available Abstract Background MicroRNAs (miRNAs are important regulators of gene expression and have been implicated in development, differentiation and pathogenesis. Hundreds of miRNAs have been discovered in mammalian genomes. Approximately 50% of mammalian miRNAs are expressed from introns of protein-coding genes; the primary transcript (pri-miRNA is therefore assumed to be the host transcript. However, very little is known about the structure of pri-miRNAs expressed from intergenic regions. Here we annotate transcript boundaries of miRNAs in human, mouse and rat genomes using various transcription features. The 5' end of the pri-miRNA is predicted from transcription start sites, CpG islands and 5' CAGE tags mapped in the upstream flanking region surrounding the precursor miRNA (pre-miRNA. The 3' end of the pri-miRNA is predicted based on the mapping of polyA signals, and supported by cDNA/EST and ditags data. The predicted pri-miRNAs are also analyzed for promoter and insulator-associated regulatory regions. Results We define sets of conserved and non-conserved human, mouse and rat pre-miRNAs using bidirectional BLAST and synteny analysis. Transcription features in their flanking regions are used to demarcate the 5' and 3' boundaries of the pri-miRNAs. The lengths and boundaries of primary transcripts are highly conserved between orthologous miRNAs. A significant fraction of pri-miRNAs have lengths between 1 and 10 kb, with very few introns. We annotate a total of 59 pri-miRNA structures, which include 82 pre-miRNAs. 36 pri-miRNAs are conserved in all 3 species. In total, 18 of the confidently annotated transcripts express more than one pre-miRNA. The upstream regions of 54% of the predicted pri-miRNAs are found to be associated with promoter and insulator regulatory sequences. Conclusion Little is known about the primary transcripts of intergenic miRNAs. Using comparative data, we are able to identify the boundaries of a significant proportion of

SAS- Semantic Annotation Service for Geoscience resources on the web

Science.gov (United States)

Elag, M.; Kumar, P.; Marini, L.; Li, R.; Jiang, P.

2015-12-01

There is a growing need for increased integration across the data and model resources that are disseminated on the web to advance their reuse across different earth science applications. Meaningful reuse of resources requires semantic metadata to realize the semantic web vision for allowing pragmatic linkage and integration among resources. Semantic metadata associates standard metadata with resources to turn them into semantically-enabled resources on the web. However, the lack of a common standardized metadata framework as well as the uncoordinated use of metadata fields across different geo-information systems, has led to a situation in which standards and related Standard Names abound. To address this need, we have designed SAS to provide a bridge between the core ontologies required to annotate resources and information systems in order to enable queries and analysis over annotation from a single environment (web). SAS is one of the services that are provided by the Geosematnic framework, which is a decentralized semantic framework to support the integration between models and data and allow semantically heterogeneous to interact with minimum human intervention. Here we present the design of SAS and demonstrate its application for annotating data and models. First we describe how predicates and their attributes are extracted from standards and ingested in the knowledge-base of the Geosemantic framework. Then we illustrate the application of SAS in annotating data managed by SEAD and annotating simulation models that have web interface. SAS is a step in a broader approach to raise the quality of geoscience data and models that are published on the web and allow users to better search, access, and use of the existing resources based on standard vocabularies that are encoded and published using semantic technologies.

Argumentation Theory. [A Selected Annotated Bibliography].

Science.gov (United States)

Benoit, William L.

Materials dealing with aspects of argumentation theory are cited in this annotated bibliography. The 50 citations are organized by topic as follows: (1) argumentation; (2) the nature of argument; (3) traditional perspectives on argument; (4) argument diagrams; (5) Chaim Perelman's theory of rhetoric; (6) the evaluation of argument; (7) argument…

Draft Genome Sequence and Gene Annotation of the Entomopathogenic Fungus Verticillium hemipterigenum

OpenAIRE

Horn, Fabian; Habel, Andreas; Scharf, Daniel H.; Dworschak, Jan; Brakhage, Axel A.; Guthke, Reinhard; Hertweck, Christian; Linde, J?rg

2015-01-01

Verticillium hemipterigenum (anamorph Torrubiella hemipterigena) is an entomopathogenic fungus and produces a broad range of secondary metabolites. Here, we present the draft genome sequence of the fungus, including gene structure and functional annotation. Genes were predicted incorporating RNA-Seq data and functionally annotated to provide the basis for further genome studies.

Annotating patient clinical records with syntactic chunks and named entities: the Harvey Corpus.

Science.gov (United States)

Savkov, Aleksandar; Carroll, John; Koeling, Rob; Cassell, Jackie

The free text notes typed by physicians during patient consultations contain valuable information for the study of disease and treatment. These notes are difficult to process by existing natural language analysis tools since they are highly telegraphic (omitting many words), and contain many spelling mistakes, inconsistencies in punctuation, and non-standard word order. To support information extraction and classification tasks over such text, we describe a de-identified corpus of free text notes, a shallow syntactic and named entity annotation scheme for this kind of text, and an approach to training domain specialists with no linguistic background to annotate the text. Finally, we present a statistical chunking system for such clinical text with a stable learning rate and good accuracy, indicating that the manual annotation is consistent and that the annotation scheme is tractable for machine learning.

CurlySMILES: a chemical language to customize and annotate encodings of molecular and nanodevice structures

Directory of Open Access Journals (Sweden)

Drefahl Axel

2011-01-01

Full Text Available Abstract CurlySMILES is a chemical line notation which extends SMILES with annotations for storage, retrieval and modeling of interlinked, coordinated, assembled and adsorbed molecules in supramolecular structures and nanodevices. Annotations are enclosed in curly braces and anchored to an atomic node or at the end of the molecular graph depending on the annotation type. CurlySMILES includes predefined annotations for stereogenicity, electron delocalization charges, extra-molecular interactions and connectivity, surface attachment, solutions, and crystal structures and allows extensions for domain-specific annotations. CurlySMILES provides a shorthand format to encode molecules with repetitive substructural parts or motifs such as monomer units in macromolecules and amino acids in peptide chains. CurlySMILES further accommodates special formats for non-molecular materials that are commonly denoted by composition of atoms or substructures rather than complete atom connectivity.

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.

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 .

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.

Annotation of selection strengths in viral genomes

DEFF Research Database (Denmark)

McCauley, Stephen; de Groot, Saskia; Mailund, Thomas

2007-01-01

Motivation: Viral genomes tend to code in overlapping reading frames to maximize information content. This may result in atypical codon bias and particular evolutionary constraints. Due to the fast mutation rate of viruses, there is additional strong evidence for varying selection between intra......- and intergenomic regions. The presence of multiple coding regions complicates the concept of Ka/Ks ratio, and thus begs for an alternative approach when investigating selection strengths. Building on the paper by McCauley & Hein (2006), we develop a method for annotating a viral genome coding in overlapping...... may thus achieve an annotation both of coding regions as well as selection strengths, allowing us to investigate different selection patterns and hypotheses. Results: We illustrate our method by applying it to a multiple alignment of four HIV2 sequences, as well as four Hepatitis B sequences. We...

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.

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

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

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The Community Junior College: An Annotated Bibliography.

Science.gov (United States)

Rarig, Emory W., Jr., Ed.

This annotated bibliography on the junior college is arranged by topic: research tools, history, functions and purposes, organization and administration, students, programs, personnel, facilities, and research. It covers publications through the fall of 1965 and has an author index. (HH)

A Resource of Quantitative Functional Annotation for Homo sapiens Genes.

Science.gov (United States)

Taşan, Murat; Drabkin, Harold J; Beaver, John E; Chua, Hon Nian; Dunham, Julie; Tian, Weidong; Blake, Judith A; Roth, Frederick P

2012-02-01

The body of human genomic and proteomic evidence continues to grow at ever-increasing rates, while annotation efforts struggle to keep pace. A surprisingly small fraction of human genes have clear, documented associations with specific functions, and new functions continue to be found for characterized genes. Here we assembled an integrated collection of diverse genomic and proteomic data for 21,341 human genes and make quantitative associations of each to 4333 Gene Ontology terms. We combined guilt-by-profiling and guilt-by-association approaches to exploit features unique to the data types. Performance was evaluated by cross-validation, prospective validation, and by manual evaluation with the biological literature. Functional-linkage networks were also constructed, and their utility was demonstrated by identifying candidate genes related to a glioma FLN using a seed network from genome-wide association studies. Our annotations are presented-alongside existing validated annotations-in a publicly accessible and searchable web interface.

Annotating and Interpreting Linear and Cyclic Peptide Tandem Mass Spectra.

