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Sample records for microbe gene ontology

  1. Gene Ontology

    Directory of Open Access Journals (Sweden)

    Gaston K. Mazandu

    2012-01-01

    Full Text Available The wide coverage and biological relevance of the Gene Ontology (GO, confirmed through its successful use in protein function prediction, have led to the growth in its popularity. In order to exploit the extent of biological knowledge that GO offers in describing genes or groups of genes, there is a need for an efficient, scalable similarity measure for GO terms and GO-annotated proteins. While several GO similarity measures exist, none adequately addresses all issues surrounding the design and usage of the ontology. We introduce a new metric for measuring the distance between two GO terms using the intrinsic topology of the GO-DAG, thus enabling the measurement of functional similarities between proteins based on their GO annotations. We assess the performance of this metric using a ROC analysis on human protein-protein interaction datasets and correlation coefficient analysis on the selected set of protein pairs from the CESSM online tool. This metric achieves good performance compared to the existing annotation-based GO measures. We used this new metric to assess functional similarity between orthologues, and show that it is effective at determining whether orthologues are annotated with similar functions and identifying cases where annotation is inconsistent between orthologues.

  2. Gene Ontology Consortium: going forward.

    Science.gov (United States)

    2015-01-01

    The Gene Ontology (GO; http://www.geneontology.org) is a community-based bioinformatics resource that supplies information about gene product function using ontologies to represent biological knowledge. Here we describe improvements and expansions to several branches of the ontology, as well as updates that have allowed us to more efficiently disseminate the GO and capture feedback from the research community. The Gene Ontology Consortium (GOC) has expanded areas of the ontology such as cilia-related terms, cell-cycle terms and multicellular organism processes. We have also implemented new tools for generating ontology terms based on a set of logical rules making use of templates, and we have made efforts to increase our use of logical definitions. The GOC has a new and improved web site summarizing new developments and documentation, serving as a portal to GO data. Users can perform GO enrichment analysis, and search the GO for terms, annotations to gene products, and associated metadata across multiple species using the all-new AmiGO 2 browser. We encourage and welcome the input of the research community in all biological areas in our continued effort to improve the Gene Ontology. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  3. Ontology - MicrobeDB.jp | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available gzip) consists of some directories (see the following table). Data file File name: ontology....tar.gz File URL: ftp://ftp.biosciencedbc.jp/archive/microbedb/LATEST/ontology.tar.gz File size: 9...he NCBI Taxonomy and INSDC ontology files were obtained from the DDBJ web site. O...ples Data item Description ontology/meo/meo.ttl An ontology for describing organismal habitats (especially focused on microbes). onto...logy/meo/meo_fma_mapping.ttl An ontology mapping files t

  4. Exploring autophagy with Gene Ontology

    Science.gov (United States)

    2018-01-01

    ABSTRACT Autophagy is a fundamental cellular process that is well conserved among eukaryotes. It is one of the strategies that cells use to catabolize substances in a controlled way. Autophagy is used for recycling cellular components, responding to cellular stresses and ridding cells of foreign material. Perturbations in autophagy have been implicated in a number of pathological conditions such as neurodegeneration, cardiac disease and cancer. The growing knowledge about autophagic mechanisms needs to be collected in a computable and shareable format to allow its use in data representation and interpretation. The Gene Ontology (GO) is a freely available resource that describes how and where gene products function in biological systems. It consists of 3 interrelated structured vocabularies that outline what gene products do at the biochemical level, where they act in a cell and the overall biological objectives to which their actions contribute. It also consists of ‘annotations’ that associate gene products with the terms. Here we describe how we represent autophagy in GO, how we create and define terms relevant to autophagy researchers and how we interrelate those terms to generate a coherent view of the process, therefore allowing an interoperable description of its biological aspects. We also describe how annotation of gene products with GO terms improves data analysis and interpretation, hence bringing a significant benefit to this field of study. PMID:29455577

  5. Visualizing conserved gene location across microbe genomes

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    Shaw, Chris D.

    2009-01-01

    This paper introduces an analysis-based zoomable visualization technique for displaying the location of genes across many related species of microbes. The purpose of this visualizatiuon is to enable a biologist to examine the layout of genes in the organism of interest with respect to the gene organization of related organisms. During the genomic annotation process, the ability to observe gene organization in common with previously annotated genomes can help a biologist better confirm the structure and function of newly analyzed microbe DNA sequences. We have developed a visualization and analysis tool that enables the biologist to observe and examine gene organization among genomes, in the context of the primary sequence of interest. This paper describes the visualization and analysis steps, and presents a case study using a number of Rickettsia genomes.

  6. Representing virus-host interactions and other multi-organism processes in the Gene Ontology.

    Science.gov (United States)

    Foulger, R E; Osumi-Sutherland, D; McIntosh, B K; Hulo, C; Masson, P; Poux, S; Le Mercier, P; Lomax, J

    2015-07-28

    The Gene Ontology project is a collaborative effort to provide descriptions of gene products in a consistent and computable language, and in a species-independent manner. The Gene Ontology is designed to be applicable to all organisms but up to now has been largely under-utilized for prokaryotes and viruses, in part because of a lack of appropriate ontology terms. To address this issue, we have developed a set of Gene Ontology classes that are applicable to microbes and their hosts, improving both coverage and quality in this area of the Gene Ontology. Describing microbial and viral gene products brings with it the additional challenge of capturing both the host and the microbe. Recognising this, we have worked closely with annotation groups to test and optimize the GO classes, and we describe here a set of annotation guidelines that allow the controlled description of two interacting organisms. Building on the microbial resources already in existence such as ViralZone, UniProtKB keywords and MeGO, this project provides an integrated ontology to describe interactions between microbial species and their hosts, with mappings to the external resources above. Housing this information within the freely-accessible Gene Ontology project allows the classes and annotation structure to be utilized by a large community of biologists and users.

  7. An Ontology-Based GIS for Genomic Data Management of Rumen Microbes.

    Science.gov (United States)

    Jelokhani-Niaraki, Saber; Tahmoorespur, Mojtaba; Minuchehr, Zarrin; Nassiri, Mohammad Reza

    2015-03-01

    During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and Protégé as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.

  8. An Ontology-Based GIS for Genomic Data Management of Rumen Microbes

    Directory of Open Access Journals (Sweden)

    Saber Jelokhani-Niaraki

    2015-03-01

    Full Text Available During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and Protégé as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.

  9. An Ontology-Based GIS for Genomic Data Management of Rumen Microbes

    Science.gov (United States)

    Jelokhani-Niaraki, Saber; Minuchehr, Zarrin; Nassiri, Mohammad Reza

    2015-01-01

    During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and Protégé as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data. PMID:25873847

  10. Defining functional distances over Gene Ontology

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    del Pozo Angela

    2008-01-01

    Full Text Available Abstract Background A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-structured ontologies exist regarding the activity of proteins (i.e. 'gene ontology' -GO-. However, functional metrics can overcome the problems in the comparing and evaluating functional assignments and predictions. As a reference of proximity, previous approaches to compare GO terms considered linkage in terms of ontology weighted by a probability distribution that balances the non-uniform 'richness' of different parts of the Direct Acyclic Graph. Here, we have followed a different approach to quantify functional similarities between GO terms. Results We propose a new method to derive 'functional distances' between GO terms that is based on the simultaneous occurrence of terms in the same set of Interpro entries, instead of relying on the structure of the GO. The coincidence of GO terms reveals natural biological links between the GO functions and defines a distance model Df which fulfils the properties of a Metric Space. The distances obtained in this way can be represented as a hierarchical 'Functional Tree'. Conclusion The method proposed provides a new definition of distance that enables the similarity between GO terms to be quantified. Additionally, the 'Functional Tree' defines groups with biological meaning enhancing its utility for protein function comparison and prediction. Finally, this approach could be for function-based protein searches in databases, and for analysing the gene clusters produced by DNA array experiments.

  11. The Gene Ontology (GO) Cellular Component Ontology: integration with SAO (Subcellular Anatomy Ontology) and other recent developments

    Science.gov (United States)

    2013-01-01

    Background The Gene Ontology (GO) (http://www.geneontology.org/) contains a set of terms for describing the activity and actions of gene products across all kingdoms of life. Each of these activities is executed in a location within a cell or in the vicinity of a cell. In order to capture this context, the GO includes a sub-ontology called the Cellular Component (CC) ontology (GO-CCO). The primary use of this ontology is for GO annotation, but it has also been used for phenotype annotation, and for the annotation of images. Another ontology with similar scope to the GO-CCO is the Subcellular Anatomy Ontology (SAO), part of the Neuroscience Information Framework Standard (NIFSTD) suite of ontologies. The SAO also covers cell components, but in the domain of neuroscience. Description Recently, the GO-CCO was enriched in content and links to the Biological Process and Molecular Function branches of GO as well as to other ontologies. This was achieved in several ways. We carried out an amalgamation of SAO terms with GO-CCO ones; as a result, nearly 100 new neuroscience-related terms were added to the GO. The GO-CCO also contains relationships to GO Biological Process and Molecular Function terms, as well as connecting to external ontologies such as the Cell Ontology (CL). Terms representing protein complexes in the Protein Ontology (PRO) reference GO-CCO terms for their species-generic counterparts. GO-CCO terms can also be used to search a variety of databases. Conclusions In this publication we provide an overview of the GO-CCO, its overall design, and some recent extensions that make use of additional spatial information. One of the most recent developments of the GO-CCO was the merging in of the SAO, resulting in a single unified ontology designed to serve the needs of GO annotators as well as the specific needs of the neuroscience community. PMID:24093723

  12. Gene function prediction based on Gene Ontology Hierarchy Preserving Hashing.

    Science.gov (United States)

    Zhao, Yingwen; Fu, Guangyuan; Wang, Jun; Guo, Maozu; Yu, Guoxian

    2018-02-23

    Gene Ontology (GO) uses structured vocabularies (or terms) to describe the molecular functions, biological roles, and cellular locations of gene products in a hierarchical ontology. GO annotations associate genes with GO terms and indicate the given gene products carrying out the biological functions described by the relevant terms. However, predicting correct GO annotations for genes from a massive set of GO terms as defined by GO is a difficult challenge. To combat with this challenge, we introduce a Gene Ontology Hierarchy Preserving Hashing (HPHash) based semantic method for gene function prediction. HPHash firstly measures the taxonomic similarity between GO terms. It then uses a hierarchy preserving hashing technique to keep the hierarchical order between GO terms, and to optimize a series of hashing functions to encode massive GO terms via compact binary codes. After that, HPHash utilizes these hashing functions to project the gene-term association matrix into a low-dimensional one and performs semantic similarity based gene function prediction in the low-dimensional space. Experimental results on three model species (Homo sapiens, Mus musculus and Rattus norvegicus) for interspecies gene function prediction show that HPHash performs better than other related approaches and it is robust to the number of hash functions. In addition, we also take HPHash as a plugin for BLAST based gene function prediction. From the experimental results, HPHash again significantly improves the prediction performance. The codes of HPHash are available at: http://mlda.swu.edu.cn/codes.php?name=HPHash. Copyright © 2018 Elsevier Inc. All rights reserved.

  13. Extracting Cross-Ontology Weighted Association Rules from Gene Ontology Annotations.

    Science.gov (United States)

    Agapito, Giuseppe; Milano, Marianna; Guzzi, Pietro Hiram; Cannataro, Mario

    2016-01-01

    Gene Ontology (GO) is a structured repository of concepts (GO Terms) that are associated to one or more gene products through a process referred to as annotation. The analysis of annotated data is an important opportunity for bioinformatics. There are different approaches of analysis, among those, the use of association rules (AR) which provides useful knowledge, discovering biologically relevant associations between terms of GO, not previously known. In a previous work, we introduced GO-WAR (Gene Ontology-based Weighted Association Rules), a methodology for extracting weighted association rules from ontology-based annotated datasets. We here adapt the GO-WAR algorithm to mine cross-ontology association rules, i.e., rules that involve GO terms present in the three sub-ontologies of GO. We conduct a deep performance evaluation of GO-WAR by mining publicly available GO annotated datasets, showing how GO-WAR outperforms current state of the art approaches.

  14. Gene Ontology-Based Analysis of Zebrafish Omics Data Using the Web Tool Comparative Gene Ontology.

    Science.gov (United States)

    Ebrahimie, Esmaeil; Fruzangohar, Mario; Moussavi Nik, Seyyed Hani; Newman, Morgan

    2017-10-01

    Gene Ontology (GO) analysis is a powerful tool in systems biology, which uses a defined nomenclature to annotate genes/proteins within three categories: "Molecular Function," "Biological Process," and "Cellular Component." GO analysis can assist in revealing functional mechanisms underlying observed patterns in transcriptomic, genomic, and proteomic data. The already extensive and increasing use of zebrafish for modeling genetic and other diseases highlights the need to develop a GO analytical tool for this organism. The web tool Comparative GO was originally developed for GO analysis of bacterial data in 2013 ( www.comparativego.com ). We have now upgraded and elaborated this web tool for analysis of zebrafish genetic data using GOs and annotations from the Gene Ontology Consortium.

  15. Fast gene ontology based clustering for microarray experiments.

    Science.gov (United States)

    Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

    2008-11-21

    Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

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

    Directory of Open Access Journals (Sweden)

    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

  17. Integrating Ontological Knowledge and Textual Evidence in Estimating Gene and Gene Product Similarity

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Posse, Christian; Gopalan, Banu; Tratz, Stephen C.; Gregory, Michelle L.

    2006-06-08

    With the rising influence of the Gene On-tology, new approaches have emerged where the similarity between genes or gene products is obtained by comparing Gene Ontology code annotations associ-ated with them. So far, these approaches have solely relied on the knowledge en-coded in the Gene Ontology and the gene annotations associated with the Gene On-tology database. The goal of this paper is to demonstrate that improvements to these approaches can be obtained by integrating textual evidence extracted from relevant biomedical literature.

  18. Bayesian assignment of gene ontology terms to gene expression experiments.

    Science.gov (United States)

    Sykacek, P

    2012-09-15

    Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Source code under GPL license is available from the author. peter.sykacek@boku.ac.at.

  19. Bayesian assignment of gene ontology terms to gene expression experiments

    Science.gov (United States)

    Sykacek, P.

    2012-01-01

    Motivation: Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. Results: This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Availability: Source code under GPL license is available from the author. Contact: peter.sykacek@boku.ac.at PMID:22962488

  20. Exploring the Optimal Strategy to Predict Essential Genes in Microbes

    Directory of Open Access Journals (Sweden)

    Yao Lu

    2011-12-01

    Full Text Available Accurately predicting essential genes is important in many aspects of biology, medicine and bioengineering. In previous research, we have developed a machine learning based integrative algorithm to predict essential genes in bacterial species. This algorithm lends itself to two approaches for predicting essential genes: learning the traits from known essential genes in the target organism, or transferring essential gene annotations from a closely related model organism. However, for an understudied microbe, each approach has its potential limitations. The first is constricted by the often small number of known essential genes. The second is limited by the availability of model organisms and by evolutionary distance. In this study, we aim to determine the optimal strategy for predicting essential genes by examining four microbes with well-characterized essential genes. Our results suggest that, unless the known essential genes are few, learning from the known essential genes in the target organism usually outperforms transferring essential gene annotations from a related model organism. In fact, the required number of known essential genes is surprisingly small to make accurate predictions. In prokaryotes, when the number of known essential genes is greater than 2% of total genes, this approach already comes close to its optimal performance. In eukaryotes, achieving the same best performance requires over 4% of total genes, reflecting the increased complexity of eukaryotic organisms. Combining the two approaches resulted in an increased performance when the known essential genes are few. Our investigation thus provides key information on accurately predicting essential genes and will greatly facilitate annotations of microbial genomes.