Science.gov (United States)

Niedermeyer, Timo Horst Johannes

2016-01-01

Nonribosomal peptides often possess pronounced bioactivity, and thus, they are often interesting hit compounds in natural product-based drug discovery programs. Their mass spectrometric characterization is difficult due to the predominant occurrence of non-proteinogenic monomers and, especially in the case of cyclic peptides, the complex fragmentation patterns observed. This makes nonribosomal peptide tandem mass spectra annotation challenging and time-consuming. To meet this challenge, software tools for this task have been developed. In this chapter, the workflow for using the software mMass for the annotation of experimentally obtained peptide tandem mass spectra is described. mMass is freely available (http://www.mmass.org), open-source, and the most advanced and user-friendly software tool for this purpose. The software enables the analyst to concisely annotate and interpret tandem mass spectra of linear and cyclic peptides. Thus, it is highly useful for accelerating the structure confirmation and elucidation of cyclic as well as linear peptides and depsipeptides.

Great Basin Experimental Range: Annotated bibliography

Science.gov (United States)

E. Durant McArthur; Bryce A. Richardson; Stanley G. Kitchen

2013-01-01

This annotated bibliography documents the research that has been conducted on the Great Basin Experimental Range (GBER, also known as the Utah Experiment Station, Great Basin Station, the Great Basin Branch Experiment Station, Great Basin Experimental Center, and other similar name variants) over the 102 years of its existence. Entries were drawn from the original...

FIGENIX: Intelligent automation of genomic annotation: expertise integration in a new software platform

Directory of Open Access Journals (Sweden)

Pontarotti Pierre

2005-08-01

Full Text Available Abstract Background Two of the main objectives of the genomic and post-genomic era are to structurally and functionally annotate genomes which consists of detecting genes' position and structure, and inferring their function (as well as of other features of genomes. Structural and functional annotation both require the complex chaining of numerous different software, algorithms and methods under the supervision of a biologist. The automation of these pipelines is necessary to manage huge amounts of data released by sequencing projects. Several pipelines already automate some of these complex chaining but still necessitate an important contribution of biologists for supervising and controlling the results at various steps. Results Here we propose an innovative automated platform, FIGENIX, which includes an expert system capable to substitute to human expertise at several key steps. FIGENIX currently automates complex pipelines of structural and functional annotation under the supervision of the expert system (which allows for example to make key decisions, check intermediate results or refine the dataset. The quality of the results produced by FIGENIX is comparable to those obtained by expert biologists with a drastic gain in terms of time costs and avoidance of errors due to the human manipulation of data. Conclusion The core engine and expert system of the FIGENIX platform currently handle complex annotation processes of broad interest for the genomic community. They could be easily adapted to new, or more specialized pipelines, such as for example the annotation of miRNAs, the classification of complex multigenic families, annotation of regulatory elements and other genomic features of interest.

SplicingTypesAnno: annotating and quantifying alternative splicing events for RNA-Seq data.

Science.gov (United States)

Sun, Xiaoyong; Zuo, Fenghua; Ru, Yuanbin; Guo, Jiqiang; Yan, Xiaoyan; Sablok, Gaurav

2015-04-01

Alternative splicing plays a key role in the regulation of the central dogma. Four major types of alternative splicing have been classified as intron retention, exon skipping, alternative 5 splice sites or alternative donor sites, and alternative 3 splice sites or alternative acceptor sites. A few algorithms have been developed to detect splice junctions from RNA-Seq reads. However, there are few tools targeting at the major alternative splicing types at the exon/intron level. This type of analysis may reveal subtle, yet important events of alternative splicing, and thus help gain deeper understanding of the mechanism of alternative splicing. This paper describes a user-friendly R package, extracting, annotating and analyzing alternative splicing types for sequence alignment files from RNA-Seq. SplicingTypesAnno can: (1) provide annotation for major alternative splicing at exon/intron level. By comparing the annotation from GTF/GFF file, it identifies the novel alternative splicing sites; (2) offer a convenient two-level analysis: genome-scale annotation for users with high performance computing environment, and gene-scale annotation for users with personal computers; (3) generate a user-friendly web report and additional BED files for IGV visualization. SplicingTypesAnno is a user-friendly R package for extracting, annotating and analyzing alternative splicing types at exon/intron level for sequence alignment files from RNA-Seq. It is publically available at https://sourceforge.net/projects/splicingtypes/files/ or http://genome.sdau.edu.cn/research/software/SplicingTypesAnno.html. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Annotation of Regular Polysemy

DEFF Research Database (Denmark)

Martinez Alonso, Hector

Regular polysemy has received a lot of attention from the theory of lexical semantics and from computational linguistics. However, there is no consensus on how to represent the sense of underspecified examples at the token level, namely when annotating or disambiguating senses of metonymic words...... and metonymic. We have conducted an analysis in English, Danish and Spanish. Later on, we have tried to replicate the human judgments by means of unsupervised and semi-supervised sense prediction. The automatic sense-prediction systems have been unable to find empiric evidence for the underspecified sense, even...

Phenex: ontological annotation of phenotypic diversity.

Directory of Open Access Journals (Sweden)

James P Balhoff

2010-05-01

Full Text Available Phenotypic differences among species have long been systematically itemized and described by biologists in the process of investigating phylogenetic relationships and trait evolution. Traditionally, these descriptions have been expressed in natural language within the context of individual journal publications or monographs. As such, this rich store of phenotype data has been largely unavailable for statistical and computational comparisons across studies or integration with other biological knowledge.Here we describe Phenex, a platform-independent desktop application designed to facilitate efficient and consistent annotation of phenotypic similarities and differences using Entity-Quality syntax, drawing on terms from community ontologies for anatomical entities, phenotypic qualities, and taxonomic names. Phenex can be configured to load only those ontologies pertinent to a taxonomic group of interest. The graphical user interface was optimized for evolutionary biologists accustomed to working with lists of taxa, characters, character states, and character-by-taxon matrices.Annotation of phenotypic data using ontologies and globally unique taxonomic identifiers will allow biologists to integrate phenotypic data from different organisms and studies, leveraging decades of work in systematics and comparative morphology.

Phenex: ontological annotation of phenotypic diversity.

Science.gov (United States)

Balhoff, James P; Dahdul, Wasila M; Kothari, Cartik R; Lapp, Hilmar; Lundberg, John G; Mabee, Paula; Midford, Peter E; Westerfield, Monte; Vision, Todd J

2010-05-05

Phenotypic differences among species have long been systematically itemized and described by biologists in the process of investigating phylogenetic relationships and trait evolution. Traditionally, these descriptions have been expressed in natural language within the context of individual journal publications or monographs. As such, this rich store of phenotype data has been largely unavailable for statistical and computational comparisons across studies or integration with other biological knowledge. Here we describe Phenex, a platform-independent desktop application designed to facilitate efficient and consistent annotation of phenotypic similarities and differences using Entity-Quality syntax, drawing on terms from community ontologies for anatomical entities, phenotypic qualities, and taxonomic names. Phenex can be configured to load only those ontologies pertinent to a taxonomic group of interest. The graphical user interface was optimized for evolutionary biologists accustomed to working with lists of taxa, characters, character states, and character-by-taxon matrices. Annotation of phenotypic data using ontologies and globally unique taxonomic identifiers will allow biologists to integrate phenotypic data from different organisms and studies, leveraging decades of work in systematics and comparative morphology.

An Annotated Bibliography of Education for Medical Librarianship, 1940-1968

Science.gov (United States)

Shirley, Sherrilynne

1969-01-01

An attempt has been made in this bibliography to represent the various viewpoints concerning education for medical librarianship equally. The topics covered include: general background reading and readings for those interested in establishing courses in medical librarianship. The former includes annotations on the history and international aspects of the subject. The latter consists of annotations of articles on early courses and present courses in medical librarianship. A final area discussed is the Medical Library Association's Code for the Training and Certification of Medical Librarians. PMID:4898629

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

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

MUTAGEN: Multi-user tool for annotating GENomes

DEFF Research Database (Denmark)

Brugger, K.; Redder, P.; Skovgaard, Marie

2003-01-01

MUTAGEN is a free prokaryotic annotation system. It offers the advantages of genome comparison, graphical sequence browsers, search facilities and open-source for user-specific adjustments. The web-interface allows several users to access the system from standard desktop computers. The Sulfolobus...

CommWalker: correctly evaluating modules in molecular networks in light of annotation bias.

Science.gov (United States)

Luecken, M D; Page, M J T; Crosby, A J; Mason, S; Reinert, G; Deane, C M

2018-03-15

Detecting novel functional modules in molecular networks is an important step in biological research. In the absence of gold standard functional modules, functional annotations are often used to verify whether detected modules/communities have biological meaning. However, as we show, the uneven distribution of functional annotations means that such evaluation methods favor communities of well-studied proteins. We propose a novel framework for the evaluation of communities as functional modules. Our proposed framework, CommWalker, takes communities as inputs and evaluates them in their local network environment by performing short random walks. We test CommWalker's ability to overcome annotation bias using input communities from four community detection methods on two protein interaction networks. We find that modules accepted by CommWalker are similarly co-expressed as those accepted by current methods. Crucially, CommWalker performs well not only in well-annotated regions, but also in regions otherwise obscured by poor annotation. CommWalker community prioritization both faithfully captures well-validated communities and identifies functional modules that may correspond to more novel biology. The CommWalker algorithm is freely available at opig.stats.ox.ac.uk/resources or as a docker image on the Docker Hub at hub.docker.com/r/lueckenmd/commwalker/. deane@stats.ox.ac.uk. Supplementary data are available at Bioinformatics online.

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/.

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.

Similarity maps and hierarchical clustering for annotating FT-IR spectral images.

Science.gov (United States)

Zhong, Qiaoyong; Yang, Chen; Großerüschkamp, Frederik; Kallenbach-Thieltges, Angela; Serocka, Peter; Gerwert, Klaus; Mosig, Axel

2013-11-20

Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization. We introduce so-called interactive similarity maps as an alternative annotation strategy for annotating infrared microscopic images. We demonstrate that segmentations obtained from interactive similarity maps lead to similarly accurate segmentations as segmentations obtained from conventionally used hierarchical clustering approaches. In order to perform this comparison on quantitative grounds, we provide a scheme that allows to identify non-horizontal cuts in dendrograms. This yields a validation scheme for hierarchical clustering approaches commonly used in infrared microscopy. We demonstrate that interactive similarity maps may identify more accurate segmentations than hierarchical clustering based approaches, and thus are a viable and due to their interactive nature attractive alternative to hierarchical clustering. Our validation scheme furthermore shows that performance of hierarchical two-means is comparable to the traditionally used Ward's clustering. As the former is much more efficient in time and memory, our results suggest another less resource demanding alternative for annotating large spectral images.

Book Reviews, Annotation, and Web Technology.

Science.gov (United States)

Schulze, Patricia

From reading texts to annotating web pages, grade 6-8 students rely on group cooperation and individual reading and writing skills in this research project that spans six 50-minute lessons. Student objectives for this project are that they will: read, discuss, and keep a journal on a book in literature circles; understand the elements of and…

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

Science.gov (United States)

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.

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

New in protein structure and function annotation: hotspots, single nucleotide polymorphisms and the 'Deep Web'.

Science.gov (United States)

Bromberg, Yana; Yachdav, Guy; Ofran, Yanay; Schneider, Reinhard; Rost, Burkhard

2009-05-01

The rapidly increasing quantity of protein sequence data continues to widen the gap between available sequences and annotations. Comparative modeling suggests some aspects of the 3D structures of approximately half of all known proteins; homology- and network-based inferences annotate some aspect of function for a similar fraction of the proteome. For most known protein sequences, however, there is detailed knowledge about neither their function nor their structure. Comprehensive efforts towards the expert curation of sequence annotations have failed to meet the demand of the rapidly increasing number of available sequences. Only the automated prediction of protein function in the absence of homology can close the gap between available sequences and annotations in the foreseeable future. This review focuses on two novel methods for automated annotation, and briefly presents an outlook on how modern web software may revolutionize the field of protein sequence annotation. First, predictions of protein binding sites and functional hotspots, and the evolution of these into the most successful type of prediction of protein function from sequence will be discussed. Second, a new tool, comprehensive in silico mutagenesis, which contributes important novel predictions of function and at the same time prepares for the onset of the next sequencing revolution, will be described. While these two new sub-fields of protein prediction represent the breakthroughs that have been achieved methodologically, it will then be argued that a different development might further change the way biomedical researchers benefit from annotations: modern web software can connect the worldwide web in any browser with the 'Deep Web' (ie, proprietary data resources). The availability of this direct connection, and the resulting access to a wealth of data, may impact drug discovery and development more than any existing method that contributes to protein annotation.

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.

Evaluating automatically annotated treebanks for linguistic research

NARCIS (Netherlands)

Bloem, J.; Bański, P.; Kupietz, M.; Lüngen, H.; Witt, A.; Barbaresi, A.; Biber, H.; Breiteneder, E.; Clematide, S.

2016-01-01

This study discusses evaluation methods for linguists to use when employing an automatically annotated treebank as a source of linguistic evidence. While treebanks are usually evaluated with a general measure over all the data, linguistic studies often focus on a particular construction or a group

DIMA – Annotation guidelines for German intonation

DEFF Research Database (Denmark)

Kügler, Frank; Smolibocki, Bernadett; Arnold, Denis

2015-01-01

This paper presents newly developed guidelines for prosodic annotation of German as a consensus system agreed upon by German intonologists. The DIMA system is rooted in the framework of autosegmental-metrical phonology. One important goal of the consensus is to make exchanging data between groups...

Annotating State of Mind in Meeting Data

NARCIS (Netherlands)

Heylen, Dirk K.J.; Reidsma, Dennis; Ordelman, Roeland J.F.; Devillers, L.; Martin, J-C.; Cowie, R.; Batliner, A.

We discuss the annotation procedure for mental state and emotion that is under development for the AMI (Augmented Multiparty Interaction) corpus. The categories that were found to be most appropriate relate not only to emotions but also to (meta-)cognitive states and interpersonal variables. The

Additions to the annotated list of marine alien biota in the Mediterranean with special emphasis on Foraminifera and Parasites

Directory of Open Access Journals (Sweden)

A. ZENETOS

2008-05-01

Full Text Available The present work is an update of the annotated list (ZENETOS et al., 2006 based on literature up to April 2008. Emphasis is given to ecofunctional/taxonomic groups poorly addressed in the annotated list, such as the foraminiferan and parasites, while macrophytes are critically reviewed following the CIESM Atlas (VERLAQUE et al., in press. Moreover, in this update the bio-geographic area addressed includes the Sea of Marmara. The update yields a further 175 alien species in the Mediterranean bringing the total to 903. As evidenced by recent findings, more and more previously known ‘casual’ aliens, are becoming established. Approximately 100 more species have become well established in the region, raising the number of established species to 496 versus 385 until 2005. In the period from January 2006 to April 2008 more than 80 published papers have resulted in the recording of 94 new aliens, which is interpreted as a new introduction every 9 days, a rate beyond the worst scenario.

Geothermal wetlands: an annotated bibliography of pertinent literature

Energy Technology Data Exchange (ETDEWEB)

Stanley, N.E.; Thurow, T.L.; Russell, B.F.; Sullivan, J.F.

1980-05-01

This annotated bibliography covers the following topics: algae, wetland ecosystems; institutional aspects; macrophytes - general, production rates, and mineral absorption; trace metal absorption; wetland soils; water quality; and other aspects of marsh ecosystems. (MHR)

Review of actinide-sediment reactions with an annotated bibliography

Energy Technology Data Exchange (ETDEWEB)

Ames, L.L.; Rai, D.; Serne, R.J.

1976-02-10

The annotated bibliography is divided into sections on chemistry and geochemistry, migration and accumulation, cultural distributions, natural distributions, and bibliographies and annual reviews. (LK)

Improving integrative searching of systems chemical biology data using semantic annotation

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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.

Visual Interpretation with Three-Dimensional Annotations (VITA): Three-Dimensional Image Interpretation Tool for Radiological Reporting

OpenAIRE

Roy, Sharmili; Brown, Michael S.; Shih, George L.

2013-01-01

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 i...

Automated Eukaryotic Gene Structure Annotation Using EVidenceModeler and the Program to Assemble Spliced Alignments

Energy Technology Data Exchange (ETDEWEB)

Haas, B J; Salzberg, S L; Zhu, W; Pertea, M; Allen, J E; Orvis, J; White, O; Buell, C R; Wortman, J R

2007-12-10

EVidenceModeler (EVM) is presented as an automated eukaryotic gene structure annotation tool that reports eukaryotic gene structures as a weighted consensus of all available evidence. EVM, when combined with the Program to Assemble Spliced Alignments (PASA), yields a comprehensive, configurable annotation system that predicts protein-coding genes and alternatively spliced isoforms. Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation.

Rapid identification of sequences for orphan enzymes to power accurate protein annotation.

Directory of Open Access Journals (Sweden)

Kevin R Ramkissoon

Full Text Available The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the "back catalog" of enzymology--"orphan enzymes," those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC database alone. In this study, we demonstrate how this orphan enzyme "back catalog" is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology's "back catalog" another powerful tool to drive accurate genome annotation.

Rapid Identification of Sequences for Orphan Enzymes to Power Accurate Protein Annotation

Science.gov (United States)

Ojha, Sunil; Watson, Douglas S.; Bomar, Martha G.; Galande, Amit K.; Shearer, Alexander G.

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the “back catalog” of enzymology – “orphan enzymes,” those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme “back catalog” is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology’s “back catalog” another powerful tool to drive accurate genome annotation. PMID:24386392

Developing national on-line services to annotate and analyse underwater imagery in a research cloud

Science.gov (United States)

Proctor, R.; Langlois, T.; Friedman, A.; Davey, B.