  1. Fast Gene Ontology based clustering for microarray experiments

    Directory of Open Access Journals (Sweden)

    Ovaska Kristian

    2008-11-01

    Full Text Available Abstract Background Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. Results We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Conclusion Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

  2. Genetic Resources for Advanced Biofuel Production Described with the Gene Ontology

    Directory of Open Access Journals (Sweden)

    Trudy eTorto-Alalibo

    2014-10-01

    Full Text Available Dramatic increases in research in the area of microbial biofuel production coupled with high-throughput data generation on bioenergy-related microbes has led to a deluge of information in the scientific literature and in databases. Consolidating this information and making it easily accessible requires a unified vocabulary. The Gene Ontology (GO fulfills that requirement, as it is a well-developed structured vocabulary that describes the activities and locations of gene products in a consistent manner across all kingdoms of life. The Microbial Energy Gene Ontology (MENGO: http://www.mengo.biochem.vt.edu project is extending the GO to include new terms to describe microbial processes of interest to bioenergy production. Our effort has added over 600 bioenergy related terms to the Gene Ontology. These terms will aid in the comprehensive annotation of gene products from diverse energy-related microbial genomes. An area of microbial energy research that has received a lot of attention is microbial production of advanced biofuels. These include alcohols such as butanol, isopropanol, isobutanol, and fuels derived from fatty acids, isoprenoids, and polyhydroxyalkanoates. These fuels are superior to first generation biofuels (ethanol and biodiesel esterified from vegetable oil or animal fat, can be generated from non-food feedstock sources, can be used as supplements or substitutes for gasoline, diesel and jet fuels, and can be stored and distributed using existing infrastructure. Here we review the roles of genes associated with synthesis of advanced biofuels, and at the same time introduce the use of the GO to describe the functions of these genes in a standardized way.

  3. Prediction of human protein function according to Gene Ontology categories

    DEFF Research Database (Denmark)

    Jensen, Lars Juhl; Gupta, Ramneek; Stærfeldt, Hans Henrik

    2003-01-01

    developed a method for prediction of protein function for a subset of classes from the Gene Ontology classification scheme. This subset includes several pharmaceutically interesting categories-transcription factors, receptors, ion channels, stress and immune response proteins, hormones and growth factors...

  4. Dovetailing biology and chemistry: integrating the Gene Ontology with the ChEBI chemical ontology

    Science.gov (United States)

    2013-01-01

    Background The Gene Ontology (GO) facilitates the description of the action of gene products in a biological context. Many GO terms refer to chemical entities that participate in biological processes. To facilitate accurate and consistent systems-wide biological representation, it is necessary to integrate the chemical view of these entities with the biological view of GO functions and processes. We describe a collaborative effort between the GO and the Chemical Entities of Biological Interest (ChEBI) ontology developers to ensure that the representation of chemicals in the GO is both internally consistent and in alignment with the chemical expertise captured in ChEBI. Results We have examined and integrated the ChEBI structural hierarchy into the GO resource through computationally-assisted manual curation of both GO and ChEBI. Our work has resulted in the creation of computable definitions of GO terms that contain fully defined semantic relationships to corresponding chemical terms in ChEBI. Conclusions The set of logical definitions using both the GO and ChEBI has already been used to automate aspects of GO development and has the potential to allow the integration of data across the domains of biology and chemistry. These logical definitions are available as an extended version of the ontology from http://purl.obolibrary.org/obo/go/extensions/go-plus.owl. PMID:23895341

  5. Classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning

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    Tsatsoulis Costas

    2010-05-01

    Full Text Available Abstract Background There is increasing evidence that gene location and surrounding genes influence the functionality of genes in the eukaryotic genome. Knowing the Gene Ontology Slim terms associated with a gene gives us insight into a gene's functionality by informing us how its gene product behaves in a cellular context using three different ontologies: molecular function, biological process, and cellular component. In this study, we analyzed if we could classify a gene in Saccharomyces cerevisiae to its correct Gene Ontology Slim term using information about its location in the genome and information from its nearest-neighbouring genes using classification learning. Results We performed experiments to establish that the MultiBoostAB algorithm using the J48 classifier could correctly classify Gene Ontology Slim terms of a gene given information regarding the gene's location and information from its nearest-neighbouring genes for training. Different neighbourhood sizes were examined to determine how many nearest neighbours should be included around each gene to provide better classification rules. Our results show that by just incorporating neighbour information from each gene's two-nearest neighbours, the percentage of correctly classified genes to their correct Gene Ontology Slim term for each ontology reaches over 80% with high accuracy (reflected in F-measures over 0.80 of the classification rules produced. Conclusions We confirmed that in classifying genes to their correct Gene Ontology Slim term, the inclusion of neighbour information from those genes is beneficial. Knowing the location of a gene and the Gene Ontology Slim information from neighbouring genes gives us insight into that gene's functionality. This benefit is seen by just including information from a gene's two-nearest neighbouring genes.

  6. Protein Annotation from Protein Interaction Networks and Gene Ontology

    OpenAIRE

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

    2011-01-01

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

  7. [Key effect genes responding to nerve injury identified by gene ontology and computer pattern recognition].

    Science.gov (United States)

    Pan, Qian; Peng, Jin; Zhou, Xue; Yang, Hao; Zhang, Wei

    2012-07-01

    In order to screen out important genes from large gene data of gene microarray after nerve injury, we combine gene ontology (GO) method and computer pattern recognition technology to find key genes responding to nerve injury, and then verify one of these screened-out genes. Data mining and gene ontology analysis of gene chip data GSE26350 was carried out through MATLAB software. Cd44 was selected from screened-out key gene molecular spectrum by comparing genes' different GO terms and positions on score map of principal component. Function interferences were employed to influence the normal binding of Cd44 and one of its ligands, chondroitin sulfate C (CSC), to observe neurite extension. Gene ontology analysis showed that the first genes on score map (marked by red *) mainly distributed in molecular transducer activity, receptor activity, protein binding et al molecular function GO terms. Cd44 is one of six effector protein genes, and attracted us with its function diversity. After adding different reagents into the medium to interfere the normal binding of CSC and Cd44, varying-degree remissions of CSC's inhibition on neurite extension were observed. CSC can inhibit neurite extension through binding Cd44 on the neuron membrane. This verifies that important genes in given physiological processes can be identified by gene ontology analysis of gene chip data.

  8. GOseek: a gene ontology search engine using enhanced keywords.

    Science.gov (United States)

    Taha, Kamal

    2013-01-01

    We propose in this paper a biological search engine called GOseek, which overcomes the limitation of current gene similarity tools. Given a set of genes, GOseek returns the most significant genes that are semantically related to the given genes. These returned genes are usually annotated to one of the Lowest Common Ancestors (LCA) of the Gene Ontology (GO) terms annotating the given genes. Most genes have several annotation GO terms. Therefore, there may be more than one LCA for the GO terms annotating the given genes. The LCA annotating the genes that are most semantically related to the given gene is the one that receives the most aggregate semantic contribution from the GO terms annotating the given genes. To identify this LCA, GOseek quantifies the contribution of the GO terms annotating the given genes to the semantics of their LCAs. That is, it encodes the semantic contribution into a numeric format. GOseek uses microarray experiment data to rank result genes based on their significance. We evaluated GOseek experimentally and compared it with a comparable gene prediction tool. Results showed marked improvement over the tool.

  9. Comparative GO: a web application for comparative gene ontology and gene ontology-based gene selection in bacteria.

    Directory of Open Access Journals (Sweden)

    Mario Fruzangohar

    Full Text Available The primary means of classifying new functions for genes and proteins relies on Gene Ontology (GO, which defines genes/proteins using a controlled vocabulary in terms of their Molecular Function, Biological Process and Cellular Component. The challenge is to present this information to researchers to compare and discover patterns in multiple datasets using visually comprehensible and user-friendly statistical reports. Importantly, while there are many GO resources available for eukaryotes, there are none suitable for simultaneous, graphical and statistical comparison between multiple datasets. In addition, none of them supports comprehensive resources for bacteria. By using Streptococcus pneumoniae as a model, we identified and collected GO resources including genes, proteins, taxonomy and GO relationships from NCBI, UniProt and GO organisations. Then, we designed database tables in PostgreSQL database server and developed a Java application to extract data from source files and loaded into database automatically. We developed a PHP web application based on Model-View-Control architecture, used a specific data structure as well as current and novel algorithms to estimate GO graphs parameters. We designed different navigation and visualization methods on the graphs and integrated these into graphical reports. This tool is particularly significant when comparing GO groups between multiple samples (including those of pathogenic bacteria from different sources simultaneously. Comparing GO protein distribution among up- or down-regulated genes from different samples can improve understanding of biological pathways, and mechanism(s of infection. It can also aid in the discovery of genes associated with specific function(s for investigation as a novel vaccine or therapeutic targets.http://turing.ersa.edu.au/BacteriaGO.

  10. Gene ontology based transfer learning for protein subcellular localization

    Directory of Open Access Journals (Sweden)

    Zhou Shuigeng

    2011-02-01

    Full Text Available Abstract Background Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as GO, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the GO terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology. Results In this paper, we propose a Gene Ontology Based Transfer Learning Model (GO-TLM for large-scale protein subcellular localization. The model transfers the signature-based homologous GO terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false GO terms that are resulted from evolutionary divergence. We derive three GO kernels from the three aspects of gene ontology to measure the GO similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for

  11. Correlating Information Contents of Gene Ontology Terms to Infer Semantic Similarity of Gene Products

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    Mingxin Gan

    2014-01-01

    Full Text Available Successful applications of the gene ontology to the inference of functional relationships between gene products in recent years have raised the need for computational methods to automatically calculate semantic similarity between gene products based on semantic similarity of gene ontology terms. Nevertheless, existing methods, though having been widely used in a variety of applications, may significantly overestimate semantic similarity between genes that are actually not functionally related, thereby yielding misleading results in applications. To overcome this limitation, we propose to represent a gene product as a vector that is composed of information contents of gene ontology terms annotated for the gene product, and we suggest calculating similarity between two gene products as the relatedness of their corresponding vectors using three measures: Pearson’s correlation coefficient, cosine similarity, and the Jaccard index. We focus on the biological process domain of the gene ontology and annotations of yeast proteins to study the effectiveness of the proposed measures. Results show that semantic similarity scores calculated using the proposed measures are more consistent with known biological knowledge than those derived using a list of existing methods, suggesting the effectiveness of our method in characterizing functional relationships between gene products.

  12. Protein annotation from protein interaction networks and Gene Ontology.

    Science.gov (United States)

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

    2011-10-01

    We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

  13. Text Mining to Support Gene Ontology Curation and Vice Versa.

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    Ruch, Patrick

    2017-01-01

    In this chapter, we explain how text mining can support the curation of molecular biology databases dealing with protein functions. We also show how curated data can play a disruptive role in the developments of text mining methods. We review a decade of efforts to improve the automatic assignment of Gene Ontology (GO) descriptors, the reference ontology for the characterization of genes and gene products. To illustrate the high potential of this approach, we compare the performances of an automatic text categorizer and show a large improvement of +225 % in both precision and recall on benchmarked data. We argue that automatic text categorization functions can ultimately be embedded into a Question-Answering (QA) system to answer questions related to protein functions. Because GO descriptors can be relatively long and specific, traditional QA systems cannot answer such questions. A new type of QA system, so-called Deep QA which uses machine learning methods trained with curated contents, is thus emerging. Finally, future advances of text mining instruments are directly dependent on the availability of high-quality annotated contents at every curation step. Databases workflows must start recording explicitly all the data they curate and ideally also some of the data they do not curate.

  14. Determining the semantic similarities among Gene Ontology terms.

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    Taha, Kamal

    2013-05-01

    We present in this paper novel techniques that determine the semantic relationships among GeneOntology (GO) terms. We implemented these techniques in a prototype system called GoSE, which resides between user application and GO database. Given a set S of GO terms, GoSE would return another set S' of GO terms, where each term in S' is semantically related to each term in S. Most current research is focused on determining the semantic similarities among GO ontology terms based solely on their IDs and proximity to one another in the GO graph structure, while overlooking the contexts of the terms, which may lead to erroneous results. The context of a GO term T is the set of other terms, whose existence in the GO graph structure is dependent on T. We propose novel techniques that determine the contexts of terms based on the concept of existence dependency. We present a stack-based sort-merge algorithm employing these techniques for determining the semantic similarities among GO terms.We evaluated GoSE experimentally and compared it with three existing methods. The results of measuring the semantic similarities among genes in KEGG and Pfam pathways retrieved from the DBGET and Sanger Pfam databases, respectively, have shown that our method outperforms the other three methods in recall and precision.

  15. GOPET: A tool for automated predictions of Gene Ontology terms

    Directory of Open Access Journals (Sweden)

    Glatting Karl-Heinz

    2006-03-01

    Full Text Available Abstract Background Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These methods, however, either apply to specific subsets, or their predictions are not formalised, or they do not provide precise confidence values for their predictions. Description We recently established a learning system for automated annotation, trained with a broad variety of different organisms to predict the standardised annotation terms from Gene Ontology (GO. Now, this method has been made available to the public via our web-service GOPET (Gene Ontology term Prediction and Evaluation Tool. It supplies annotation for sequences of any organism. For each predicted term an appropriate confidence value is provided. The basic method had been developed for predicting molecular function GO-terms. It is now expanded to predict biological process terms. This web service is available via http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar Conclusion Our web service gives experimental researchers as well as the bioinformatics community a valuable sequence annotation device. Additionally, GOPET also provides less significant annotation data which may serve as an extended discovery platform for the user.

  16. The representation of heart development in the gene ontology.

    Science.gov (United States)

    Khodiyar, Varsha K; Hill, David P; Howe, Doug; Berardini, Tanya Z; Tweedie, Susan; Talmud, Philippa J; Breckenridge, Ross; Bhattarcharya, Shoumo; Riley, Paul; Scambler, Peter; Lovering, Ruth C

    2011-06-01

    An understanding of heart development is critical in any systems biology approach to cardiovascular disease. The interpretation of data generated from high-throughput technologies (such as microarray and proteomics) is also essential to this approach. However, characterizing the role of genes in the processes underlying heart development and cardiovascular disease involves the non-trivial task of data analysis and integration of previous knowledge. The Gene Ontology (GO) Consortium provides structured controlled biological vocabularies that are used to summarize previous functional knowledge for gene products across all species. One aspect of GO describes biological processes, such as development and signaling. In order to support high-throughput cardiovascular research, we have initiated an effort to fully describe heart development in GO; expanding the number of GO terms describing heart development from 12 to over 280. This new ontology describes heart morphogenesis, the differentiation of specific cardiac cell types, and the involvement of signaling pathways in heart development. This work also aligns GO with the current views of the heart development research community and its representation in the literature. This extension of GO allows gene product annotators to comprehensively capture the genetic program leading to the developmental progression of the heart. This will enable users to integrate heart development data across species, resulting in the comprehensive retrieval of information about this subject. The revised GO structure, combined with gene product annotations, should improve the interpretation of data from high-throughput methods in a variety of cardiovascular research areas, including heart development, congenital cardiac disease, and cardiac stem cell research. Additionally, we invite the heart development community to contribute to the expansion of this important dataset for the benefit of future research in this area. Copyright © 2011

  17. The Representation of Heart Development in the Gene Ontology

    Science.gov (United States)

    Khodiyar, Varsha K.; Hill, David P.; Howe, Doug; Berardini, Tanya Z.; Tweedie, Susan; Talmud, Philippa J.; Breckenridge, Ross; Bhattarcharya, Shoumo; Riley, Paul; Scambler, Peter; Lovering, Ruth C.

    2012-01-01

    An understanding of heart development is critical in any systems biology approach to cardiovascular disease. The interpretation of data generated from high-throughput technologies (such as microarray and proteomics) is also essential to this approach. However, characterizing the role of genes in the processes underlying heart development and cardiovascular disease involves the non-trivial task of data analysis and integration of previous knowledge. The Gene Ontology (GO) Consortium provides structured controlled biological vocabularies that are used to summarize previous functional knowledge for gene products across all species. One aspect of GO describes biological processes, such as development and signaling. In order to support high-throughput cardiovascular research, we have initiated an effort to fully describe heart development in GO; expanding the number of GO terms describing heart development from 12 to over 280. This new ontology describes heart morphogenesis, the differentiation of specific cardiac cell types, and the involvement of signaling pathways in heart development and aligns GO with the current views of the heart development research community and its representation in the literature. This extension of GO allows gene product annotators to comprehensively capture the genetic program leading to the developmental progression of the heart. This will enable users to integrate heart development data across species, resulting in the comprehensive retrieval of information about this subject. The revised GO structure, combined with gene product annotations, should improve the interpretation of data from high-throughput methods in a variety of cardiovascular research areas, including heart development, congenital cardiac disease, and cardiac stem cell research. Additionally, we invite the heart development community to contribute to the expansion of this important dataset for the benefit of future research in this area. PMID:21419760

  18. Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships.

    Science.gov (United States)

    Manda, Prashanti; McCarthy, Fiona; Bridges, Susan M

    2013-10-01

    The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

  19. Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology.