2017-12-01

Fish image annotation data is currently collected by various research, management and academic institutions globally (+100,000's hours of deployments) with varying degrees of standardisation and limited formal collaboration or data synthesis. We present a case study of how national on-line services, developed within a domain-oriented research cloud, have been used to annotate habitat images and synthesise fish annotation data sets collected using Autonomous Underwater Vehicles (AUVs) and baited remote underwater stereo-video (stereo-BRUV). Two developing software tools have been brought together in the marine science cloud to provide marine biologists with a powerful service for image annotation. SQUIDLE+ is an online platform designed for exploration, management and annotation of georeferenced images & video data. It provides a flexible annotation framework allowing users to work with their preferred annotation schemes. We have used SQUIDLE+ to sample the habitat composition and complexity of images of the benthos collected using stereo-BRUV. GlobalArchive is designed to be a centralised repository of aquatic ecological survey data with design principles including ease of use, secure user access, flexible data import, and the collection of any sampling and image analysis information. To easily share and synthesise data we have implemented data sharing protocols, including Open Data and synthesis Collaborations, and a spatial map to explore global datasets and filter to create a synthesis. These tools in the science cloud, together with a virtual desktop analysis suite offering python and R environments offer an unprecedented capability to deliver marine biodiversity information of value to marine managers and scientists alike.

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.

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...

JAFA: a protein function annotation meta-server

DEFF Research Database (Denmark)

Friedberg, Iddo; Harder, Tim; Godzik, Adam

2006-01-01

Annotations, or JAFA server. JAFA queries several function prediction servers with a protein sequence and assembles the returned predictions in a legible, non-redundant format. In this manner, JAFA combines the predictions of several servers to provide a comprehensive view of what are the predicted functions...

A Case Study of Using a Social Annotation Tool to Support Collaboratively Learning

Science.gov (United States)

Gao, Fei

2013-01-01

The purpose of the study was to understand student interaction and learning supported by a collaboratively social annotation tool--Diigo. The researcher examined through a case study how students participated and interacted when learning an online text with the social annotation tool--Diigo, and how they perceived their experience. The findings…

MGmapper: Reference based mapping and taxonomy annotation of metagenomics sequence reads

DEFF Research Database (Denmark)

Petersen, Thomas Nordahl; Lukjancenko, Oksana; Thomsen, Martin Christen Frølund

2017-01-01

number of false positive species annotations are a problem unless thresholds or post-processing are applied to differentiate between correct and false annotations. MGmapper is a package to process raw next generation sequence data and perform reference based sequence assignment, followed by a post...... pipeline is freely available as a bitbucked package (https://bitbucket.org/genomicepidemiology/mgmapper). A web-version (https://cge.cbs.dtu.dk/services/MGmapper) provides the basic functionality for analysis of small fastq datasets....

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.

Ratsnake: A Versatile Image Annotation Tool with Application to Computer-Aided Diagnosis

Directory of Open Access Journals (Sweden)

D. K. Iakovidis

2014-01-01

Full Text Available Image segmentation and annotation are key components of image-based medical computer-aided diagnosis (CAD systems. In this paper we present Ratsnake, a publicly available generic image annotation tool providing annotation efficiency, semantic awareness, versatility, and extensibility, features that can be exploited to transform it into an effective CAD system. In order to demonstrate this unique capability, we present its novel application for the evaluation and quantification of salient objects and structures of interest in kidney biopsy images. Accurate annotation identifying and quantifying such structures in microscopy images can provide an estimation of pathogenesis in obstructive nephropathy, which is a rather common disease with severe implication in children and infants. However a tool for detecting and quantifying the disease is not yet available. A machine learning-based approach, which utilizes prior domain knowledge and textural image features, is considered for the generation of an image force field customizing the presented tool for automatic evaluation of kidney biopsy images. The experimental evaluation of the proposed application of Ratsnake demonstrates its efficiency and effectiveness and promises its wide applicability across a variety of medical imaging domains.

Annotated Bibliography of Textbooks and Reference Materials in Marine Sciences. Provisional Edition. Intergovernmental Oceanographic Commission, Technical Series.

Science.gov (United States)

United Nations Educational, Scientific, and Cultural Organization, Paris (France). Intergovernmental Oceanographic Commission.

Presented is an annotated bibliography based on selected materials from a preliminary survey of existing bibliographies, publishers' listings, and other sources. It is intended to serve educators and researchers, especially those in countries where marine sciences are just developing. One hundred annotated and 450 non-annotated entries are…

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.

Consumer energy research: an annotated bibliography. Vol. 1. [Some text in French

Energy Technology Data Exchange (ETDEWEB)

Anderson, D.C.; McDougall, G.H.G.

1983-01-01

This annotated bibliography attempts to provide a comprehensive package of existing information in consumer related energy research. A concentrated effort was made to collect unpublished material as well as material from journals and other sources, including governments, utilities, research institutes and private firms. A deliberate effort was made to include agencies outside North America. For the most part the bibliography is limited to annotations of empirical studies. However, it includes a number of descriptive reports which appear to make a significant contribution to understanding consumers and energy use. The format of the annotations diplays the author, date of publication, title and source of the study. Annotations of empirical studies are divided into four parts: objectives, methods, variables and findings/implications. Care was taken to provide a reasonable amount of detail in the annotations to enable the reader to understand the methodology, the results and the degree to which the implications of the study can be generalized to other situations. Studies are arranged alphabetically by author. The content of the studies reviewed is classified in a series of tables which are intended to provide a summary of sources, types and foci of the various studies. These tables are intended to aid researchers interested in specific topics to locate those studies most relevant to their work. The studies are categorized using a number of different classification criteria, for example, methodology used, type of energy form, type of policy initiative, and type of consumer activity. A general overview of the studies is also presented. 20 tabs.

Quantification of the impact of PSI:Biology according to the annotations of the determined structures.

Science.gov (United States)

DePietro, Paul J; Julfayev, Elchin S; McLaughlin, William A

2013-10-21

Protein Structure Initiative:Biology (PSI:Biology) is the third phase of PSI where protein structures are determined in high-throughput to characterize their biological functions. The transition to the third phase entailed the formation of PSI:Biology Partnerships which are composed of structural genomics centers and biomedical science laboratories. We present a method to examine the impact of protein structures determined under the auspices of PSI:Biology by measuring their rates of annotations. The mean numbers of annotations per structure and per residue are examined. These are designed to provide measures of the amount of structure to function connections that can be leveraged from each structure. One result is that PSI:Biology structures are found to have a higher rate of annotations than structures determined during the first two phases of PSI. A second result is that the subset of PSI:Biology structures determined through PSI:Biology Partnerships have a higher rate of annotations than those determined exclusive of those partnerships. Both results hold when the annotation rates are examined either at the level of the entire protein or for annotations that are known to fall at specific residues within the portion of the protein that has a determined structure. We conclude that PSI:Biology determines structures that are estimated to have a higher degree of biomedical interest than those determined during the first two phases of PSI based on a broad array of biomedical annotations. For the PSI:Biology Partnerships, we see that there is an associated added value that represents part of the progress toward the goals of PSI:Biology. We interpret the added value to mean that team-based structural biology projects that utilize the expertise and technologies of structural genomics centers together with biological laboratories in the community are conducted in a synergistic manner. We show that the annotation rates can be used in conjunction with established metrics, i

Impingement: an annotated bibliography

International Nuclear Information System (INIS)

Uziel, M.S.; Hannon, E.H.

1979-04-01

This bibliography of 655 annotated references on impingement of aquatic organisms at intake structures of thermal-power-plant cooling systems was compiled from the published and unpublished literature. The bibliography includes references from 1928 to 1978 on impingement monitoring programs; impingement impact assessment; applicable law; location and design of intake structures, screens, louvers, and other barriers; fish behavior and swim speed as related to impingement susceptibility; and the effects of light, sound, bubbles, currents, and temperature on fish behavior. References are arranged alphabetically by author or corporate author. Indexes are provided for author, keywords, subject category, geographic location, taxon, and title

Reading Actively Online: An Exploratory Investigation of Online Annotation Tools for Inquiry Learning

Science.gov (United States)

Lu, Jingyan; Deng, Liping

2012-01-01

This study seeks to design and facilitate active reading among secondary school students with an online annotation tool--Diigo. Two classes of different academic performance levels were recruited to examine their annotation behavior and perceptions of Diigo. We wanted to determine whether the two classes differed in how they used Diigo; how they…

Reading Actively Online: An Exploratory Investigation of Online Annotation Tools for Inquiry Learning / La lecture active en ligne: étude exploratoire sur les outils d'annotation en ligne pour l'apprentissage par l’enquête

OpenAIRE

Jingyan Lu; Liping Deng

2012-01-01

This study seeks to design and facilitate active reading among secondary school students with an online annotation tool – Diigo. Two classes of different academic performance levels were recruited to examine their annotation behavior and perceptions of Diigo. We wanted to determine whether the two classes differed in how they used Diigo; how they perceived Diigo; and whether how they used Diigo was related to how they perceived it. Using annotation data and surveys in which students reported ...

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....

Annotating Cancer Variants and Anti-Cancer Therapeutics in Reactome

Energy Technology Data Exchange (ETDEWEB)

Milacic, Marija; Haw, Robin, E-mail: robin.haw@oicr.on.ca; Rothfels, Karen; Wu, Guanming [Informatics and Bio-computing Platform, Ontario Institute for Cancer Research, Toronto, ON, M5G0A3 (Canada); Croft, David; Hermjakob, Henning [European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD (United Kingdom); D’Eustachio, Peter [Department of Biochemistry, NYU School of Medicine, New York, NY 10016 (United States); Stein, Lincoln [Informatics and Bio-computing Platform, Ontario Institute for Cancer Research, Toronto, ON, M5G0A3 (Canada)

2012-11-08

Reactome describes biological pathways as chemical reactions that closely mirror the actual physical interactions that occur in the cell. Recent extensions of our data model accommodate the annotation of cancer and other disease processes. First, we have extended our class of protein modifications to accommodate annotation of changes in amino acid sequence and the formation of fusion proteins to describe the proteins involved in disease processes. Second, we have added a disease attribute to reaction, pathway, and physical entity classes that uses disease ontology terms. To support the graphical representation of “cancer” pathways, we have adapted our Pathway Browser to display disease variants and events in a way that allows comparison with the wild type pathway, and shows connections between perturbations in cancer and other biological pathways. The curation of pathways associated with cancer, coupled with our efforts to create other disease-specific pathways, will interoperate with our existing pathway and network analysis tools. Using the Epidermal Growth Factor Receptor (EGFR) signaling pathway as an example, we show how Reactome annotates and presents the altered biological behavior of EGFR variants due to their altered kinase and ligand-binding properties, and the mode of action and specificity of anti-cancer therapeutics.

Annotating cancer variants and anti-cancer therapeutics in reactome.

Science.gov (United States)

Milacic, Marija; Haw, Robin; Rothfels, Karen; Wu, Guanming; Croft, David; Hermjakob, Henning; D'Eustachio, Peter; Stein, Lincoln

2012-11-08

Reactome describes biological pathways as chemical reactions that closely mirror the actual physical interactions that occur in the cell. Recent extensions of our data model accommodate the annotation of cancer and other disease processes. First, we have extended our class of protein modifications to accommodate annotation of changes in amino acid sequence and the formation of fusion proteins to describe the proteins involved in disease processes. Second, we have added a disease attribute to reaction, pathway, and physical entity classes that uses disease ontology terms. To support the graphical representation of "cancer" pathways, we have adapted our Pathway Browser to display disease variants and events in a way that allows comparison with the wild type pathway, and shows connections between perturbations in cancer and other biological pathways. The curation of pathways associated with cancer, coupled with our efforts to create other disease-specific pathways, will interoperate with our existing pathway and network analysis tools. Using the Epidermal Growth Factor Receptor (EGFR) signaling pathway as an example, we show how Reactome annotates and presents the altered biological behavior of EGFR variants due to their altered kinase and ligand-binding properties, and the mode of action and specificity of anti-cancer therapeutics.

Annotating Cancer Variants and Anti-Cancer Therapeutics in Reactome

International Nuclear Information System (INIS)

Milacic, Marija; Haw, Robin; Rothfels, Karen; Wu, Guanming; Croft, David; Hermjakob, Henning; D’Eustachio, Peter; Stein, Lincoln

2012-01-01

Reactome describes biological pathways as chemical reactions that closely mirror the actual physical interactions that occur in the cell. Recent extensions of our data model accommodate the annotation of cancer and other disease processes. First, we have extended our class of protein modifications to accommodate annotation of changes in amino acid sequence and the formation of fusion proteins to describe the proteins involved in disease processes. Second, we have added a disease attribute to reaction, pathway, and physical entity classes that uses disease ontology terms. To support the graphical representation of “cancer” pathways, we have adapted our Pathway Browser to display disease variants and events in a way that allows comparison with the wild type pathway, and shows connections between perturbations in cancer and other biological pathways. The curation of pathways associated with cancer, coupled with our efforts to create other disease-specific pathways, will interoperate with our existing pathway and network analysis tools. Using the Epidermal Growth Factor Receptor (EGFR) signaling pathway as an example, we show how Reactome annotates and presents the altered biological behavior of EGFR variants due to their altered kinase and ligand-binding properties, and the mode of action and specificity of anti-cancer therapeutics

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

xGDBvm: A Web GUI-Driven Workflow for Annotating Eukaryotic Genomes in the Cloud.

Science.gov (United States)

Duvick, Jon; Standage, Daniel S; Merchant, Nirav; Brendel, Volker P

2016-04-01

Genome-wide annotation of gene structure requires the integration of numerous computational steps. Currently, annotation is arguably best accomplished through collaboration of bioinformatics and domain experts, with broad community involvement. However, such a collaborative approach is not scalable at today's pace of sequence generation. To address this problem, we developed the xGDBvm software, which uses an intuitive graphical user interface to access a number of common genome analysis and gene structure tools, preconfigured in a self-contained virtual machine image. Once their virtual machine instance is deployed through iPlant's Atmosphere cloud services, users access the xGDBvm workflow via a unified Web interface to manage inputs, set program parameters, configure links to high-performance computing (HPC) resources, view and manage output, apply analysis and editing tools, or access contextual help. The xGDBvm workflow will mask the genome, compute spliced alignments from transcript and/or protein inputs (locally or on a remote HPC cluster), predict gene structures and gene structure quality, and display output in a public or private genome browser complete with accessory tools. Problematic gene predictions are flagged and can be reannotated using the integrated yrGATE annotation tool. xGDBvm can also be configured to append or replace existing data or load precomputed data. Multiple genomes can be annotated and displayed, and outputs can be archived for sharing or backup. xGDBvm can be adapted to a variety of use cases including de novo genome annotation, reannotation, comparison of different annotations, and training or teaching. © 2016 American Society of Plant Biologists. All rights reserved.

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

Directory of Open Access Journals (Sweden)

Yushen Du

2016-11-01

Full Text Available Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp, we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available.

GoGene: gene annotation in the fast lane.

Science.gov (United States)

Plake, Conrad; Royer, Loic; Winnenburg, Rainer; Hakenberg, Jörg; Schroeder, Michael

2009-07-01

High-throughput screens such as microarrays and RNAi screens produce huge amounts of data. They typically result in hundreds of genes, which are often further explored and clustered via enriched GeneOntology terms. The strength of such analyses is that they build on high-quality manual annotations provided with the GeneOntology. However, the weakness is that annotations are restricted to process, function and location and that they do not cover all known genes in model organisms. GoGene addresses this weakness by complementing high-quality manual annotation with high-throughput text mining extracting co-occurrences of genes and ontology terms from literature. GoGene contains over 4,000,000 associations between genes and gene-related terms for 10 model organisms extracted from more than 18,000,000 PubMed entries. It does not cover only process, function and location of genes, but also biomedical categories such as diseases, compounds, techniques and mutations. By bringing it all together, GoGene provides the most recent and most complete facts about genes and can rank them according to novelty and importance. GoGene accepts keywords, gene lists, gene sequences and protein sequences as input and supports search for genes in PubMed, EntrezGene and via BLAST. Since all associations of genes to terms are supported by evidence in the literature, the results are transparent and can be verified by the user. GoGene is available at http://gopubmed.org/gogene.

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.

GFFview: A Web Server for Parsing and Visualizing Annotation Information of Eukaryotic Genome.

Science.gov (United States)

Deng, Feilong; Chen, Shi-Yi; Wu, Zhou-Lin; Hu, Yongsong; Jia, Xianbo; Lai, Song-Jia

2017-10-01

Owing to wide application of RNA sequencing (RNA-seq) technology, more and more eukaryotic genomes have been extensively annotated, such as the gene structure, alternative splicing, and noncoding loci. Annotation information of genome is prevalently stored as plain text in General Feature Format (GFF), which could be hundreds or thousands Mb in size. Therefore, it is a challenge for manipulating GFF file for biologists who have no bioinformatic skill. In this study, we provide a web server (GFFview) for parsing the annotation information of eukaryotic genome and then generating statistical description of six indices for visualization. GFFview is very useful for investigating quality and difference of the de novo assembled transcriptome in RNA-seq studies.

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…

Publishing a Quality Context-aware Annotated Corpus and Lexicon for Harassment Research

OpenAIRE

Rezvan, Mohammadreza; Shekarpour, Saeedeh; Balasuriya, Lakshika; Thirunarayan, Krishnaprasad; Shalin, Valerie; Sheth, Amit

2018-01-01

Having a quality annotated corpus is essential especially for applied research. Despite the recent focus of Web science community on researching about cyberbullying, the community dose not still have standard benchmarks. In this paper, we publish first, a quality annotated corpus and second, an offensive words lexicon capturing different types type of harassment as (i) sexual harassment, (ii) racial harassment, (iii) appearance-related harassment, (iv) intellectual harassment, and (v) politic...