    Science.gov (United States)

    Lovering, Ruth C; Roncaglia, Paola; Howe, Douglas G; Laulederkind, Stanley J F; Khodiyar, Varsha K; Berardini, Tanya Z; Tweedie, Susan; Foulger, Rebecca E; Osumi-Sutherland, David; Campbell, Nancy H; Huntley, Rachael P; Talmud, Philippa J; Blake, Judith A; Breckenridge, Ross; Riley, Paul R; Lambiase, Pier D; Elliott, Perry M; Clapp, Lucie; Tinker, Andrew; Hill, David P

    2018-02-01

    A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. © 2018 The Authors.

  20. Codon bias and gene ontology in holometabolous and hemimetabolous insects.

    Science.gov (United States)

    Carlini, David B; Makowski, Matthew

    2015-12-01

    The relationship between preferred codon use (PCU), developmental mode, and gene ontology (GO) was investigated in a sample of nine insect species with sequenced genomes. These species were selected to represent two distinct modes of insect development, holometabolism and hemimetabolism, with an aim toward determining whether the differences in developmental timing concomitant with developmental mode would be mirrored by differences in PCU in their developmental genes. We hypothesized that the developmental genes of holometabolous insects should be under greater selective pressure for efficient translation, manifest as increased PCU, than those of hemimetabolous insects because holometabolism requires abundant protein expression over shorter time intervals than hemimetabolism, where proteins are required more uniformly in time. Preferred codon sets were defined for each species, from which the frequency of PCU for each gene was obtained. Although there were substantial differences in the genomic base composition of holometabolous and hemimetabolous insects, both groups exhibited a general preference for GC-ending codons, with the former group having higher PCU averaged across all genes. For each species, the biological process GO term for each gene was assigned that of its Drosophila homolog(s), and PCU was calculated for each GO term category. The top two GO term categories for PCU enrichment in the holometabolous insects were anatomical structure development and cell differentiation. The increased PCU in the developmental genes of holometabolous insects may reflect a general strategy to maximize the protein production of genes expressed in bursts over short time periods, e.g., heat shock proteins. J. Exp. Zool. (Mol. Dev. Evol.) 324B: 686-698, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  1. Networks in biological systems: An investigation of the Gene Ontology as an evolving network

    International Nuclear Information System (INIS)

    Coronnello, C; Tumminello, M; Micciche, S; Mantegna, R.N.

    2009-01-01

    Many biological systems can be described as networks where different elements interact, in order to perform biological processes. We introduce a network associated with the Gene Ontology. Specifically, we construct a correlation-based network where the vertices are the terms of the Gene Ontology and the link between each two terms is weighted on the basis of the number of genes that they have in common. We analyze a filtered network obtained from the correlation-based network and we characterize its evolution over different releases of the Gene Ontology.

  2. 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).

  3. A methodology to migrate the gene ontology to a description logic environment using DAML+OIL.

    Science.gov (United States)

    Wroe, C J; Stevens, R; Goble, C A; Ashburner, M

    2003-01-01

    The Gene Ontology Next Generation Project (GONG) is developing a staged methodology to evolve the current representation of the Gene Ontology into DAML+OIL in order to take advantage of the richer formal expressiveness and the reasoning capabilities of the underlying description logic. Each stage provides a step level increase in formal explicit semantic content with a view to supporting validation, extension and multiple classification of the Gene Ontology. The paper introduces DAML+OIL and demonstrates the activity within each stage of the methodology and the functionality gained.

  4. 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.

  5. Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

    Science.gov (United States)

    Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

    2014-01-01

    Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

  6. The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach.

    Science.gov (United States)

    Hindumathi, V; Kranthi, T; Rao, S B; Manimaran, P

    2014-06-01

    With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

  7. Multi-label literature classification based on the Gene Ontology graph

    Directory of Open Access Journals (Sweden)

    Lu Xinghua

    2008-12-01

    Full Text Available Abstract Background The Gene Ontology is a controlled vocabulary for representing knowledge related to genes and proteins in a computable form. The current effort of manually annotating proteins with the Gene Ontology is outpaced by the rate of accumulation of biomedical knowledge in literature, which urges the development of text mining approaches to facilitate the process by automatically extracting the Gene Ontology annotation from literature. The task is usually cast as a text classification problem, and contemporary methods are confronted with unbalanced training data and the difficulties associated with multi-label classification. Results In this research, we investigated the methods of enhancing automatic multi-label classification of biomedical literature by utilizing the structure of the Gene Ontology graph. We have studied three graph-based multi-label classification algorithms, including a novel stochastic algorithm and two top-down hierarchical classification methods for multi-label literature classification. We systematically evaluated and compared these graph-based classification algorithms to a conventional flat multi-label algorithm. The results indicate that, through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods can significantly improve predictions of the Gene Ontology terms implied by the analyzed text. Furthermore, the graph-based multi-label classifiers are capable of suggesting Gene Ontology annotations (to curators that are closely related to the true annotations even if they fail to predict the true ones directly. A software package implementing the studied algorithms is available for the research community. Conclusion Through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods have better potential than the conventional flat multi-label classification approach to facilitate

  8. Using the gene ontology to scan multilevel gene sets for associations in genome wide association studies.

    Science.gov (United States)

    Schaid, Daniel J; Sinnwell, Jason P; Jenkins, Gregory D; McDonnell, Shannon K; Ingle, James N; Kubo, Michiaki; Goss, Paul E; Costantino, Joseph P; Wickerham, D Lawrence; Weinshilboum, Richard M

    2012-01-01

    Gene-set analyses have been widely used in gene expression studies, and some of the developed methods have been extended to genome wide association studies (GWAS). Yet, complications due to linkage disequilibrium (LD) among single nucleotide polymorphisms (SNPs), and variable numbers of SNPs per gene and genes per gene-set, have plagued current approaches, often leading to ad hoc "fixes." To overcome some of the current limitations, we developed a general approach to scan GWAS SNP data for both gene-level and gene-set analyses, building on score statistics for generalized linear models, and taking advantage of the directed acyclic graph structure of the gene ontology when creating gene-sets. However, other types of gene-set structures can be used, such as the popular Kyoto Encyclopedia of Genes and Genomes (KEGG). Our approach combines SNPs into genes, and genes into gene-sets, but assures that positive and negative effects of genes on a trait do not cancel. To control for multiple testing of many gene-sets, we use an efficient computational strategy that accounts for LD and provides accurate step-down adjusted P-values for each gene-set. Application of our methods to two different GWAS provide guidance on the potential strengths and weaknesses of our proposed gene-set analyses. © 2011 Wiley Periodicals, Inc.

  9. Protein-Protein Interaction Network and Gene Ontology

    Science.gov (United States)

    Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah

    Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.

  10. Gene Ontology and KEGG Enrichment Analyses of Genes Related to Age-Related Macular Degeneration

    Directory of Open Access Journals (Sweden)

    Jian Zhang

    2014-01-01

    Full Text Available Identifying disease genes is one of the most important topics in biomedicine and may facilitate studies on the mechanisms underlying disease. Age-related macular degeneration (AMD is a serious eye disease; it typically affects older adults and results in a loss of vision due to retina damage. In this study, we attempt to develop an effective method for distinguishing AMD-related genes. Gene ontology and KEGG enrichment analyses of known AMD-related genes were performed, and a classification system was established. In detail, each gene was encoded into a vector by extracting enrichment scores of the gene set, including it and its direct neighbors in STRING, and gene ontology terms or KEGG pathways. Then certain feature-selection methods, including minimum redundancy maximum relevance and incremental feature selection, were adopted to extract key features for the classification system. As a result, 720 GO terms and 11 KEGG pathways were deemed the most important factors for predicting AMD-related genes.

  11. Automatic annotation of protein motif function with Gene Ontology terms

    Directory of Open Access Journals (Sweden)

    Gopalakrishnan Vanathi

    2004-09-01

    Full Text Available Abstract Background Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern searching algorithms and programs exist foridentifying candidate protein motifs at the whole genome level. However, amuch needed and importanttask is to determine the functions of the newly identified protein motifs. The Gene Ontology (GO project is an endeavor to annotate the function of genes or protein sequences with terms from a dynamic, controlled vocabulary and these annotations serve well as a knowledge base. Results This paperpresents methods to mine the GO knowledge base and use the association between the GO terms assigned to a sequence and the motifs matched by the same sequence as evidence for predicting the functions of novel protein motifs automatically. The task of assigning GO terms to protein motifsis viewed as both a binary classification and information retrieval problem, where PROSITE motifs are used as samples for mode training and functional prediction. The mutual information of a motif and aGO term association isfound to be a very useful feature. We take advantageof the known motifs to train a logistic regression classifier, which allows us to combine mutual information with other frequency-based features and obtain a probability of correctassociation. The trained logistic regression model has intuitively meaningful and logically plausible parameter values, and performs very well empirically according to our evaluation criteria. Conclusions In this research, different methods for automatic annotation of protein motifs have been investigated. Empirical result demonstrated that the methods have a great potential for detecting and augmenting information about thefunctions of newly discovered candidate protein motifs.

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

    Science.gov (United States)

    Li, Yanpeng; Yu, Hong

    2014-01-01

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

  13. Length bias correction in gene ontology enrichment analysis using logistic regression.

    Science.gov (United States)

    Mi, Gu; Di, Yanming; Emerson, Sarah; Cumbie, Jason S; Chang, Jeff H

    2012-01-01

    When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible.

  14. Diet, genes, and microbes: complexities of colon cancer prevention.

    Science.gov (United States)

    Birt, Diane F; Phillips, Gregory J

    2014-01-01

    Colorectal cancer is one of the leading causes of cancer-related deaths in the United States, and generally, as countries climb the economic ladder, their rates of colon cancer increase. Colon cancer was an early disease where key genetic mutations were identified as important in disease progression, and there is considerable interest in determining whether specific mutations sensitize the colon to cancer prevention strategies. Epidemiological studies have revealed that fiber- and vegetable-rich diets and physical activity are associated with reduced rates of colon cancer, while consumption of red and processed meat, or alcoholic beverages, and overconsumption as reflected in obesity are associated with increased rates. Animal studies have probed these effects and suggested directions for further refinement of diet in colon cancer prevention. Recently a central role for the microorganisms in the gastrointestinal tract in colon cancer development is being probed, and it is hypothesized that the microbes may integrate diet and host genetics in the etiology of the disease. This review provides background on dietary, genetic, and microbial impacts on colon cancer and describes an ongoing project using rodent models to assess the ability of digestion-resistant starch in the integration of these factors with the goal of furthering colon cancer prevention.

  15. Of genes and microbes: solving the intricacies in host genomes.

    Science.gov (United States)

    Wang, Jun; Chen, Liang; Zhao, Na; Xu, Xizhan; Xu, Yakun; Zhu, Baoli

    2018-05-01

    Microbiome research is a quickly developing field in biomedical research, and we have witnessed its potential in understanding the physiology, metabolism and immunology, its critical role in understanding the health and disease of the host, and its vast capacity in disease prediction, intervention and treatment. However, many of the fundamental questions still need to be addressed, including the shaping forces of microbial diversity between individuals and across time. Microbiome research falls into the classical nature vs. nurture scenario, such that host genetics shape part of the microbiome, while environmental influences change the original course of microbiome development. In this review, we focus on the nature, i.e., the genetic part of the equation, and summarize the recent efforts in understanding which parts of the genome, especially the human and mouse genome, play important roles in determining the composition and functions of microbial communities, primarily in the gut but also on the skin. We aim to present an overview of different approaches in studying the intricate relationships between host genetic variations and microbes, its underlying philosophy and methodology, and we aim to highlight a few key discoveries along this exploration, as well as current pitfalls. More evidence and results will surely appear in upcoming studies, and the accumulating knowledge will lead to a deeper understanding of what we could finally term a "hologenome", that is, the organized, closely interacting genome of the host and the microbiome.

  16. Aspergillus flavus Blast2GO gene ontology database: elevated growth temperature alters amino acid metabolism

    Science.gov (United States)

    The availability of a representative gene ontology (GO) database is a prerequisite for a successful functional genomics study. Using online Blast2GO resources we constructed a GO database of Aspergillus flavus. Of the predicted total 13,485 A. flavus genes 8,987 were annotated with GO terms. The mea...

  17. 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.

  18. Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

  19. A new measure for functional similarity of gene products based on Gene Ontology

    Directory of Open Access Journals (Sweden)

    Lengauer Thomas

    2006-06-01

    Full Text Available Abstract Background Gene Ontology (GO is a standard vocabulary of functional terms and allows for coherent annotation of gene products. These annotations provide a basis for new methods that compare gene products regarding their molecular function and biological role. Results We present a new method for comparing sets of GO terms and for assessing the functional similarity of gene products. The method relies on two semantic similarity measures; simRel and funSim. One measure (simRel is applied in the comparison of the biological processes found in different groups of organisms. The other measure (funSim is used to find functionally related gene products within the same or between different genomes. Results indicate that the method, in addition to being in good agreement with established sequence similarity approaches, also provides a means for the identification of functionally related proteins independent of evolutionary relationships. The method is also applied to estimating functional similarity between all proteins in Saccharomyces cerevisiae and to visualizing the molecular function space of yeast in a map of the functional space. A similar approach is used to visualize the functional relationships between protein families. Conclusion The approach enables the comparison of the underlying molecular biology of different taxonomic groups and provides a new comparative genomics tool identifying functionally related gene products independent of homology. The proposed map of the functional space provides a new global view on the functional relationships between gene products or protein families.

  20. GO(vis), a gene ontology visualization tool based on multi-dimensional values.

    Science.gov (United States)

    Ning, Zi; Jiang, Zhenran

    2010-05-01

    Most of gene product similarity measurements concentrate on the information content of Gene Ontology (GO) terms or use a path-based similarity between GO terms, which may ignore other important information contained in the structure of the ontology. In our study, we integrate different GO similarity measure approaches to analyze the functional relationship of genes and gene products with a new triangle-based visualization tool called GO(Vis). The purpose of this tool is to demonstrate the effect of three important information factors when measuring the similarity between gene products. One advantage of this tool is that its important ratio can be adjusted to meet different measuring requirements according to the biological knowledge of each factor. The experimental results demonstrate that GO(Vis) can display diagrams of the functional relationship for gene products effectively.

  1. Prediction of highly expressed genes in microbes based on chromatin accessibility

    Directory of Open Access Journals (Sweden)

    Ussery David W

    2007-02-01

    Full Text Available Abstract Background It is well known that gene expression is dependent on chromatin structure in eukaryotes and it is likely that chromatin can play a role in bacterial gene expression as well. Here, we use a nucleosomal position preference measure of anisotropic DNA flexibility to predict highly expressed genes in microbial genomes. We compare these predictions with those based on codon adaptation index (CAI values, and also with experimental data for 6 different microbial genomes, with a particular interest in experimental data from Escherichia coli. Moreover, position preference is examined further in 328 sequenced microbial genomes. Results We find that absolute gene expression levels are correlated with the position preference in many microbial genomes. It is postulated that in these regions, the DNA may be more accessible to the transcriptional machinery. Moreover, ribosomal proteins and ribosomal RNA are encoded by DNA having significantly lower position preference values than other genes in fast-replicating microbes. Conclusion This insight into DNA structure-dependent gene expression in microbes may be exploited for predicting the expression of non-translated genes such as non-coding RNAs that may not be predicted by any of the conventional codon usage bias approaches.

  2. A multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors for functional gene analysis.

    Science.gov (United States)

    Weber, Kristoffer; Bartsch, Udo; Stocking, Carol; Fehse, Boris

    2008-04-01

    Functional gene analysis requires the possibility of overexpression, as well as downregulation of one, or ideally several, potentially interacting genes. Lentiviral vectors are well suited for this purpose as they ensure stable expression of complementary DNAs (cDNAs), as well as short-hairpin RNAs (shRNAs), and can efficiently transduce a wide spectrum of cell targets when packaged within the coat proteins of other viruses. Here we introduce a multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors designed according to the "building blocks" principle. Using a wide spectrum of different fluorescent markers, including drug-selectable enhanced green fluorescent protein (eGFP)- and dTomato-blasticidin-S resistance fusion proteins, LeGO vectors allow simultaneous analysis of multiple genes and shRNAs of interest within single, easily identifiable cells. Furthermore, each functional module is flanked by unique cloning sites, ensuring flexibility and individual optimization. The efficacy of these vectors for analyzing multiple genes in a single cell was demonstrated in several different cell types, including hematopoietic, endothelial, and neural stem and progenitor cells, as well as hepatocytes. LeGO vectors thus represent a valuable tool for investigating gene networks using conditional ectopic expression and knock-down approaches simultaneously.