Reading Actively Online: An Exploratory Investigation of Online Annotation Tools for Inquiry Learning / La lecture active en ligne: étude exploratoire sur les outils d'annotation en ligne pour l'apprentissage par l’enquête

Directory of Open Access Journals (Sweden)

Jingyan Lu

2012-11-01

Full Text Available This study seeks to design and facilitate active reading among secondary school students with an online annotation tool – Diigo. Two classes of different academic performance levels were recruited to examine their annotation behavior and perceptions of Diigo. We wanted to determine whether the two classes differed in how they used Diigo; how they perceived Diigo; and whether how they used Diigo was related to how they perceived it. Using annotation data and surveys in which students reported on their use and perceptions of Diigo, we found that although the tool facilitated individual annotations, the two classes used and perceived it differently. Overall, the study showed Diigo to be a promising tool for enhancing active reading in the inquiry learning process. Cette étude vise à concevoir et à faciliter la lecture active chez les élèves du secondaire grâce à l’outil d'annotation en ligne Diigo. Deux classes avec des niveaux de rendement scolaire différents ont été retenues afin qu’on examine leur manière d’annoter et leur perception de Diigo. Nous avons voulu déterminer si les deux classes diffèrent dans leur façon d’utiliser Diigo, leur perception de Diigo, et si leur manière d’utiliser Diigo était liée à leur perception. En utilisant les données d'annotation et d'enquêtes dans lesquelles les élèves relataient leur utilisation et leur perception de Diigo, nous avons constaté que, même si l'outil a facilité les annotations individuelles, les deux classes l’ont utilisé et perçu différemment. Dans l'ensemble, l'étude a montré que Diigo est un outil prometteur pour l'amélioration de la lecture active dans le processus d'apprentissage par enquête.

A Methodology and Implementation for Annotating Digital Images for Context-appropriate Use in an Academic Health Care Environment

Science.gov (United States)

Goede, Patricia A.; Lauman, Jason R.; Cochella, Christopher; Katzman, Gregory L.; Morton, David A.; Albertine, Kurt H.

2004-01-01

Use of digital medical images has become common over the last several years, coincident with the release of inexpensive, mega-pixel quality digital cameras and the transition to digital radiology operation by hospitals. One problem that clinicians, medical educators, and basic scientists encounter when handling images is the difficulty of using business and graphic arts commercial-off-the-shelf (COTS) software in multicontext authoring and interactive teaching environments. The authors investigated and developed software-supported methodologies to help clinicians, medical educators, and basic scientists become more efficient and effective in their digital imaging environments. The software that the authors developed provides the ability to annotate images based on a multispecialty methodology for annotation and visual knowledge representation. This annotation methodology is designed by consensus, with contributions from the authors and physicians, medical educators, and basic scientists in the Departments of Radiology, Neurobiology and Anatomy, Dermatology, and Ophthalmology at the University of Utah. The annotation methodology functions as a foundation for creating, using, reusing, and extending dynamic annotations in a context-appropriate, interactive digital environment. The annotation methodology supports the authoring process as well as output and presentation mechanisms. The annotation methodology is the foundation for a Windows implementation that allows annotated elements to be represented as structured eXtensible Markup Language and stored separate from the image(s). PMID:14527971

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.

Annotated Bibliography of Law-Related Pollution Prevention Sources.

Science.gov (United States)

Lynch, Holly; Murphy, Elaine

This annotated bibliography of law-related pollution prevention sources was prepared by the National Pollution Prevention Center for Higher Education. Some topics of the items include waste reduction, hazardous wastes, risk reduction, environmental policy, pollution prevention, environmental protection, environmental leadership, environmental…

Annotating Evidence Based Clinical Guidelines : A Lightweight Ontology

NARCIS (Netherlands)

Hoekstra, R.; de Waard, A.; Vdovjak, R.; Paschke, A.; Burger, A.; Romano, P.; Marshall, M.S.; Splendiani, A.

2012-01-01

This paper describes a lightweight ontology for representing annotations of declarative evidence based clinical guidelines. We present the motivation and requirements for this representation, based on an analysis of several guidelines. The ontology provides the means to connect clinical questions

Douglas-fir tussock moth: an annotated bibliography.

Science.gov (United States)

Robert W. Campbell; Lorna C. Youngs

1978-01-01

This annotated bibliography includes references to 338 papers. Each deals in some way with either the Douglas-fir tussock moth, Orgyia pseudotsugata (McDunnough), or a related species. Specifically, 210 publications and 82 unpublished documents make some reference, at least, to the Douglas-fir tussock moth; 55 are concerned with other species in...

A framework for automatic annotation of web pages using the Google Rich Snippets vocabulary

NARCIS (Netherlands)

Meer, van der J.; Boon, F.; Hogenboom, F.P.; Frasincar, F.; Kaymak, U.

2011-01-01

One of the latest developments for the Semantic Web is Google Rich Snippets, a service that uses Web page annotations for displaying search results in a visually appealing manner. In this paper we propose the Automatic Review Recognition and annOtation of Web pages (ARROW) framework, which is able

Collaborative web-based annotation of video footage of deep-sea life, ecosystems and geological processes

Science.gov (United States)

Kottmann, R.; Ratmeyer, V.; Pop Ristov, A.; Boetius, A.

2012-04-01

More and more seagoing scientific expeditions use video-controlled research platforms such as Remote Operating Vehicles (ROV), Autonomous Underwater Vehicles (AUV), and towed camera systems. These produce many hours of video material which contains detailed and scientifically highly valuable footage of the biological, chemical, geological, and physical aspects of the oceans. Many of the videos contain unique observations of unknown life-forms which are rare, and which cannot be sampled and studied otherwise. To make such video material online accessible and to create a collaborative annotation environment the "Video Annotation and processing platform" (V-App) was developed. A first solely web-based installation for ROV videos is setup at the German Center for Marine Environmental Sciences (available at http://videolib.marum.de). It allows users to search and watch videos with a standard web browser based on the HTML5 standard. Moreover, V-App implements social web technologies allowing a distributed world-wide scientific community to collaboratively annotate videos anywhere at any time. It has several features fully implemented among which are: • User login system for fine grained permission and access control • Video watching • Video search using keywords, geographic position, depth and time range and any combination thereof • Video annotation organised in themes (tracks) such as biology and geology among others in standard or full screen mode • Annotation keyword management: Administrative users can add, delete, and update single keywords for annotation or upload sets of keywords from Excel-sheets • Download of products for scientific use This unique web application system helps making costly ROV videos online available (estimated cost range between 5.000 - 10.000 Euros per hour depending on the combination of ship and ROV). Moreover, with this system each expert annotation adds instantaneous available and valuable knowledge to otherwise uncharted

Annotation and retrieval system of CAD models based on functional semantics

Science.gov (United States)

Wang, Zhansong; Tian, Ling; Duan, Wenrui

2014-11-01

CAD model retrieval based on functional semantics is more significant than content-based 3D model retrieval during the mechanical conceptual design phase. However, relevant research is still not fully discussed. Therefore, a functional semantic-based CAD model annotation and retrieval method is proposed to support mechanical conceptual design and design reuse, inspire designer creativity through existing CAD models, shorten design cycle, and reduce costs. Firstly, the CAD model functional semantic ontology is constructed to formally represent the functional semantics of CAD models and describe the mechanical conceptual design space comprehensively and consistently. Secondly, an approach to represent CAD models as attributed adjacency graphs(AAG) is proposed. In this method, the geometry and topology data are extracted from STEP models. On the basis of AAG, the functional semantics of CAD models are annotated semi-automatically by matching CAD models that contain the partial features of which functional semantics have been annotated manually, thereby constructing CAD Model Repository that supports model retrieval based on functional semantics. Thirdly, a CAD model retrieval algorithm that supports multi-function extended retrieval is proposed to explore more potential creative design knowledge in the semantic level. Finally, a prototype system, called Functional Semantic-based CAD Model Annotation and Retrieval System(FSMARS), is implemented. A case demonstrates that FSMARS can successfully botain multiple potential CAD models that conform to the desired function. The proposed research addresses actual needs and presents a new way to acquire CAD models in the mechanical conceptual design phase.

Genome-wide annotation of the soybean WRKY family and functional characterization of genes involved in response to Phakopsora pachyrhizi infection.

Science.gov (United States)

Bencke-Malato, Marta; Cabreira, Caroline; Wiebke-Strohm, Beatriz; Bücker-Neto, Lauro; Mancini, Estefania; Osorio, Marina B; Homrich, Milena S; Turchetto-Zolet, Andreia Carina; De Carvalho, Mayra C C G; Stolf, Renata; Weber, Ricardo L M; Westergaard, Gastón; Castagnaro, Atílio P; Abdelnoor, Ricardo V; Marcelino-Guimarães, Francismar C; Margis-Pinheiro, Márcia; Bodanese-Zanettini, Maria Helena

2014-09-10

Many previous studies have shown that soybean WRKY transcription factors are involved in the plant response to biotic and abiotic stresses. Phakopsora pachyrhizi is the causal agent of Asian Soybean Rust, one of the most important soybean diseases. There are evidences that WRKYs are involved in the resistance of some soybean genotypes against that fungus. The number of WRKY genes already annotated in soybean genome was underrepresented. In the present study, a genome-wide annotation of the soybean WRKY family was carried out and members involved in the response to P. pachyrhizi were identified. As a result of a soybean genomic databases search, 182 WRKY-encoding genes were annotated and 33 putative pseudogenes identified. Genes involved in the response to P. pachyrhizi infection were identified using superSAGE, RNA-Seq of microdissected lesions and microarray experiments. Seventy-five genes were differentially expressed during fungal infection. The expression of eight WRKY genes was validated by RT-qPCR. The expression of these genes in a resistant genotype was earlier and/or stronger compared with a susceptible genotype in response to P. pachyrhizi infection. Soybean somatic embryos were transformed in order to overexpress or silence WRKY genes. Embryos overexpressing a WRKY gene were obtained, but they were unable to convert into plants. When infected with P. pachyrhizi, the leaves of the silenced transgenic line showed a higher number of lesions than the wild-type plants. The present study reports a genome-wide annotation of soybean WRKY family. The participation of some members in response to P. pachyrhizi infection was demonstrated. The results contribute to the elucidation of gene function and suggest the manipulation of WRKYs as a strategy to increase fungal resistance in soybean plants.

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.

Natural-Annotation-based Unsupervised Construction of Korean-Chinese Domain Dictionary

Science.gov (United States)

Liu, Wuying; Wang, Lin

2018-03-01

The large-scale bilingual parallel resource is significant to statistical learning and deep learning in natural language processing. This paper addresses the automatic construction issue of the Korean-Chinese domain dictionary, and presents a novel unsupervised construction method based on the natural annotation in the raw corpus. We firstly extract all Korean-Chinese word pairs from Korean texts according to natural annotations, secondly transform the traditional Chinese characters into the simplified ones, and finally distill out a bilingual domain dictionary after retrieving the simplified Chinese words in an extra Chinese domain dictionary. The experimental results show that our method can automatically build multiple Korean-Chinese domain dictionaries efficiently.

Automatically annotating web pages using Google Rich Snippets

NARCIS (Netherlands)

Hogenboom, F.P.; Frasincar, F.; Vandic, D.; Meer, van der J.; Boon, F.; Kaymak, U.

2011-01-01

We propose the Automatic Review Recognition and annO- tation of Web pages (ARROW) framework, a framework for Web page review identification and annotation using RDFa Google Rich Snippets. The ARROW framework consists of four steps: hotspot identification, subjectivity analysis, in- formation

Sequence-based feature prediction and annotation of proteins

DEFF Research Database (Denmark)

Juncker, Agnieszka; Jensen, Lars J.; Pierleoni, Andrea

2009-01-01

A recent trend in computational methods for annotation of protein function is that many prediction tools are combined in complex workflows and pipelines to facilitate the analysis of feature combinations, for example, the entire repertoire of kinase-binding motifs in the human proteome....

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.

Forecasting Reading Anxiety for Promoting English-Language Reading Performance Based on Reading Annotation Behavior

Science.gov (United States)

Chen, Chih-Ming; Wang, Jung-Ying; Chen, Yong-Ting; Wu, Jhih-Hao

2016-01-01

To reduce effectively the reading anxiety of learners while reading English articles, a C4.5 decision tree, a widely used data mining technique, was used to develop a personalized reading anxiety prediction model (PRAPM) based on individual learners' reading annotation behavior in a collaborative digital reading annotation system (CDRAS). In…

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.

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

Science.gov (United States)

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.

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.

Annotated Bibliography of EDGE2D Use

Energy Technology Data Exchange (ETDEWEB)

J.D. Strachan and G. Corrigan

2005-06-24

This annotated bibliography is intended to help EDGE2D users, and particularly new users, find existing published literature that has used EDGE2D. Our idea is that a person can find existing studies which may relate to his intended use, as well as gain ideas about other possible applications by scanning the attached tables.

Annotated Bibliography of EDGE2D Use

International Nuclear Information System (INIS)

Strachan, J.D.; Corrigan, G.

2005-01-01

This annotated bibliography is intended to help EDGE2D users, and particularly new users, find existing published literature that has used EDGE2D. Our idea is that a person can find existing studies which may relate to his intended use, as well as gain ideas about other possible applications by scanning the attached tables

The National Cancer Informatics Program (NCIP) Annotation and Image Markup (AIM) Foundation model.

Science.gov (United States)

Mongkolwat, Pattanasak; Kleper, Vladimir; Talbot, Skip; Rubin, Daniel

2014-12-01

Knowledge contained within in vivo imaging annotated by human experts or computer programs is typically stored as unstructured text and separated from other associated information. The National Cancer Informatics Program (NCIP) Annotation and Image Markup (AIM) Foundation information model is an evolution of the National Institute of Health's (NIH) National Cancer Institute's (NCI) Cancer Bioinformatics Grid (caBIG®) AIM model. The model applies to various image types created by various techniques and disciplines. It has evolved in response to the feedback and changing demands from the imaging community at NCI. The foundation model serves as a base for other imaging disciplines that want to extend the type of information the model collects. The model captures physical entities and their characteristics, imaging observation entities and their characteristics, markups (two- and three-dimensional), AIM statements, calculations, image source, inferences, annotation role, task context or workflow, audit trail, AIM creator details, equipment used to create AIM instances, subject demographics, and adjudication observations. An AIM instance can be stored as a Digital Imaging and Communications in Medicine (DICOM) structured reporting (SR) object or Extensible Markup Language (XML) document for further processing and analysis. An AIM instance consists of one or more annotations and associated markups of a single finding along with other ancillary information in the AIM model. An annotation describes information about the meaning of pixel data in an image. A markup is a graphical drawing placed on the image that depicts a region of interest. This paper describes fundamental AIM concepts and how to use and extend AIM for various imaging disciplines.

Wanda ML - a markup language for digital annotation

NARCIS (Netherlands)

Franke, K.Y.; Guyon, I.; Schomaker, L.R.B.; Vuurpijl, L.G.

2004-01-01

WANDAML is an XML-based markup language for the annotation and filter journaling of digital documents. It addresses in particular the needs of forensic handwriting data examination, by allowing experts to enter information about writer, material (pen, paper), script and content, and to record chains

An Oral History Annotation Tool for INTER-VIEWs

NARCIS (Netherlands)

Heuvel, H. van den; Sanders, E.P.; Rutten, R.; Scagliola, S.; Witkamp, P.

2012-01-01

We present a web-based tool for retrieving and annotating audio fragments of e.g. interviews. Our collection contains 250 interviews with veterans of Dutch conflicts and military missions. The audio files of the interviews were disclosed using ASR technology focussed at keyword retrieval. Resulting

The WANDAML Markup Language for Digital Document Annotation

NARCIS (Netherlands)

Franke, K.; Guyon, I.; Schomaker, L.; Vuurpijl, L.

2004-01-01

WANDAML is an XML-based markup language for the annotation and filter journaling of digital documents. It addresses in particular the needs of forensic handwriting data examination, by allowing experts to enter information about writer, material (pen, paper), script and content, and to record chains

Virtual Ribosome - a comprehensive DNA translation tool with support for integration of sequence feature annotation

DEFF Research Database (Denmark)

Wernersson, Rasmus

2006-01-01

of alternative start codons. ( ii) Integration of sequences feature annotation - in particular, native support for working with files containing intron/ exon structure annotation. The software is available for both download and online use at http://www.cbs.dtu.dk/services/VirtualRibosome/....

New genes expressed in human brains: implications for annotating evolving genomes.

Science.gov (United States)

Zhang, Yong E; Landback, Patrick; Vibranovski, Maria; Long, Manyuan

2012-11-01

New genes have frequently formed and spread to fixation in a wide variety of organisms, constituting abundant sets of lineage-specific genes. It was recently reported that an excess of primate-specific and human-specific genes were upregulated in the brains of fetuses and infants, and especially in the prefrontal cortex, which is involved in cognition. These findings reveal the prevalent addition of new genetic components to the transcriptome of the human brain. More generally, these findings suggest that genomes are continually evolving in both sequence and content, eroding the conservation endowed by common ancestry. Despite increasing recognition of the importance of new genes, we highlight here that these genes are still seriously under-characterized in functional studies and that new gene annotation is inconsistent in current practice. We propose an integrative approach to annotate new genes, taking advantage of functional and evolutionary genomic methods. We finally discuss how the refinement of new gene annotation will be important for the detection of evolutionary forces governing new gene origination. Copyright © 2012 WILEY Periodicals, Inc.