  3. Approaching the axiomatic enrichment of the Gene Ontology from a lexical perspective.

    Science.gov (United States)

    Quesada-Martínez, Manuel; Mikroyannidi, Eleni; Fernández-Breis, Jesualdo Tomás; Stevens, Robert

    2015-09-01

    The main goal of this work is to measure how lexical regularities in biomedical ontology labels can be used for the automatic creation of formal relationships between classes, and to evaluate the results of applying our approach to the Gene Ontology (GO). In recent years, we have developed a method for the lexical analysis of regularities in biomedical ontology labels, and we showed that the labels can present a high degree of regularity. In this work, we extend our method with a cross-products extension (CPE) metric, which estimates the potential interest of a specific regularity for axiomatic enrichment in the lexical analysis, using information on exact matches in external ontologies. The GO consortium recently enriched the GO by using so-called cross-product extensions. Cross-products are generated by establishing axioms that relate a given GO class with classes from the GO or other biomedical ontologies. We apply our method to the GO and study how its lexical analysis can identify and reconstruct the cross-products that are defined by the GO consortium. The label of the classes of the GO are highly regular in lexical terms, and the exact matches with labels of external ontologies affect 80% of the GO classes. The CPE metric reveals that 31.48% of the classes that exhibit regularities have fragments that are classes into two external ontologies that are selected for our experiment, namely, the Cell Ontology and the Chemical Entities of Biological Interest ontology, and 18.90% of them are fully decomposable into smaller parts. Our results show that the CPE metric permits our method to detect GO cross-product extensions with a mean recall of 62% and a mean precision of 28%. The study is completed with an analysis of false positives to explain this precision value. We think that our results support the claim that our lexical approach can contribute to the axiomatic enrichment of biomedical ontologies and that it can provide new insights into the engineering of

  4. Muscle Research and Gene Ontology: New standards for improved data integration.

    Science.gov (United States)

    Feltrin, Erika; Campanaro, Stefano; Diehl, Alexander D; Ehler, Elisabeth; Faulkner, Georgine; Fordham, Jennifer; Gardin, Chiara; Harris, Midori; Hill, David; Knoell, Ralph; Laveder, Paolo; Mittempergher, Lorenza; Nori, Alessandra; Reggiani, Carlo; Sorrentino, Vincenzo; Volpe, Pompeo; Zara, Ivano; Valle, Giorgio; Deegan, Jennifer

    2009-01-29

    The Gene Ontology Project provides structured controlled vocabularies for molecular biology that can be used for the functional annotation of genes and gene products. In a collaboration between the Gene Ontology (GO) Consortium and the muscle biology community, we have made large-scale additions to the GO biological process and cellular component ontologies. The main focus of this ontology development work concerns skeletal muscle, with specific consideration given to the processes of muscle contraction, plasticity, development, and regeneration, and to the sarcomere and membrane-delimited compartments. Our aims were to update the existing structure to reflect current knowledge, and to resolve, in an accommodating manner, the ambiguity in the language used by the community. The updated muscle terminologies have been incorporated into the GO. There are now 159 new terms covering critical research areas, and 57 existing terms have been improved and reorganized to follow their usage in muscle literature. The revised GO structure should improve the interpretation of data from high-throughput (e.g. microarray and proteomic) experiments in the area of muscle science and muscle disease. We actively encourage community feedback on, and gene product annotation with these new terms. Please visit the Muscle Community Annotation Wiki http://wiki.geneontology.org/index.php/Muscle_Biology.

  5. Muscle Research and Gene Ontology: New standards for improved data integration

    Directory of Open Access Journals (Sweden)

    Nori Alessandra

    2009-01-01

    Full Text Available Abstract Background The Gene Ontology Project provides structured controlled vocabularies for molecular biology that can be used for the functional annotation of genes and gene products. In a collaboration between the Gene Ontology (GO Consortium and the muscle biology community, we have made large-scale additions to the GO biological process and cellular component ontologies. The main focus of this ontology development work concerns skeletal muscle, with specific consideration given to the processes of muscle contraction, plasticity, development, and regeneration, and to the sarcomere and membrane-delimited compartments. Our aims were to update the existing structure to reflect current knowledge, and to resolve, in an accommodating manner, the ambiguity in the language used by the community. Results The updated muscle terminologies have been incorporated into the GO. There are now 159 new terms covering critical research areas, and 57 existing terms have been improved and reorganized to follow their usage in muscle literature. Conclusion The revised GO structure should improve the interpretation of data from high-throughput (e.g. microarray and proteomic experiments in the area of muscle science and muscle disease. We actively encourage community feedback on, and gene product annotation with these new terms. Please visit the Muscle Community Annotation Wiki http://wiki.geneontology.org/index.php/Muscle_Biology.

  6. Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; He, Yongqun

    2017-03-14

    Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of

  7. The mammalian adult neurogenesis gene ontology (MANGO provides a structural framework for published information on genes regulating adult hippocampal neurogenesis.

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    Rupert W Overall

    Full Text Available BACKGROUND: Adult hippocampal neurogenesis is not a single phenotype, but consists of a number of sub-processes, each of which is under complex genetic control. Interpretation of gene expression studies using existing resources often does not lead to results that address the interrelatedness of these processes. Formal structure, such as provided by ontologies, is essential in any field for comprehensive interpretation of existing knowledge but, until now, such a structure has been lacking for adult neurogenesis. METHODOLOGY/PRINCIPAL FINDINGS: We have created a resource with three components 1. A structured ontology describing the key stages in the development of adult hippocampal neural stem cells into functional granule cell neurons. 2. A comprehensive survey of the literature to annotate the results of all published reports on gene function in adult hippocampal neurogenesis (257 manuscripts covering 228 genes to the appropriate terms in our ontology. 3. An easy-to-use searchable interface to the resulting database made freely available online. The manuscript presents an overview of the database highlighting global trends such as the current bias towards research on early proliferative stages, and an example gene set enrichment analysis. A limitation of the resource is the current scope of the literature which, however, is growing by around 100 publications per year. With the ontology and database in place, new findings can be rapidly annotated and regular updates of the database will be made publicly available. CONCLUSIONS/SIGNIFICANCE: The resource we present allows relevant interpretation of gene expression screens in terms of defined stages of postnatal neuronal development. Annotation of genes by hand from the adult neurogenesis literature ensures the data are directly applicable to the system under study. We believe this approach could also serve as an example to other fields in a 'bottom-up' community effort complementing the already

  8. Systematically characterizing and prioritizing chemosensitivity related gene based on Gene Ontology and protein interaction network

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    Chen Xin

    2012-10-01

    Full Text Available Abstract Background The identification of genes that predict in vitro cellular chemosensitivity of cancer cells is of great importance. Chemosensitivity related genes (CRGs have been widely utilized to guide clinical and cancer chemotherapy decisions. In addition, CRGs potentially share functional characteristics and network features in protein interaction networks (PPIN. Methods In this study, we proposed a method to identify CRGs based on Gene Ontology (GO and PPIN. Firstly, we documented 150 pairs of drug-CCRG (curated chemosensitivity related gene from 492 published papers. Secondly, we characterized CCRGs from the perspective of GO and PPIN. Thirdly, we prioritized CRGs based on CCRGs’ GO and network characteristics. Lastly, we evaluated the performance of the proposed method. Results We found that CCRG enriched GO terms were most often related to chemosensitivity and exhibited higher similarity scores compared to randomly selected genes. Moreover, CCRGs played key roles in maintaining the connectivity and controlling the information flow of PPINs. We then prioritized CRGs using CCRG enriched GO terms and CCRG network characteristics in order to obtain a database of predicted drug-CRGs that included 53 CRGs, 32 of which have been reported to affect susceptibility to drugs. Our proposed method identifies a greater number of drug-CCRGs, and drug-CCRGs are much more significantly enriched in predicted drug-CRGs, compared to a method based on the correlation of gene expression and drug activity. The mean area under ROC curve (AUC for our method is 65.2%, whereas that for the traditional method is 55.2%. Conclusions Our method not only identifies CRGs with expression patterns strongly correlated with drug activity, but also identifies CRGs in which expression is weakly correlated with drug activity. This study provides the framework for the identification of signatures that predict in vitro cellular chemosensitivity and offers a valuable

  9. GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology

    OpenAIRE

    Caniza, Horacio; Romero, Alfonso E.; Heron, Samuel; Yang, Haixuan; Devoto, Alessandra; Frasca, Marco; Mesiti, Marco; Valentini, Giorgio; Paccanaro, Alberto

    2014-01-01

    Summary: We present GOssTo, the Gene Ontology semantic similarity Tool, a user-friendly software system for calculating semantic similarities between gene products according to the Gene Ontology. GOssTo is bundled with six semantic similarity measures, including both term- and graph-based measures, and has extension capabilities to allow the user to add new similarities. Importantly, for any measure, GOssTo can also calculate the Random Walk Contribution that has been shown to greatly improve...

  10. Gene Ontology Terms and Automated Annotation for Energy-Related Microbial Genomes

    Energy Technology Data Exchange (ETDEWEB)

    Mukhopadhyay, Biswarup [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Tyler, Brett M. [Oregon State Univ., Corvallis, OR (United States); Setubal, Joao [Univ. of Sao Paulo (Brazil); Murali, T. M. [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

    2017-11-03

    Gene Ontology (GO) is one of the more widely used functional ontologies for describing gene functions at various levels. The project developed 660 GO terms for describing energy-related microbial processes and filled the known gaps in this area of the GO system, and then used these terms to describe functions of 179 genes to showcase the utilities of the new resources. It hosted a series of workshops and made presentations at key meetings to inform and train scientific community members on these terms and to receive inputs from them for the GO term generation efforts. The project has developed a website for storing and displaying the resources (http://www.mengo.biochem.vt.edu/). The outcome of the project was further disseminated through peer-reviewed publications and poster and seminar presentations.

  11. Metagenomic Profiling of Soil Microbes to Mine Salt Stress Tolerance Genes

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    Vasim Ahmed

    2018-02-01

    Full Text Available Osmotolerance is one of the critical factors for successful survival and colonization of microbes in saline environments. Nonetheless, information about these osmotolerance mechanisms is still inadequate. Exploration of the saline soil microbiome for its community structure and novel genetic elements is likely to provide information on the mechanisms involved in osmoadaptation. The present study explores the saline soil microbiome for its native structure and novel genetic elements involved in osmoadaptation. 16S rRNA gene sequence analysis has indicated the dominance of halophilic/halotolerant phylotypes affiliated to Proteobacteria, Actinobacteria, Gemmatimonadetes, Bacteroidetes, Firmicutes, and Acidobacteria. A functional metagenomics approach led to the identification of osmotolerant clones SSR1, SSR4, SSR6, SSR2 harboring BCAA_ABCtp, GSDH, STK_Pknb, and duf3445 genes. Furthermore, transposon mutagenesis, genetic, physiological and functional studies in close association has confirmed the role of these genes in osmotolerance. Enhancement in host osmotolerance possibly though the cytosolic accumulation of amino acids, reducing equivalents and osmolytes involving BCAA-ABCtp, GSDH, and STKc_PknB. Decoding of the genetic elements prevalent within these microbes can be exploited either as such for ameliorating soils or their genetically modified forms can assist crops to resist and survive in saline environment.

  12. Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

    Science.gov (United States)

    Zhang, Shu-Bo; Tang, Qiang-Rong

    2016-07-21

    Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Is the crowd better as an assistant or a replacement in ontology engineering? An exploration through the lens of the Gene Ontology.

    Science.gov (United States)

    Mortensen, Jonathan M; Telis, Natalie; Hughey, Jacob J; Fan-Minogue, Hua; Van Auken, Kimberly; Dumontier, Michel; Musen, Mark A

    2016-04-01

    Biomedical ontologies contain errors. Crowdsourcing, defined as taking a job traditionally performed by a designated agent and outsourcing it to an undefined large group of people, provides scalable access to humans. Therefore, the crowd has the potential to overcome the limited accuracy and scalability found in current ontology quality assurance approaches. Crowd-based methods have identified errors in SNOMED CT, a large, clinical ontology, with an accuracy similar to that of experts, suggesting that crowdsourcing is indeed a feasible approach for identifying ontology errors. This work uses that same crowd-based methodology, as well as a panel of experts, to verify a subset of the Gene Ontology (200 relationships). Experts identified 16 errors, generally in relationships referencing acids and metals. The crowd performed poorly in identifying those errors, with an area under the receiver operating characteristic curve ranging from 0.44 to 0.73, depending on the methods configuration. However, when the crowd verified what experts considered to be easy relationships with useful definitions, they performed reasonably well. Notably, there are significantly fewer Google search results for Gene Ontology concepts than SNOMED CT concepts. This disparity may account for the difference in performance - fewer search results indicate a more difficult task for the worker. The number of Internet search results could serve as a method to assess which tasks are appropriate for the crowd. These results suggest that the crowd fits better as an expert assistant, helping experts with their verification by completing the easy tasks and allowing experts to focus on the difficult tasks, rather than an expert replacement. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Humans as Superorganisms: How Microbes, Viruses, Imprinted Genes, and Other Selfish Entities Shape Our Behavior.

    Science.gov (United States)

    Kramer, Peter; Bressan, Paola

    2015-07-01

    Psychologists and psychiatrists tend to be little aware that (a) microbes in our brains and guts are capable of altering our behavior; (b) viral DNA that was incorporated into our DNA millions of years ago is implicated in mental disorders; (c) many of us carry the cells of another human in our brains; and (d) under the regulation of viruslike elements, the paternally inherited and maternally inherited copies of some genes compete for domination in the offspring, on whom they have opposite physical and behavioral effects. This article provides a broad overview, aimed at a wide readership, of the consequences of our coexistence with these selfish entities. The overarching message is that we are not unitary individuals but superorganisms, built out of both human and nonhuman elements; it is their interaction that determines who we are. © The Author(s) 2015.

  15. Zebrafish Expression Ontology of Gene Sets (ZEOGS): a tool to analyze enrichment of zebrafish anatomical terms in large gene sets.

    Science.gov (United States)

    Prykhozhij, Sergey V; Marsico, Annalisa; Meijsing, Sebastiaan H

    2013-09-01

    The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene expression

  16. Zebrafish Expression Ontology of Gene Sets (ZEOGS): A Tool to Analyze Enrichment of Zebrafish Anatomical Terms in Large Gene Sets

    Science.gov (United States)

    Marsico, Annalisa

    2013-01-01

    Abstract The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene

  17. GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data.

    Science.gov (United States)

    Rue-Albrecht, Kévin; McGettigan, Paul A; Hernández, Belinda; Nalpas, Nicolas C; Magee, David A; Parnell, Andrew C; Gordon, Stephen V; MacHugh, David E

    2016-03-11

    Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or prognostic biomarkers. While integration of differential expression statistics has been used to refine gene set enrichment analyses, such approaches are typically limited to single gene lists resulting from simple two-group comparisons or time-series analyses. In contrast, functional class scoring and machine learning approaches provide powerful alternative methods to leverage molecular measurements for pathway analyses, and to compare continuous and multi-level categorical factors. We introduce GOexpress, a software package for scoring and summarising the capacity of gene ontology features to simultaneously classify samples from multiple experimental groups. GOexpress integrates normalised gene expression data (e.g., from microarray and RNA-seq experiments) and phenotypic information of individual samples with gene ontology annotations to derive a ranking of genes and gene ontology terms using a supervised learning approach. The default random forest algorithm allows interactions between all experimental factors, and competitive scoring of expressed genes to evaluate their relative importance in classifying predefined groups of samples. GOexpress enables rapid identification and visualisation of ontology-related gene panels that robustly classify groups of samples and supports both categorical (e.g., infection status, treatment) and continuous (e.g., time-series, drug concentrations) experimental factors. The use of standard Bioconductor extension packages and publicly available gene ontology annotations facilitates straightforward integration of GOexpress within existing computational biology pipelines.

  18. Integration of the Gene Ontology into an object-oriented architecture

    Directory of Open Access Journals (Sweden)

    Zheng W Jim

    2005-05-01

    Full Text Available Abstract Background To standardize gene product descriptions, a formal vocabulary defined as the Gene Ontology (GO has been developed. GO terms have been categorized into biological processes, molecular functions, and cellular components. However, there is no single representation that integrates all the terms into one cohesive model. Furthermore, GO definitions have little information explaining the underlying architecture that forms these terms, such as the dynamic and static events occurring in a process. In contrast, object-oriented models have been developed to show dynamic and static events. A portion of the TGF-beta signaling pathway, which is involved in numerous cellular events including cancer, differentiation and development, was used to demonstrate the feasibility of integrating the Gene Ontology into an object-oriented model. Results Using object-oriented models we have captured the static and dynamic events that occur during a representative GO process, "transforming growth factor-beta (TGF-beta receptor complex assembly" (GO:0007181. Conclusion We demonstrate that the utility of GO terms can be enhanced by object-oriented technology, and that the GO terms can be integrated into an object-oriented model by serving as a basis for the generation of object functions and attributes.

  19. MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction

    Directory of Open Access Journals (Sweden)

    Kohlbacher Oliver

    2009-09-01

    Full Text Available Abstract Background Knowledge of subcellular localization of proteins is crucial to proteomics, drug target discovery and systems biology since localization and biological function are highly correlated. In recent years, numerous computational prediction methods have been developed. Nevertheless, there is still a need for prediction methods that show more robustness and higher accuracy. Results We extended our previous MultiLoc predictor by incorporating phylogenetic profiles and Gene Ontology terms. Two different datasets were used for training the system, resulting in two versions of this high-accuracy prediction method. One version is specialized for globular proteins and predicts up to five localizations, whereas a second version covers all eleven main eukaryotic subcellular localizations. In a benchmark study with five localizations, MultiLoc2 performs considerably better than other methods for animal and plant proteins and comparably for fungal proteins. Furthermore, MultiLoc2 performs clearly better when using a second dataset that extends the benchmark study to all eleven main eukaryotic subcellular localizations. Conclusion MultiLoc2 is an extensive high-performance subcellular protein localization prediction system. By incorporating phylogenetic profiles and Gene Ontology terms MultiLoc2 yields higher accuracies compared to its previous version. Moreover, it outperforms other prediction systems in two benchmarks studies. MultiLoc2 is available as user-friendly and free web-service, available at: http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc2.

  20. A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.

    Science.gov (United States)

    Mazandu, Gaston K; Chimusa, Emile R; Mbiyavanga, Mamana; Mulder, Nicola J

    2016-02-01

    Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly compute, manipulate and explore these measures, we introduce A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis). It is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures. A-DaGO-Fun has the advantage not only of handling datasets from the current high-throughput genome-wide applications, but also allowing users to choose the most relevant semantic similarity approach for their biological applications and to adapt a given module to their needs. A-DaGO-Fun is freely available to the research community at http://web.cbio.uct.ac.za/ITGOM/adagofun. It is implemented in Linux using Python under free software (GNU General Public Licence). gmazandu@cbio.uct.ac.za or Nicola.Mulder@uct.ac.za Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. GO-Bayes: Gene Ontology-based overrepresentation analysis using a Bayesian approach.

    Science.gov (United States)

    Zhang, Song; Cao, Jing; Kong, Y Megan; Scheuermann, Richard H

    2010-04-01

    A typical approach for the interpretation of high-throughput experiments, such as gene expression microarrays, is to produce groups of genes based on certain criteria (e.g. genes that are differentially expressed). To gain more mechanistic insights into the underlying biology, overrepresentation analysis (ORA) is often conducted to investigate whether gene sets associated with particular biological functions, for example, as represented by Gene Ontology (GO) annotations, are statistically overrepresented in the identified gene groups. However, the standard ORA, which is based on the hypergeometric test, analyzes each GO term in isolation and does not take into account the dependence structure of the GO-term hierarchy. We have developed a Bayesian approach (GO-Bayes) to measure overrepresentation of GO terms that incorporates the GO dependence structure by taking into account evidence not only from individual GO terms, but also from their related terms (i.e. parents, children, siblings, etc.). The Bayesian framework borrows information across related GO terms to strengthen the detection of overrepresentation signals. As a result, this method tends to identify sets of closely related GO terms rather than individual isolated GO terms. The advantage of the GO-Bayes approach is demonstrated with a simulation study and an application example.

  2. Ontology-based Brucella vaccine literature indexing and systematic analysis of gene-vaccine association network

    Science.gov (United States)

    2011-01-01

    Background Vaccine literature indexing is poorly performed in PubMed due to limited hierarchy of Medical Subject Headings (MeSH) annotation in the vaccine field. Vaccine Ontology (VO) is a community-based biomedical ontology that represents various vaccines and their relations. SciMiner is an in-house literature mining system that supports literature indexing and gene name tagging. We hypothesize that application of VO in SciMiner will aid vaccine literature indexing and mining of vaccine-gene interaction networks. As a test case, we have examined vaccines for Brucella, the causative agent of brucellosis in humans and animals. Results The VO-based SciMiner (VO-SciMiner) was developed to incorporate a total of 67 Brucella vaccine terms. A set of rules for term expansion of VO terms were learned from training data, consisting of 90 biomedical articles related to Brucella vaccine terms. VO-SciMiner demonstrated high recall (91%) and precision (99%) from testing a separate set of 100 manually selected biomedical articles. VO-SciMiner indexing exhibited superior performance in retrieving Brucella vaccine-related papers over that obtained with MeSH-based PubMed literature search. For example, a VO-SciMiner search of "live attenuated Brucella vaccine" returned 922 hits as of April 20, 2011, while a PubMed search of the same query resulted in only 74 hits. Using the abstracts of 14,947 Brucella-related papers, VO-SciMiner identified 140 Brucella genes associated with Brucella vaccines. These genes included known protective antigens, virulence factors, and genes closely related to Brucella vaccines. These VO-interacting Brucella genes were significantly over-represented in biological functional categories, including metabolite transport and metabolism, replication and repair, cell wall biogenesis, intracellular trafficking and secretion, posttranslational modification, and chaperones. Furthermore, a comprehensive interaction network of Brucella vaccines and genes were

  3. SoFoCles: feature filtering for microarray classification based on gene ontology.

    Science.gov (United States)

    Papachristoudis, Georgios; Diplaris, Sotiris; Mitkas, Pericles A

    2010-02-01

    Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classification problems with the use of external, well-defined knowledge retrieved from the Gene Ontology. The notion of semantic similarity is used to derive genes that are involved in the same biological path during the microarray experiment, by enriching a feature set that has been initially produced with legacy methods. Among its other functionalities, SoFoCles offers a large repository of semantic similarity methods that are used in order to derive feature sets and marker genes. The structure and functionality of the tool are discussed in detail, as well as its ability to improve classification accuracy. Through experimental evaluation, SoFoCles is shown to outperform other classification schemes in terms of classification accuracy in two real datasets using different semantic similarity computation approaches.

  4. Development of Ecogenomic Sensors for Remote Detection of Marine Microbes, Their Genes and Gene Products

    Science.gov (United States)

    Scholin, C.; Preston, C.; Harris, A.; Birch, J.; Marin, R.; Jensen, S.; Roman, B.; Everlove, C.; Makarewicz, A.; Riot, V.; Hadley, D.; Benett, W.; Dzenitis, J.

    2008-12-01

    An internet search using the phrase "ecogenomic sensor" will return numerous references that speak broadly to the idea of detecting molecular markers indicative of specific organisms, genes or other biomarkers within an environmental context. However, a strict and unified definition of "ecogenomic sensor" is lacking and the phrase may be used for laboratory-based tools and techniques as well as semi or fully autonomous systems that can be deployed outside of laboratory. We are exploring development of an ecogenomic sensor from the perspective of a field-portable device applied towards oceanographic research and water quality monitoring. The device is known as the Environmental Sample Processor, or ESP. The ESP employs wet chemistry molecular analytical techniques to autonomously assess the presence and abundance of specific organisms, their genes and/or metabolites in near real-time. Current detection chemistries rely on low- density DNA probe and protein arrays. This presentation will emphasize results from 2007-8 field trials when the ESP was moored in Monterey Bay, CA, as well as current engineering activities for improving analytical capacity of the instrument. Changes in microbial community structure at the rRNA level were observed remotely in accordance with changing chemical and physical oceanographic conditions. Current developments include incorporation of a reusable solid phase extraction column for purifying nucleic acids and a 4-channel real-time PCR module. Users can configure this system to support a variety of PCR master mixes, primer/probe combinations and control templates. An update on progress towards fielding a PCR- enabled ESP will be given along with an outline of plans for its use in coastal and oligotrophic oceanic regimes.

  5. Gene dosage, expression, and ontology analysis identifies driver genes in the carcinogenesis and chemoradioresistance of cervical cancer.

    Directory of Open Access Journals (Sweden)

    Malin Lando

    2009-11-01

    Full Text Available Integrative analysis of gene dosage, expression, and ontology (GO data was performed to discover driver genes in the carcinogenesis and chemoradioresistance of cervical cancers. Gene dosage and expression profiles of 102 locally advanced cervical cancers were generated by microarray techniques. Fifty-two of these patients were also analyzed with the Illumina expression method to confirm the gene expression results. An independent cohort of 41 patients was used for validation of gene expressions associated with clinical outcome. Statistical analysis identified 29 recurrent gains and losses and 3 losses (on 3p, 13q, 21q associated with poor outcome after chemoradiotherapy. The intratumor heterogeneity, assessed from the gene dosage profiles, was low for these alterations, showing that they had emerged prior to many other alterations and probably were early events in carcinogenesis. Integration of the alterations with gene expression and GO data identified genes that were regulated by the alterations and revealed five biological processes that were significantly overrepresented among the affected genes: apoptosis, metabolism, macromolecule localization, translation, and transcription. Four genes on 3p (RYBP, GBE1 and 13q (FAM48A, MED4 correlated with outcome at both the gene dosage and expression level and were satisfactorily validated in the independent cohort. These integrated analyses yielded 57 candidate drivers of 24 genetic events, including novel loci responsible for chemoradioresistance. Further mapping of the connections among genetic events, drivers, and biological processes suggested that each individual event stimulates specific processes in carcinogenesis through the coordinated control of multiple genes. The present results may provide novel therapeutic opportunities of both early and advanced stage cervical cancers.

  6. Application of RNA-seq and Bioimaging Methods to Study Microbe-Microbe Interactions and Their Effects on Biofilm Formation and Gene Expression

    DEFF Research Database (Denmark)

    Amador Hierro, Cristina Isabel; Sternberg, Claus; Jelsbak, Lars

    2017-01-01

    Complex interactions between pathogenic bacteria, the microbiota, and the host can modify pathogen physiology and behavior. We describe two different experimental approaches to study microbe-microbe interactions in in vitro systems containing surface-associated microbial populations. One method i...

  7. Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application.

    Science.gov (United States)

    Roubelakis, Maria G; Zotos, Pantelis; Papachristoudis, Georgios; Michalopoulos, Ioannis; Pappa, Kalliopi I; Anagnou, Nicholas P; Kossida, Sophia

    2009-06-16

    microRNAs (miRNAs) are single-stranded RNA molecules of about 20-23 nucleotides length found in a wide variety of organisms. miRNAs regulate gene expression, by interacting with target mRNAs at specific sites in order to induce cleavage of the message or inhibit translation. Predicting or verifying mRNA targets of specific miRNAs is a difficult process of great importance. GOmir is a novel stand-alone application consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools as well as the experimentally supported targets from TarBase and also providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir represents a new tool incorporating two separate Java applications integrated into one stand-alone Java application. GOmir (by using up to five different databases) introduces miRNA predicted targets accompanied by (a) full gene description, (b) functional analysis and (c) detailed gene ontology clustering. Additionally, a reverse search initiated by a potential target can also be conducted. GOmir can freely be downloaded BRFAA.

  8. An ontology-driven semantic mashup of gene and biological pathway information: application to the domain of nicotine dependence.

    Science.gov (United States)

    Sahoo, Satya S; Bodenreider, Olivier; Rutter, Joni L; Skinner, Karen J; Sheth, Amit P

    2008-10-01

    This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. RESOURCE PAGE: http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/

  9. False positive reduction in protein-protein interaction predictions using gene ontology annotations

    Directory of Open Access Journals (Sweden)

    Lin Yen-Han

    2007-07-01

    Full Text Available Abstract Background Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated. Results Gene Ontology (GO annotations were used to reduce false positive protein-protein interactions (PPI pairs resulting from computational predictions. Using experimentally obtained PPI pairs as a training dataset, eight top-ranking keywords were extracted from GO molecular function annotations. The sensitivity of these keywords is 64.21% in the yeast experimental dataset and 80.83% in the worm experimental dataset. The specificities, a measure of recovery power, of these keywords applied to four predicted PPI datasets for each studied organisms, are 48.32% and 46.49% (by average of four datasets in yeast and worm, respectively. Based on eight top-ranking keywords and co-localization of interacting proteins a set of two knowledge rules were deduced and applied to remove false positive protein pairs. The 'strength', a measure of improvement provided by the rules was defined based on the signal-to-noise ratio and implemented to measure the applicability of knowledge rules applying to the predicted PPI datasets. Depending on the employed PPI-predicting methods, the strength varies between two and ten-fold of randomly removing protein pairs from the datasets. Conclusion Gene Ontology annotations along with the deduced knowledge rules could be implemented to partially

  10. Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.

    Science.gov (United States)

    Walls, Ramona L; Deck, John; Guralnick, Robert; Baskauf, Steve; Beaman, Reed; Blum, Stanley; Bowers, Shawn; Buttigieg, Pier Luigi; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Morrison, Norman; Ó Tuama, Éamonn; Schildhauer, Mark; Smith, Barry; Stucky, Brian J; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.

  11. Semantics in Support of Biodiversity Knowledge Discovery: An Introduction to the Biological Collections Ontology and Related Ontologies

    Science.gov (United States)

    Baskauf, Steve; Blum, Stanley; Bowers, Shawn; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Tuama, Éamonn Ó.; Schildhauer, Mark; Smith, Barry; Stucky, Brian J.; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers

  12. Gene ontology analysis of pairwise genetic associations in two genome-wide studies of sporadic ALS

    Directory of Open Access Journals (Sweden)

    Kim Nora

    2012-07-01

    Full Text Available Abstract Background It is increasingly clear that common human diseases have a complex genetic architecture characterized by both additive and nonadditive genetic effects. The goal of the present study was to determine whether patterns of both additive and nonadditive genetic associations aggregate in specific functional groups as defined by the Gene Ontology (GO. Results We first estimated all pairwise additive and nonadditive genetic effects using the multifactor dimensionality reduction (MDR method that makes few assumptions about the underlying genetic model. Statistical significance was evaluated using permutation testing in two genome-wide association studies of ALS. The detection data consisted of 276 subjects with ALS and 271 healthy controls while the replication data consisted of 221 subjects with ALS and 211 healthy controls. Both studies included genotypes from approximately 550,000 single-nucleotide polymorphisms (SNPs. Each SNP was mapped to a gene if it was within 500 kb of the start or end. Each SNP was assigned a p-value based on its strongest joint effect with the other SNPs. We then used the Exploratory Visual Analysis (EVA method and software to assign a p-value to each gene based on the overabundance of significant SNPs at the α = 0.05 level in the gene. We also used EVA to assign p-values to each GO group based on the overabundance of significant genes at the α = 0.05 level. A GO category was determined to replicate if that category was significant at the α = 0.05 level in both studies. We found two GO categories that replicated in both studies. The first, ‘Regulation of Cellular Component Organization and Biogenesis’, a GO Biological Process, had p-values of 0.010 and 0.014 in the detection and replication studies, respectively. The second, ‘Actin Cytoskeleton’, a GO Cellular Component, had p-values of 0.040 and 0.046 in the detection and replication studies, respectively. Conclusions Pathway

  13. Mining and gene ontology based annotation of SSR markers from expressed sequence tags of Humulus lupulus

    Science.gov (United States)

    Singh, Swati; Gupta, Sanchita; Mani, Ashutosh; Chaturvedi, Anoop

    2012-01-01

    Humulus lupulus is commonly known as hops, a member of the family moraceae. Currently many projects are underway leading to the accumulation of voluminous genomic and expressed sequence tag sequences in public databases. The genetically characterized domains in these databases are limited due to non-availability of reliable molecular markers. The large data of EST sequences are available in hops. The simple sequence repeat markers extracted from EST data are used as molecular markers for genetic characterization, in the present study. 25,495 EST sequences were examined and assembled to get full-length sequences. Maximum frequency distribution was shown by mononucleotide SSR motifs i.e. 60.44% in contig and 62.16% in singleton where as minimum frequency are observed for hexanucleotide SSR in contig (0.09%) and pentanucleotide SSR in singletons (0.12%). Maximum trinucleotide motifs code for Glutamic acid (GAA) while AT/TA were the most frequent repeat of dinucleotide SSRs. Flanking primer pairs were designed in-silico for the SSR containing sequences. Functional categorization of SSRs containing sequences was done through gene ontology terms like biological process, cellular component and molecular function. PMID:22368382

  14. Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

    Directory of Open Access Journals (Sweden)

    Lei Yang

    2014-01-01

    Full Text Available Cliques (maximal complete subnets in protein-protein interaction (PPI network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.