Fast and accurate semantic annotation of bioassays exploiting a hybrid of machine learning and user confirmation.

Science.gov (United States)

Clark, Alex M; Bunin, Barry A; Litterman, Nadia K; Schürer, Stephan C; Visser, Ubbo

2014-01-01

Bioinformatics and computer aided drug design rely on the curation of a large number of protocols for biological assays that measure the ability of potential drugs to achieve a therapeutic effect. These assay protocols are generally published by scientists in the form of plain text, which needs to be more precisely annotated in order to be useful to software methods. We have developed a pragmatic approach to describing assays according to the semantic definitions of the BioAssay Ontology (BAO) project, using a hybrid of machine learning based on natural language processing, and a simplified user interface designed to help scientists curate their data with minimum effort. We have carried out this work based on the premise that pure machine learning is insufficiently accurate, and that expecting scientists to find the time to annotate their protocols manually is unrealistic. By combining these approaches, we have created an effective prototype for which annotation of bioassay text within the domain of the training set can be accomplished very quickly. Well-trained annotations require single-click user approval, while annotations from outside the training set domain can be identified using the search feature of a well-designed user interface, and subsequently used to improve the underlying models. By drastically reducing the time required for scientists to annotate their assays, we can realistically advocate for semantic annotation to become a standard part of the publication process. Once even a small proportion of the public body of bioassay data is marked up, bioinformatics researchers can begin to construct sophisticated and useful searching and analysis algorithms that will provide a diverse and powerful set of tools for drug discovery researchers.

Fast and accurate semantic annotation of bioassays exploiting a hybrid of machine learning and user confirmation

Directory of Open Access Journals (Sweden)

Alex M. Clark

2014-08-01

Full Text Available Bioinformatics and computer aided drug design rely on the curation of a large number of protocols for biological assays that measure the ability of potential drugs to achieve a therapeutic effect. These assay protocols are generally published by scientists in the form of plain text, which needs to be more precisely annotated in order to be useful to software methods. We have developed a pragmatic approach to describing assays according to the semantic definitions of the BioAssay Ontology (BAO project, using a hybrid of machine learning based on natural language processing, and a simplified user interface designed to help scientists curate their data with minimum effort. We have carried out this work based on the premise that pure machine learning is insufficiently accurate, and that expecting scientists to find the time to annotate their protocols manually is unrealistic. By combining these approaches, we have created an effective prototype for which annotation of bioassay text within the domain of the training set can be accomplished very quickly. Well-trained annotations require single-click user approval, while annotations from outside the training set domain can be identified using the search feature of a well-designed user interface, and subsequently used to improve the underlying models. By drastically reducing the time required for scientists to annotate their assays, we can realistically advocate for semantic annotation to become a standard part of the publication process. Once even a small proportion of the public body of bioassay data is marked up, bioinformatics researchers can begin to construct sophisticated and useful searching and analysis algorithms that will provide a diverse and powerful set of tools for drug discovery researchers.

xGDBvm: A Web GUI-Driven Workflow for Annotating Eukaryotic Genomes in the Cloud[OPEN

Science.gov (United States)

Merchant, Nirav

2016-01-01

Genome-wide annotation of gene structure requires the integration of numerous computational steps. Currently, annotation is arguably best accomplished through collaboration of bioinformatics and domain experts, with broad community involvement. However, such a collaborative approach is not scalable at today’s pace of sequence generation. To address this problem, we developed the xGDBvm software, which uses an intuitive graphical user interface to access a number of common genome analysis and gene structure tools, preconfigured in a self-contained virtual machine image. Once their virtual machine instance is deployed through iPlant’s Atmosphere cloud services, users access the xGDBvm workflow via a unified Web interface to manage inputs, set program parameters, configure links to high-performance computing (HPC) resources, view and manage output, apply analysis and editing tools, or access contextual help. The xGDBvm workflow will mask the genome, compute spliced alignments from transcript and/or protein inputs (locally or on a remote HPC cluster), predict gene structures and gene structure quality, and display output in a public or private genome browser complete with accessory tools. Problematic gene predictions are flagged and can be reannotated using the integrated yrGATE annotation tool. xGDBvm can also be configured to append or replace existing data or load precomputed data. Multiple genomes can be annotated and displayed, and outputs can be archived for sharing or backup. xGDBvm can be adapted to a variety of use cases including de novo genome annotation, reannotation, comparison of different annotations, and training or teaching. PMID:27020957

DANN: a deep learning approach for annotating the pathogenicity of genetic variants.

Science.gov (United States)

Quang, Daniel; Chen, Yifei; Xie, Xiaohui

2015-03-01

Annotating genetic variants, especially non-coding variants, for the purpose of identifying pathogenic variants remains a challenge. Combined annotation-dependent depletion (CADD) is an algorithm designed to annotate both coding and non-coding variants, and has been shown to outperform other annotation algorithms. CADD trains a linear kernel support vector machine (SVM) to differentiate evolutionarily derived, likely benign, alleles from simulated, likely deleterious, variants. However, SVMs cannot capture non-linear relationships among the features, which can limit performance. To address this issue, we have developed DANN. DANN uses the same feature set and training data as CADD to train a deep neural network (DNN). DNNs can capture non-linear relationships among features and are better suited than SVMs for problems with a large number of samples and features. We exploit Compute Unified Device Architecture-compatible graphics processing units and deep learning techniques such as dropout and momentum training to accelerate the DNN training. DANN achieves about a 19% relative reduction in the error rate and about a 14% relative increase in the area under the curve (AUC) metric over CADD's SVM methodology. All data and source code are available at https://cbcl.ics.uci.edu/public_data/DANN/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Predicting Emotions in Facial Expressions from the Annotations in Naturally Occurring First Encounters

DEFF Research Database (Denmark)

Navarretta, Costanza

2014-01-01

This paper deals with the automatic identification of emotions from the manual annotations of the shape and functions of facial expressions in a Danish corpus of video recorded naturally occurring first encounters. More specifically, a support vector classified is trained on the corpus annotations...... to identify emotions in facial expressions. In the classification experiments, we test to what extent emotions expressed in naturally-occurring conversations can be identified automatically by a classifier trained on the manual annotations of the shape of facial expressions and co-occurring speech tokens. We...... also investigate the relation between emotions and the communicative functions of facial expressions. Both emotion labels and their values in a three dimensional space are identified. The three dimensions are Pleasure, Arousal and Dominance. The results of our experiments indicate that the classifiers...

Seeing the forest for the trees: annotating small RNA producing genes in plants.

Science.gov (United States)

Coruh, Ceyda; Shahid, Saima; Axtell, Michael J

2014-04-01

A key goal in genomics is the complete annotation of the expressed regions of the genome. In plants, substantial portions of the genome make regulatory small RNAs produced by Dicer-Like (DCL) proteins and utilized by Argonaute (AGO) proteins. These include miRNAs and various types of endogenous siRNAs. Small RNA-seq, enabled by cheap and fast DNA sequencing, has produced an enormous volume of data on plant miRNA and siRNA expression in recent years. In this review, we discuss recent progress in using small RNA-seq data to produce stable and reliable annotations of miRNA and siRNA genes in plants. In addition, we highlight key goals for the future of small RNA gene annotation in plants. Copyright © 2014 Elsevier Ltd. All rights reserved.

Persuasion: Attitude/Behavior Change. A Selected, Annotated Bibliography.

Science.gov (United States)

Benoit, William L.

Designed for teachers, students and researchers of the psychological dimensions of attitude and behavior change, this annotated bibliography lists books, bibliographies and articles on the subject ranging from general introductions and surveys through specific research studies, and from theoretical position essays to literature reviews. The 42…

A statistical framework to predict functional non-coding regions in the human genome through integrated analysis of annotation data.

Science.gov (United States)

Lu, Qiongshi; Hu, Yiming; Sun, Jiehuan; Cheng, Yuwei; Cheung, Kei-Hoi; Zhao, Hongyu

2015-05-27

Identifying functional regions in the human genome is a major goal in human genetics. Great efforts have been made to functionally annotate the human genome either through computational predictions, such as genomic conservation, or high-throughput experiments, such as the ENCODE project. These efforts have resulted in a rich collection of functional annotation data of diverse types that need to be jointly analyzed for integrated interpretation and annotation. Here we present GenoCanyon, a whole-genome annotation method that performs unsupervised statistical learning using 22 computational and experimental annotations thereby inferring the functional potential of each position in the human genome. With GenoCanyon, we are able to predict many of the known functional regions. The ability of predicting functional regions as well as its generalizable statistical framework makes GenoCanyon a unique and powerful tool for whole-genome annotation. The GenoCanyon web server is available at http://genocanyon.med.yale.edu.

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.

Semantic Annotation of Unstructured Documents Using Concepts Similarity

Directory of Open Access Journals (Sweden)

Fernando Pech