  15. GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data

    Directory of Open Access Journals (Sweden)

    Domont Gilberto B

    2009-02-01

    Full Text Available Abstract Background Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge. Results Here we present a new algorithm, termed GO Explorer (GOEx, that leverages the gene ontology (GO to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172. We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few. Conclusion GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at http://pcarvalho.com/patternlab.

  16. GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data.

    Science.gov (United States)

    Carvalho, Paulo C; Fischer, Juliana Sg; Chen, Emily I; Domont, Gilberto B; Carvalho, Maria Gc; Degrave, Wim M; Yates, John R; Barbosa, Valmir C

    2009-02-24

    Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge. Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few. GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at http://pcarvalho.com/patternlab.

  17. 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.

  18. Effect Of Spaceflight On Microbial Gene Expression And Virulence: Preliminary Results From Microbe Payload Flown On-Board STS-115

    Science.gov (United States)

    Wilson, J. W.; HonerzuBentrup, K,; Schurr, M. J.; Buchanan, K.; Morici, L.; Hammond, T.; Allen, P.; Baker, C.; Ott, C. M.; Nelman-Gonzalez M.; hide

    2007-01-01

    Human presence in space, whether permanent or temporary, is accompanied by the presence of microbes. However, the extent of microbial changes in response to spaceflight conditions and the corresponding changes to infectious disease risk is unclear. Previous studies have indicated that spaceflight weakens the immune system in humans and animals. In addition, preflight and in-flight monitoring of the International Space Station (ISS) and other spacecraft indicates the presence of opportunistic pathogens and the potential of obligate pathogens. Altered antibiotic resistance of microbes in flight has also been shown. As astronauts and cosmonauts live for longer periods in a closed environment, especially one using recycled water and air, there is an increased risk to crewmembers of infectious disease events occurring in-flight. Therefore, understanding how the space environment affects microorganisms and their disease potential is critically important for spaceflight missions and requires further study. The goal of this flight experiment, operationally called MICROBE, is to utilize three model microbial pathogens, Salmonella typhimurium, Pseudomonas aeruginosa, and Candida albicans to examine the global effects of spaceflight on microbial gene expression and virulence attributes. Specifically, the aims are (1) to perform microarray-mediated gene expression profiling of S. typhimurium, P. aeruginosa, and C. albicans, in response to spaceflight in comparison to ground controls and (2) to determine the effect of spaceflight on the virulence potential of these microorganisms immediately following their return from spaceflight using murine models. The model microorganisms were selected as they have been isolated from preflight or in-flight monitoring, represent different degrees of pathogenic behavior, are well characterized, and have sequenced genomes with available microarrays. In particular, extensive studies of S. typhimurium by the Principal Investigator, Dr. Nickerson

  19. Closing the loop: from paper to protein annotation using supervised Gene Ontology classification.

    Science.gov (United States)

    Gobeill, Julien; Pasche, Emilie; Vishnyakova, Dina; Ruch, Patrick

    2014-01-01

    Gene function curation of the literature with Gene Ontology (GO) concepts is one particularly time-consuming task in genomics, and the help from bioinformatics is highly requested to keep up with the flow of publications. In 2004, the first BioCreative challenge already designed a task of automatic GO concepts assignment from a full text. At this time, results were judged far from reaching the performances required by real curation workflows. In particular, supervised approaches produced the most disappointing results because of lack of training data. Ten years later, the available curation data have massively grown. In 2013, the BioCreative IV GO task revisited the automatic GO assignment task. For this issue, we investigated the power of our supervised classifier, GOCat. GOCat computes similarities between an input text and already curated instances contained in a knowledge base to infer GO concepts. The subtask A consisted in selecting GO evidence sentences for a relevant gene in a full text. For this, we designed a state-of-the-art supervised statistical approach, using a naïve Bayes classifier and the official training set, and obtained fair results. The subtask B consisted in predicting GO concepts from the previous output. For this, we applied GOCat and reached leading results, up to 65% for hierarchical recall in the top 20 outputted concepts. Contrary to previous competitions, machine learning has this time outperformed standard dictionary-based approaches. Thanks to BioCreative IV, we were able to design a complete workflow for curation: given a gene name and a full text, this system is able to select evidence sentences for curation and to deliver highly relevant GO concepts. Contrary to previous competitions, machine learning this time outperformed dictionary-based systems. Observed performances are sufficient for being used in a real semiautomatic curation workflow. GOCat is available at http://eagl.unige.ch/GOCat/. http://eagl.unige.ch/GOCat4FT/.

  20. PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements.

    Science.gov (United States)

    Mi, Huaiyu; Huang, Xiaosong; Muruganujan, Anushya; Tang, Haiming; Mills, Caitlin; Kang, Diane; Thomas, Paul D

    2017-01-04

    The PANTHER database (Protein ANalysis THrough Evolutionary Relationships, http://pantherdb.org) contains comprehensive information on the evolution and function of protein-coding genes from 104 completely sequenced genomes. PANTHER software tools allow users to classify new protein sequences, and to analyze gene lists obtained from large-scale genomics experiments. In the past year, major improvements include a large expansion of classification information available in PANTHER, as well as significant enhancements to the analysis tools. Protein subfamily functional classifications have more than doubled due to progress of the Gene Ontology Phylogenetic Annotation Project. For human genes (as well as a few other organisms), PANTHER now also supports enrichment analysis using pathway classifications from the Reactome resource. The gene list enrichment tools include a new 'hierarchical view' of results, enabling users to leverage the structure of the classifications/ontologies; the tools also allow users to upload genetic variant data directly, rather than requiring prior conversion to a gene list. The updated coding single-nucleotide polymorphisms (SNP) scoring tool uses an improved algorithm. The hidden Markov model (HMM) search tools now use HMMER3, dramatically reducing search times and improving accuracy of E-value statistics. Finally, the PANTHER Tree-Attribute Viewer has been implemented in JavaScript, with new views for exploring protein sequence evolution. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  1. Metagenome Analysis of Protein Domain Collocation within Cellulase Genes of Goat Rumen Microbes

    Directory of Open Access Journals (Sweden)

    SooYeon Lim

    2013-08-01

    Full Text Available In this study, protein domains with cellulase activity in goat rumen microbes were investigated using metagenomic and bioinformatic analyses. After the complete genome of goat rumen microbes was obtained using a shotgun sequencing method, 217,892,109 pair reads were filtered, including only those with 70% identity, 100-bp matches, and thresholds below E−10 using METAIDBA. These filtered contigs were assembled and annotated using blastN against the NCBI nucleotide database. As a result, a microbial community structure with 1431 species was analyzed, among which Prevotella ruminicola 23 bacteria and Butyrivibrio proteoclasticus B316 were the dominant groups. In parallel, 201 sequences related with cellulase activities (EC.3.2.1.4 were obtained through blast searches using the enzyme.dat file provided by the NCBI database. After translating the nucleotide sequence into a protein sequence using Interproscan, 28 protein domains with cellulase activity were identified using the HMMER package with threshold E values below 10−5. Cellulase activity protein domain profiling showed that the major protein domains such as lipase GDSL, cellulase, and Glyco hydro 10 were present in bacterial species with strong cellulase activities. Furthermore, correlation plots clearly displayed the strong positive correlation between some protein domain groups, which was indicative of microbial adaption in the goat rumen based on feeding habits. This is the first metagenomic analysis of cellulase activity protein domains using bioinformatics from the goat rumen.

  2. The Proteasix Ontology.

    Science.gov (United States)

    Arguello Casteleiro, Mercedes; Klein, Julie; Stevens, Robert

    2016-06-04

    The Proteasix Ontology (PxO) is an ontology that supports the Proteasix tool; an open-source peptide-centric tool that can be used to predict automatically and in a large-scale fashion in silico the proteases involved in the generation of proteolytic cleavage fragments (peptides) The PxO re-uses parts of the Protein Ontology, the three Gene Ontology sub-ontologies, the Chemical Entities of Biological Interest Ontology, the Sequence Ontology and bespoke extensions to the PxO in support of a series of roles: 1. To describe the known proteases and their target cleaveage sites. 2. To enable the description of proteolytic cleaveage fragments as the outputs of observed and predicted proteolysis. 3. To use knowledge about the function, species and cellular location of a protease and protein substrate to support the prioritisation of proteases in observed and predicted proteolysis. The PxO is designed to describe the biological underpinnings of the generation of peptides. The peptide-centric PxO seeks to support the Proteasix tool by separating domain knowledge from the operational knowledge used in protease prediction by Proteasix and to support the confirmation of its analyses and results. The Proteasix Ontology may be found at: http://bioportal.bioontology.org/ontologies/PXO . This ontology is free and open for use by everyone.

  3. Community structures and activity of denitrifying microbes in a forested catchment in central Japan: survey using nitrite reductase genes

    Science.gov (United States)

    Ohte, N.; Aoki, M.; Katsuyama, C.; Suwa, Y.; Tange, T.

    2012-12-01

    To elucidate the mechanisms of denitrification processes in the forested catchment, microbial ecological approaches have been applied in an experimental watershed that has previously investigated its hydrological processes. The study catchment is located in the Chiba prefecture in central Japan under the temperate Asian monsoon climate. Potential activities of denitrification of soil samples were measured by incubation experiments under anoxic condition associated with Na15NO3 addition. Existence and variety of microbes having nitrite reductase genes were investigated by PCR amplification, cloning and sequencings of nirK and nirS fragments after DNA extraction. Contrary to our early expectation that the potential denitrification activity was higher at deeper soil horizon with consistent groundwater residence than that in the surface soil, denitrification potential was higher in shallower soil horizons than deeper soils. This suggested that the deficiency of NO3- as a respiratory substrate for denitrifier occurred in deeper soils especially in the summer. However, high denitrification activity and presence of microbes having nirK and nirS in surface soils usually under aerobic condition was explainable by the fact that the majority of denitrifying bacteria have been recognized as a facultative anaerobic bacterium. This also suggests the possibility of that denitrification occurs even in the surface soils if the wet condition is provided by rainwater during and after a storm event. Community structures of microbes having nirK were different between near surface and deeper soil horizons, and ones having nirS was different between saturated zone (under groundwater table) and unsaturated soil horizons. These imply that microbial communities with nisK are sensitive to the concentration of soil organic matters and ones with nirS is sensitive to soil moisture contents.

  4. Gene-ontology enrichment analysis in two independent family-based samples highlights biologically plausible processes for autism spectrum disorders.

    LENUS (Irish Health Repository)

    Anney, Richard J L

    2012-02-01

    Recent genome-wide association studies (GWAS) have implicated a range of genes from discrete biological pathways in the aetiology of autism. However, despite the strong influence of genetic factors, association studies have yet to identify statistically robust, replicated major effect genes or SNPs. We apply the principle of the SNP ratio test methodology described by O\\'Dushlaine et al to over 2100 families from the Autism Genome Project (AGP). Using a two-stage design we examine association enrichment in 5955 unique gene-ontology classifications across four groupings based on two phenotypic and two ancestral classifications. Based on estimates from simulation we identify excess of association enrichment across all analyses. We observe enrichment in association for sets of genes involved in diverse biological processes, including pyruvate metabolism, transcription factor activation, cell-signalling and cell-cycle regulation. Both genes and processes that show enrichment have previously been examined in autistic disorders and offer biologically plausibility to these findings.

  5. PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

    Science.gov (United States)

    Hawkins, Troy; Chitale, Meghana; Luban, Stanislav; Kihara, Daisuke

    2009-02-15

    Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http

  6. DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures.

    Science.gov (United States)

    Mazandu, Gaston K; Mulder, Nicola J

    2013-09-25

    The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis.

  7. Prediction of highly expressed genes in microbes based on chromatin accessibility

    DEFF Research Database (Denmark)

    Willenbrock, Hanni; Ussery, David

    2007-01-01

    BACKGROUND: It is well known that gene expression is dependent on chromatin structure in eukaryotes and it is likely that chromatin can play a role in bacterial gene expression as well. Here, we use a nucleosomal position preference measure of anisotropic DNA flexibility to predict highly expressed...

  8. GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes.

    Science.gov (United States)

    Solovieva, Elena; Shikanai, Toshihide; Fujita, Noriaki; Narimatsu, Hisashi

    2018-04-18

    Inherited mutations in glyco-related genes can affect the biosynthesis and degradation of glycans and result in severe genetic diseases and disorders. The Glyco-Disease Genes Database (GDGDB), which provides information about these diseases and disorders as well as their causative genes, has been developed by the Research Center for Medical Glycoscience (RCMG) and released in April 2010. GDGDB currently provides information on about 80 genetic diseases and disorders caused by single-gene mutations in glyco-related genes. Many biomedical resources provide information about genetic disorders and genes involved in their pathogenesis, but resources focused on genetic disorders known to be related to glycan metabolism are lacking. With the aim of providing more comprehensive knowledge on genetic diseases and disorders of glycan biosynthesis and degradation, we enriched the content of the GDGDB database and improved the methods for data representation. We developed the Genetic Glyco-Diseases Ontology (GGDonto) and a RDF/SPARQL-based user interface using Semantic Web technologies. In particular, we represented the GGDonto content using Semantic Web languages, such as RDF, RDFS, SKOS, and OWL, and created an interactive user interface based on SPARQL queries. This user interface provides features to browse the hierarchy of the ontology, view detailed information on diseases and related genes, and find relevant background information. Moreover, it provides the ability to filter and search information by faceted and keyword searches. Focused on the molecular etiology, pathogenesis, and clinical manifestations of genetic diseases and disorders of glycan metabolism and developed as a knowledge-base for this scientific field, GGDonto provides comprehensive information on various topics, including links to aid the integration with other scientific resources. The availability and accessibility of this knowledge will help users better understand how genetic defects impact the

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

    Directory of Open Access Journals (Sweden)

    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

  10. GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology.

    Science.gov (United States)

    Caniza, Horacio; Romero, Alfonso E; Heron, Samuel; Yang, Haixuan; Devoto, Alessandra; Frasca, Marco; Mesiti, Marco; Valentini, Giorgio; Paccanaro, Alberto

    2014-08-01

    We present GOssTo, the Gene Ontology semantic similarity Tool, a user-friendly software system for calculating semantic similarities between gene products according to the Gene Ontology. GOssTo is bundled with six semantic similarity measures, including both term- and graph-based measures, and has extension capabilities to allow the user to add new similarities. Importantly, for any measure, GOssTo can also calculate the Random Walk Contribution that has been shown to greatly improve the accuracy of similarity measures. GOssTo is very fast, easy to use, and it allows the calculation of similarities on a genomic scale in a few minutes on a regular desktop machine. alberto@cs.rhul.ac.uk GOssTo is available both as a stand-alone application running on GNU/Linux, Windows and MacOS from www.paccanarolab.org/gossto and as a web application from www.paccanarolab.org/gosstoweb. The stand-alone application features a simple and concise command line interface for easy integration into high-throughput data processing pipelines. © The Author 2014. Published by Oxford University Press.

  11. Signalign: An Ontology of DNA as Signal for Comparative Gene Structure Prediction Using Information-Coding-and-Processing Techniques.

    Science.gov (United States)

    Yu, Ning; Guo, Xuan; Gu, Feng; Pan, Yi

    2016-03-01

    Conventional character-analysis-based techniques in genome analysis manifest three main shortcomings-inefficiency, inflexibility, and incompatibility. In our previous research, a general framework, called DNA As X was proposed for character-analysis-free techniques to overcome these shortcomings, where X is the intermediates, such as digit, code, signal, vector, tree, graph network, and so on. In this paper, we further implement an ontology of DNA As Signal, by designing a tool named Signalign for comparative gene structure analysis, in which DNA sequences are converted into signal series, processed by modified method of dynamic time warping and measured by signal-to-noise ratio (SNR). The ontology of DNA As Signal integrates the principles and concepts of other disciplines including information coding theory and signal processing into sequence analysis and processing. Comparing with conventional character-analysis-based methods, Signalign can not only have the equivalent or superior performance, but also enrich the tools and the knowledge library of computational biology by extending the domain from character/string to diverse areas. The evaluation results validate the success of the character-analysis-free technique for improved performances in comparative gene structure prediction.

  12. Expression profiling and gene ontology analysis in fathead minnow (Pimephales promelas) liver following exposure to pulp and paper mill effluents

    Energy Technology Data Exchange (ETDEWEB)

    Costigan, Shannon L.; Werner, Julieta; Ouellet, Jacob D.; Hill, Lauren G. [Department of Biology, Lakehead University, 955 Oliver Road, Ontario P7B 5E1, (Canada); Law, R. David, E-mail: dlaw@lakeheadu.ca [Department of Biology, Lakehead University, 955 Oliver Road, Ontario P7B 5E1, (Canada)

    2012-10-15

    Many studies link pulp and paper mill effluent (PPME) exposure to adverse effects in fish populations present in the mill receiving environments. These impacts are often characteristic of endocrine disruption and may include impaired reproduction, development and survival. While these physiological endpoints are well-characterized, the molecular mechanisms causing them are not yet understood. To investigate changes in gene transcription induced by exposure to a PPME at several stages of treatment, male and female fathead minnows (FHMs) were exposed for 6 days to 25% (v/v) secondary (biologically) treated kraft effluent (TK) or 100% (v/v) combined mill outfall (CMO) from a mill producing both kraft pulp and newsprint. The gene expression changes in the livers of these fish were analyzed using a 22 K oligonucleotide microarray. Exposure to TK or CMO resulted in significant changes in the expression levels of 105 and 238 targets in male FHMs and 296 and 133 targets in females, respectively. Targets were then functionally analyzed using gene ontology tools to identify the biological processes in fish hepatocytes that were affected by exposure to PPME after its secondary treatment. Proteolysis was affected in female FHMs exposed to both TK and CMO. In male FHMs, no processes were affected by TK exposure, while sterol, isoprenoid, steroid and cholesterol biosynthesis and electron transport were up-regulated by CMO exposure. The results presented in this study indicate that short-term exposure to PPMEs affects the expression of reproduction-related genes in the livers of both male and female FHMs, and that secondary treatment of PPMEs may not neutralize all of their metabolic effects in fish. Gene ontology analysis of microarray data may enable identification of biological processes altered by toxicant exposure and thus provide an additional tool for monitoring the impact of PPMEs on fish populations.

  13. Expression profiling and gene ontology analysis in fathead minnow (Pimephales promelas) liver following exposure to pulp and paper mill effluents

    International Nuclear Information System (INIS)

    Costigan, Shannon L.; Werner, Julieta; Ouellet, Jacob D.; Hill, Lauren G.; Law, R. David

    2012-01-01

    Many studies link pulp and paper mill effluent (PPME) exposure to adverse effects in fish populations present in the mill receiving environments. These impacts are often characteristic of endocrine disruption and may include impaired reproduction, development and survival. While these physiological endpoints are well-characterized, the molecular mechanisms causing them are not yet understood. To investigate changes in gene transcription induced by exposure to a PPME at several stages of treatment, male and female fathead minnows (FHMs) were exposed for 6 days to 25% (v/v) secondary (biologically) treated kraft effluent (TK) or 100% (v/v) combined mill outfall (CMO) from a mill producing both kraft pulp and newsprint. The gene expression changes in the livers of these fish were analyzed using a 22 K oligonucleotide microarray. Exposure to TK or CMO resulted in significant changes in the expression levels of 105 and 238 targets in male FHMs and 296 and 133 targets in females, respectively. Targets were then functionally analyzed using gene ontology tools to identify the biological processes in fish hepatocytes that were affected by exposure to PPME after its secondary treatment. Proteolysis was affected in female FHMs exposed to both TK and CMO. In male FHMs, no processes were affected by TK exposure, while sterol, isoprenoid, steroid and cholesterol biosynthesis and electron transport were up-regulated by CMO exposure. The results presented in this study indicate that short-term exposure to PPMEs affects the expression of reproduction-related genes in the livers of both male and female FHMs, and that secondary treatment of PPMEs may not neutralize all of their metabolic effects in fish. Gene ontology analysis of microarray data may enable identification of biological processes altered by toxicant exposure and thus provide an additional tool for monitoring the impact of PPMEs on fish populations.

  14. Quantum ontologies

    International Nuclear Information System (INIS)

    Stapp, H.P.

    1988-12-01

    Quantum ontologies are conceptions of the constitution of the universe that are compatible with quantum theory. The ontological orientation is contrasted to the pragmatic orientation of science, and reasons are given for considering quantum ontologies both within science, and in broader contexts. The principal quantum ontologies are described and evaluated. Invited paper at conference: Bell's Theorem, Quantum Theory, and Conceptions of the Universe, George Mason University, October 20-21, 1988. 16 refs

  15. Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology.

    Science.gov (United States)

    Masino, Aaron J; Dechene, Elizabeth T; Dulik, Matthew C; Wilkens, Alisha; Spinner, Nancy B; Krantz, Ian D; Pennington, Jeffrey W; Robinson, Peter N; White, Peter S

    2014-07-21

    Exome sequencing is a promising method for diagnosing patients with a complex phenotype. However, variant interpretation relative to patient phenotype can be challenging in some scenarios, particularly clinical assessment of rare complex phenotypes. Each patient's sequence reveals many possibly damaging variants that must be individually assessed to establish clear association with patient phenotype. To assist interpretation, we implemented an algorithm that ranks a given set of genes relative to patient phenotype. The algorithm orders genes by the semantic similarity computed between phenotypic descriptors associated with each gene and those describing the patient. Phenotypic descriptor terms are taken from the Human Phenotype Ontology (HPO) and semantic similarity is derived from each term's information content. Model validation was performed via simulation and with clinical data. We simulated 33 Mendelian diseases with 100 patients per disease. We modeled clinical conditions by adding noise and imprecision, i.e. phenotypic terms unrelated to the disease and terms less specific than the actual disease terms. We ranked the causative gene against all 2488 HPO annotated genes. The median causative gene rank was 1 for the optimal and noise cases, 12 for the imprecision case, and 60 for the imprecision with noise case. Additionally, we examined a clinical cohort of subjects with hearing impairment. The disease gene median rank was 22. However, when also considering the patient's exome data and filtering non-exomic and common variants, the median rank improved to 3. Semantic similarity can rank a causative gene highly within a gene list relative to patient phenotype characteristics, provided that imprecision is mitigated. The clinical case results suggest that phenotype rank combined with variant analysis provides significant improvement over the individual approaches. We expect that this combined prioritization approach may increase accuracy and decrease effort for

  16. Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.

    Directory of Open Access Journals (Sweden)

    Allan Peter Davis

    Full Text Available Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/ manually curates chemical-gene, chemical-disease, and gene-disease interactions from the scientific literature. The use of official gene symbols in CTD interactions enables this information to be combined with the Gene Ontology (GO file from NCBI Gene. By integrating these GO-gene annotations with CTD's gene-disease dataset, we produce 753,000 inferences between 15,700 GO terms and 4,200 diseases, providing opportunities to explore presumptive molecular underpinnings of diseases and identify biological similarities. Through a variety of applications, we demonstrate the utility of this novel resource. As a proof-of-concept, we first analyze known repositioned drugs (e.g., raloxifene and sildenafil and see that their target diseases have a greater degree of similarity when comparing GO terms vs. genes. Next, a computational analysis predicts seemingly non-intuitive diseases (e.g., stomach ulcers and atherosclerosis as being similar to bipolar disorder, and these are validated in the literature as reported co-diseases. Additionally, we leverage other CTD content to develop testable hypotheses about thalidomide-gene networks to treat seemingly disparate diseases. Finally, we illustrate how CTD tools can rank a series of drugs as potential candidates for repositioning against B-cell chronic lymphocytic leukemia and predict cisplatin and the small molecule inhibitor JQ1 as lead compounds. The CTD dataset is freely available for users to navigate pathologies within the context of extensive biological processes, molecular functions, and cellular components conferred by GO. This inference set should aid researchers, bioinformaticists, and

  17. DOSE RESPONSE FROM HIGH THROUGHPUT GENE EXPRESSION STUDIES AND THE INFLUENCE OF TIME AND CELL LINE ON INFERRED MODE OF ACTION BY ONTOLOGIC ENRICHMENT (SOT)

    Science.gov (United States)

    Gene expression with ontologic enrichment and connectivity mapping tools is widely used to infer modes of action (MOA) for therapeutic drugs. Despite progress in high-throughput (HT) genomic systems, strategies suitable to identify industrial chemical MOA are needed. The L1000 is...

  18. HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins.

    Science.gov (United States)

    Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

    2014-01-01

    Protein subcellular localization prediction, as an essential step to elucidate the functions in vivo of proteins and identify drugs targets, has been extensively studied in previous decades. Instead of only determining subcellular localization of single-label proteins, recent studies have focused on predicting both single- and multi-location proteins. Computational methods based on Gene Ontology (GO) have been demonstrated to be superior to methods based on other features. However, existing GO-based methods focus on the occurrences of GO terms and disregard their relationships. This paper proposes a multi-label subcellular-localization predictor, namely HybridGO-Loc, that leverages not only the GO term occurrences but also the inter-term relationships. This is achieved by hybridizing the GO frequencies of occurrences and the semantic similarity between GO terms. Given a protein, a set of GO terms are retrieved by searching against the gene ontology database, using the accession numbers of homologous proteins obtained via BLAST search as the keys. The frequency of GO occurrences and semantic similarity (SS) between GO terms are used to formulate frequency vectors and semantic similarity vectors, respectively, which are subsequently hybridized to construct fusion vectors. An adaptive-decision based multi-label support vector machine (SVM) classifier is proposed to classify the fusion vectors. Experimental results based on recent benchmark datasets and a new dataset containing novel proteins show that the proposed hybrid-feature predictor significantly outperforms predictors based on individual GO features as well as other state-of-the-art predictors. For readers' convenience, the HybridGO-Loc server, which is for predicting virus or plant proteins, is available online at http://bioinfo.eie.polyu.edu.hk/HybridGoServer/.

  19. Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms.

    Science.gov (United States)

    Falda, Marco; Toppo, Stefano; Pescarolo, Alessandro; Lavezzo, Enrico; Di Camillo, Barbara; Facchinetti, Andrea; Cilia, Elisa; Velasco, Riccardo; Fontana, Paolo

    2012-03-28

    Predicting protein function has become increasingly demanding in the era of next generation sequencing technology. The task to assign a curator-reviewed function to every single sequence is impracticable. Bioinformatics tools, easy to use and able to provide automatic and reliable annotations at a genomic scale, are necessary and urgent. In this scenario, the Gene Ontology has provided the means to standardize the annotation classification with a structured vocabulary which can be easily exploited by computational methods. Argot2 is a web-based function prediction tool able to annotate nucleic or protein sequences from small datasets up to entire genomes. It accepts as input a list of sequences in FASTA format, which are processed using BLAST and HMMER searches vs UniProKB and Pfam databases respectively; these sequences are then annotated with GO terms retrieved from the UniProtKB-GOA database and the terms are weighted using the e-values from BLAST and HMMER. The weighted GO terms are processed according to both their semantic similarity relations described by the Gene Ontology and their associated score. The algorithm is based on the original idea developed in a previous tool called Argot. The entire engine has been completely rewritten to improve both accuracy and computational efficiency, thus allowing for the annotation of complete genomes. The revised algorithm has been already employed and successfully tested during in-house genome projects of grape and apple, and has proven to have a high precision and recall in all our benchmark conditions. It has also been successfully compared with Blast2GO, one of the methods most commonly employed for sequence annotation. The server is freely accessible at http://www.medcomp.medicina.unipd.it/Argot2.

  20. On the Use of Gene Ontology Annotations to Assess Functional Similarity among Orthologs and Paralogs: A Short Report.

    Directory of Open Access Journals (Sweden)

    Paul D Thomas

    Full Text Available A recent paper (Nehrt et al., PLoS Comput. Biol. 7:e1002073, 2011 has proposed a metric for the "functional similarity" between two genes that uses only the Gene Ontology (GO annotations directly derived from published experimental results. Applying this metric, the authors concluded that paralogous genes within the mouse genome or the human genome are more functionally similar on average than orthologous genes between these genomes, an unexpected result with broad implications if true. We suggest, based on both theoretical and empirical considerations, that this proposed metric should not be interpreted as a functional similarity, and therefore cannot be used to support any conclusions about the "ortholog conjecture" (or, more properly, the "ortholog functional conservation hypothesis". First, we reexamine the case studies presented by Nehrt et al. as examples of orthologs with divergent functions, and come to a very different conclusion: they actually exemplify how GO annotations for orthologous genes provide complementary information about conserved biological functions. We then show that there is a global ascertainment bias in the experiment-based GO annotations for human and mouse genes: particular types of experiments tend to be performed in different model organisms. We conclude that the reported statistical differences in annotations between pairs of orthologous genes do not reflect differences in biological function, but rather complementarity in experimental approaches. Our results underscore two general considerations for researchers proposing novel types of analysis based on the GO: 1 that GO annotations are often incomplete, potentially in a biased manner, and subject to an "open world assumption" (absence of an annotation does not imply absence of a function, and 2 that conclusions drawn from a novel, large-scale GO analysis should whenever possible be supported by careful, in-depth examination of examples, to help ensure the

  1. Transcriptome and Gene Ontology (GO) Enrichment Analysis Reveals Genes Involved in Biotin Metabolism That Affect L-Lysine Production in Corynebacterium glutamicum.

    Science.gov (United States)

    Kim, Hong-Il; Kim, Jong-Hyeon; Park, Young-Jin

    2016-03-09

    Corynebacterium glutamicum is widely used for amino acid production. In the present study, 543 genes showed a significant change in their mRNA expression levels in L-lysine-producing C. glutamicum ATCC21300 than that in the wild-type C. glutamicum ATCC13032. Among these 543 differentially expressed genes (DEGs), 28 genes were up- or downregulated. In addition, 454 DEGs were functionally enriched and categorized based on BLAST sequence homologies and gene ontology (GO) annotations using the Blast2GO software. Interestingly, NCgl0071 (bioB, encoding biotin synthase) was expressed at levels ~20-fold higher in the L-lysine-producing ATCC21300 strain than that in the wild-type ATCC13032 strain. Five other genes involved in biotin metabolism or transport--NCgl2515 (bioA, encoding adenosylmethionine-8-amino-7-oxononanoate aminotransferase), NCgl2516 (bioD, encoding dithiobiotin synthetase), NCgl1883, NCgl1884, and NCgl1885--were also expressed at significantly higher levels in the L-lysine-producing ATCC21300 strain than that in the wild-type ATCC13032 strain, which we determined using both next-generation RNA sequencing and quantitative real-time PCR analysis. When we disrupted the bioB gene in C. glutamicum ATCC21300, L-lysine production decreased by approximately 76%, and the three genes involved in biotin transport (NCgl1883, NCgl1884, and NCgl1885) were significantly downregulated. These results will be helpful to improve our understanding of C. glutamicum for industrial amino acid production.

  2. Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

    Science.gov (United States)

    Ikram, Najmul; Qadir, Muhammad Abdul; Afzal, Muhammad Tanvir

    2018-01-01

    Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic similarity methods, and in protein function prediction. In this research, we investigate the relationship between the two similarity methods. The results suggest absence of a strong correlation between sequence and semantic similarities. There is a large number of proteins with low sequence similarity and high semantic similarity. We observe that Pearson's correlation coefficient is not sufficient to explain the nature of this relationship. Interestingly, the term semantic similarity values above 0 and below 1 do not seem to play a role in improving the correlation. That is, the correlation coefficient depends only on the number of common GO terms in proteins under comparison, and the semantic similarity measurement method does not influence it. Semantic similarity and sequence similarity have a distinct behavior. These findings are of significant effect for future works on protein comparison, and will help understand the semantic similarity between proteins in a better way.

  3. An ontology-driven semantic mash-up of gene and biological pathway information: Application to the domain of nicotine dependence

    Science.gov (United States)

    Sahoo, Satya S.; Bodenreider, Olivier; Rutter, Joni L.; Skinner, Karen J.; Sheth, Amit P.

    2008-01-01

    Objectives This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. Methods We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Results Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Conclusion Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. Resource page http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/ PMID:18395495

  4. OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data.

    Science.gov (United States)

    Huang, Jingshan; Gutierrez, Fernando; Strachan, Harrison J; Dou, Dejing; Huang, Weili; Smith, Barry; Blake, Judith A; Eilbeck, Karen; Natale, Darren A; Lin, Yu; Wu, Bin; Silva, Nisansa de; Wang, Xiaowei; Liu, Zixing; Borchert, Glen M; Tan, Ming; Ruttenberg, Alan

    2016-01-01

    As a special class of non-coding RNAs (ncRNAs), microRNAs (miRNAs) perform important roles in numerous biological and pathological processes. The realization of miRNA functions depends largely on how miRNAs regulate specific target genes. It is therefore critical to identify, analyze, and cross-reference miRNA-target interactions to better explore and delineate miRNA functions. Semantic technologies can help in this regard. We previously developed a miRNA domain-specific application ontology, Ontology for MIcroRNA Target (OMIT), whose goal was to serve as a foundation for semantic annotation, data integration, and semantic search in the miRNA field. In this paper we describe our continuing effort to develop the OMIT, and demonstrate its use within a semantic search system, OmniSearch, designed to facilitate knowledge capture of miRNA-target interaction data. Important changes in the current version OMIT are summarized as: (1) following a modularized ontology design (with 2559 terms imported from the NCRO ontology); (2) encoding all 1884 human miRNAs (vs. 300 in previous versions); and (3) setting up a GitHub project site along with an issue tracker for more effective community collaboration on the ontology development. The OMIT ontology is free and open to all users, accessible at: http://purl.obolibrary.org/obo/omit.owl. The OmniSearch system is also free and open to all users, accessible at: http://omnisearch.soc.southalabama.edu/index.php/Software.

  5. Ontological Planning

    Directory of Open Access Journals (Sweden)

    Ahmet Alkan

    2017-12-01

    • Is it possible to redefine ontology within the hierarchical structure of planning? We are going to seek answers to some of these questions within the limited scope of this paper and we are going to offer the rest for discussion by just asking them. In light of these assessments, drawing attention, based on ontological knowledge relying on the wholeness of universe, to the question, on macro level planning, of whether or not the ontological realities of man, energy and movements of thinking can provide macro data for planning on a universal level as important factors affecting mankind will be one of the limited objectives of the paper.

  6. 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.

  7. The Use of Gene Ontology Term and KEGG Pathway Enrichment for Analysis of Drug Half-Life.

    Directory of Open Access Journals (Sweden)

    Yu-Hang Zhang

    Full Text Available A drug's biological half-life is defined as the time required for the human body to metabolize or eliminate 50% of the initial drug dosage. Correctly measuring the half-life of a given drug is helpful for the safe and accurate usage of the drug. In this study, we investigated which gene ontology (GO terms and biological pathways were highly related to the determination of drug half-life. The investigated drugs, with known half-lives, were analyzed based on their enrichment scores for associated GO terms and KEGG pathways. These scores indicate which GO terms or KEGG pathways the drug targets. The feature selection method, minimum redundancy maximum relevance, was used to analyze these GO terms and KEGG pathways and to identify important GO terms and pathways, such as sodium-independent organic anion transmembrane transporter activity (GO:0015347, monoamine transmembrane transporter activity (GO:0008504, negative regulation of synaptic transmission (GO:0050805, neuroactive ligand-receptor interaction (hsa04080, serotonergic synapse (hsa04726, and linoleic acid metabolism (hsa00591, among others. This analysis confirmed our results and may show evidence for a new method in studying drug half-lives and building effective computational methods for the prediction of drug half-lives.

  8. Biotin in microbes, the genes involved in its biosynthesis, its biochemical role and perspectives for biotechnological production.

    Science.gov (United States)

    Streit, W R; Entcheva, P

    2003-03-01

    Biotin (vitamin H) is one of the most fascinating cofactors involved in central pathways in pro- and eukaryotic cell metabolism. Since its original discovery in 1901, research has led to the discovery of the complete biotin biosynthesis pathways in many different microbes and much work has been done on the highly intriguing and complex biochemistry of biotin biosynthesis. While humans and animals require several hundred micrograms of biotin per day, most microbes, plants and fungi appear to be able to synthesize the cofactor themselves. Biotin is added to many food, feed and cosmetic products, creating a world market of 10-30 t/year. However, the majority of the biotin sold is synthesized in a chemical process. Since the chemical synthesis is linked with a high environmental burden, much effort has been put into the development of biotin-overproducing microbes. A summary of biotin biosynthesis and its biological role is presented; and current strategies for the improvement of microbial biotin production using modern biotechnological techniques are discussed.

  9. Lentiviral gene ontology (LeGO) vectors equipped with novel drug-selectable fluorescent proteins: new building blocks for cell marking and multi-gene analysis.

    Science.gov (United States)

    Weber, K; Mock, U; Petrowitz, B; Bartsch, U; Fehse, B

    2010-04-01

    Vector-encoded fluorescent proteins (FPs) facilitate unambiguous identification or sorting of gene-modified cells by fluorescence-activated cell sorting (FACS). Exploiting this feature, we have recently developed lentiviral gene ontology (LeGO) vectors (www.LentiGO-Vectors.de) for multi-gene analysis in different target cells. In this study, we extend the LeGO principle by introducing 10 different drug-selectable FPs created by fusing one of the five selection marker (protecting against blasticidin, hygromycin, neomycin, puromycin and zeocin) and one of the five FP genes (Cerulean, eGFP, Venus, dTomato and mCherry). All tested fusion proteins allowed both fluorescence-mediated detection and drug-mediated selection of LeGO-transduced cells. Newly generated codon-optimized hygromycin- and neomycin-resistance genes showed improved expression as compared with their ancestors. New LeGO constructs were produced at titers >10(6) per ml (for non-concentrated supernatants). We show efficient combinatorial marking and selection of various cells, including mesenchymal stem cells, simultaneously transduced with different LeGO constructs. Inclusion of the cytomegalovirus early enhancer/chicken beta-actin promoter into LeGO vectors facilitated robust transgene expression in and selection of neural stem cells and their differentiated progeny. We suppose that the new drug-selectable markers combining advantages of FACS and drug selection are well suited for numerous applications and vector systems. Their inclusion into LeGO vectors opens new possibilities for (stem) cell tracking and functional multi-gene analysis.

  10. The Gene Ontology Differs in Bursa of Fabricius Between Two Breeds of Ducks Post Hatching by Enriching the Differentially Expressed Genes

    Directory of Open Access Journals (Sweden)

    H Liu

    Full Text Available ABSTRACT The bursa of Fabricius (BF is the central humoral immune organ unique to birds. The present study investigated the possible difference on a molecular level between two duck breeds. The digital gene expression profiling (DGE technology was used to enrich the differentially expressed genes (DEGs in BF between the Jianchang and Nonghua-P strains of ducks. DGE data identified 195 DEGs in the bursa. Gene Ontology (GO analysis suggested that DEGs were mainly enriched in the metabolic pathways and ribosome components. Pathways analysis identified the spliceosome, RNA transport, RNA degradation process, Jak-STAT signaling pathway, TNF signaling pathway and B cell receptor signaling pathway. The results indicated that the main difference in the BF between the two duck strains was in the capabilities of protein formation and B cell development. These data have revealed the main divergence in the BF on a molecular level between genetically different duck breeds and may help to perform molecular breeding programs in poultry in the future.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. [Using (1)H-nuclear magnetic resonance metabolomics and gene ontology to establish pathological staging model for esophageal cancer patients].

    Science.gov (United States)

    Chen, X; Wang, K; Chen, W; Jiang, H; Deng, P C; Li, Z J; Peng, J; Zhou, Z Y; Yang, H; Huang, G X; Zeng, J

    2016-07-01

    (ethanol amine, hydroxy-propionic acid, homocysteine and estriol) were eventually selected. gene ontology analysis showed that 54 enzymes and genes regulated the 4 key metabolic markers. The quantitative prediction model of esophageal cancer staging based on esophageal cancer NMR spectrum were established. Cross-validation results showed that the predicted effect was good (root mean square error=5.3, R(2)=0.47, P=0.036). The systems biology approaches based on metabolomics and enzyme-gene regulatory network analysis can be used to quantify the metabolic network disturbance of patients with advanced esophageal cancer, and to predict preoperative clinical staging of esophageal cancer patients by plasma NMR metabolomics.

  13. Delineation and interpretation of gene networks towards their effect in cellular physiology- a reverse engineering approach for the identification of critical molecular players, through the use of ontologies.

    Science.gov (United States)

    Moutselos, K; Maglogiannis, I; Chatziioannou, A

    2010-01-01

    Exploiting ontologies, provides clues regarding the involvement of certain molecular processes in the cellular phenotypic manifestation. However, identifying individual molecular actors (genes, proteins, etc.) for targeted biological validation in a generic, prioritized, fashion, based in objective measures of their effects in the cellular physiology, remains a challenge. In this work, a new meta-analysis algorithm is proposed for the holistic interpretation of the information captured in -omic experiments, that is showcased in a transcriptomic, dynamic, DNA microarray dataset, which examines the effect of mastic oil treatment in Lewis lung carcinoma cells. Through the use of the Gene Ontology this algorithm relates genes to specific cellular pathways and vice versa in order to further reverse engineer the critical role of specific genes, starting from the results of various statistical enrichment analyses. The algorithm is able to discriminate candidate hub-genes, implying critical biochemical cross-talk. Moreover, performance measures of the algorithm are derived, when evaluated with respect to the differential expression gene list of the dataset.

  14. SUGOI: automated ontology interchangeability

    CSIR Research Space (South Africa)

    Khan, ZC

    2015-04-01

    Full Text Available A foundational ontology can solve interoperability issues among the domain ontologies aligned to it. However, several foundational ontologies have been developed, hence such interoperability issues exist among domain ontologies. The novel SUGOI tool...

  15. Inferring ontology graph structures using OWL reasoning

    KAUST Repository

    Rodriguez-Garcia, Miguel Angel

    2018-01-05

    Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies\\' semantic content remains a challenge.We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies\\' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph .Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.

  16. Inferring ontology graph structures using OWL reasoning.

    Science.gov (United States)

    Rodríguez-García, Miguel Ángel; Hoehndorf, Robert

    2018-01-05

    Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies' semantic content remains a challenge. We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph . Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.

  17. Ontology evolution in physics

    OpenAIRE

    Chan, Michael

    2013-01-01

    With the advent of reasoning problems in dynamic environments, there is an increasing need for automated reasoning systems to automatically adapt to unexpected changes in representations. In particular, the automation of the evolution of their ontologies needs to be enhanced without substantially sacrificing expressivity in the underlying representation. Revision of beliefs is not enough, as adding to or removing from beliefs does not change the underlying formal language. Gene...

  18. Mutations in fetal genes involved in innate immunity and host defense against microbes increase risk of preterm premature rupture of membranes (PPROM).

    Science.gov (United States)

    Modi, Bhavi P; Teves, Maria E; Pearson, Laurel N; Parikh, Hardik I; Haymond-Thornburg, Hannah; Tucker, John L; Chaemsaithong, Piya; Gomez-Lopez, Nardhy; York, Timothy P; Romero, Roberto; Strauss, Jerome F

    2017-11-01

    Twin studies have revealed a significant contribution of the fetal genome to risk of preterm birth. Preterm premature rupture of membranes (PPROM) is the leading identifiable cause of preterm delivery. Infection and inflammation of the fetal membranes is commonly found associated with PPROM. We carried out whole exome sequencing (WES) of genomic DNA from neonates born of African-American mothers whose pregnancies were complicated by PPROM (76) or were normal term pregnancies (N = 43) to identify mutations in 35 candidate genes involved in innate immunity and host defenses against microbes. Targeted genotyping of mutations in the candidates discovered by WES was conducted on an additional 188 PPROM cases and 175 controls. We identified rare heterozygous nonsense and frameshift mutations in several of the candidate genes, including CARD6, CARD8, DEFB1, FUT2, MBL2, NLP10, NLRP12, and NOD2. We discovered that some mutations (CARD6, DEFB1, FUT2, MBL2, NLRP10, NOD2) were present only in PPROM cases. We conclude that rare damaging mutations in innate immunity and host defense genes, the majority being heterozygous, are more frequent in neonates born of pregnancies complicated by PPROM. These findings suggest that the risk of preterm birth in African-Americans may be conferred by mutations in multiple genes encoding proteins involved in dampening the innate immune response or protecting the host against microbial infection and microbial products. © 2017 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.

  19. Radiation induced pesticidal microbes

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Ki Yup; Lee, Y. K.; Kim, J. S.; Kim, J. K.; Lee, S. J.; Lim, D. S

    2001-01-01

    To isolate pesticidal microbes against plant pathogenic fungi, 4 strains of bacteria(K1. K3, K4, YS1) were isolated from mushroom compost and hot spring. K4, K1, K3, YS1 strain showed wide antifungal spectrum and high antifungal activities against 12 kinds of fungi. Specific proteins and the specific transcribed genes were found from the YS1 and its radiation-induced mutants. And knock-out mutants of antifungal activity were derived by transposon mutagenesis. From these knock-out mutants, the antifungal activity related genes and its modification by gamma-ray radiation are going to be studied. These results suggested that radiation could be an useful tool for the induction of functional mutants.

  20. Radiation induced pesticidal microbes

    International Nuclear Information System (INIS)

    Kim, Ki Yup; Lee, Y. K.; Kim, J. S.; Kim, J. K.; Lee, S. J.; Lim, D. S.

    2001-01-01

    To isolate pesticidal microbes against plant pathogenic fungi, 4 strains of bacteria(K1. K3, K4, YS1) were isolated from mushroom compost and hot spring. K4, K1, K3, YS1 strain showed wide antifungal spectrum and high antifungal activities against 12 kinds of fungi. Specific proteins and the specific transcribed genes were found from the YS1 and its radiation-induced mutants. And knock-out mutants of antifungal activity were derived by transposon mutagenesis. From these knock-out mutants, the antifungal activity related genes and its modification by gamma-ray radiation are going to be studied. These results suggested that radiation could be an useful tool for the induction of functional mutants

  1. Building ontologies with basic formal ontology

    CERN Document Server

    Arp, Robert; Spear, Andrew D.

    2015-01-01

    In the era of "big data," science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology that is of particular relevance to biomedicine, covering theoretical components of ontologies, best practices for ontology design, and examples of biomedical ontologies in use. After defining an ontology as a representation of the types of entities in a given domain, the book distinguishes between different kinds of ontologies and taxonomies, and shows how applied ontology draws on more traditional ideas from metaphysics. It presents the core features of the Basic Formal Ontology (BFO), now u...

  2. The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability.

    Science.gov (United States)

    Diehl, Alexander D; Meehan, Terrence F; Bradford, Yvonne M; Brush, Matthew H; Dahdul, Wasila M; Dougall, David S; He, Yongqun; Osumi-Sutherland, David; Ruttenberg, Alan; Sarntivijai, Sirarat; Van Slyke, Ceri E; Vasilevsky, Nicole A; Haendel, Melissa A; Blake, Judith A; Mungall, Christopher J

    2016-07-04

    The Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies. Recent work on the CL has focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class 'cell in vitro' have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning. The CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies-for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs. The ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the

  3. GOASVM: a subcellular location predictor by incorporating term-frequency gene ontology into the general form of Chou's pseudo-amino acid composition.

    Science.gov (United States)

    Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

    2013-04-21

    Prediction of protein subcellular localization is an important yet challenging problem. Recently, several computational methods based on Gene Ontology (GO) have been proposed to tackle this problem and have demonstrated superiority over methods based on other features. Existing GO-based methods, however, do not fully use the GO information. This paper proposes an efficient GO method called GOASVM that exploits the information from the GO term frequencies and distant homologs to represent a protein in the general form of Chou's pseudo-amino acid composition. The method first selects a subset of relevant GO terms to form a GO vector space. Then for each protein, the method uses the accession number (AC) of the protein or the ACs of its homologs to find the number of occurrences of the selected GO terms in the Gene Ontology annotation (GOA) database as a means to construct GO vectors for support vector machines (SVMs) classification. With the advantages of GO term frequencies and a new strategy to incorporate useful homologous information, GOASVM can achieve a prediction accuracy of 72.2% on a new independent test set comprising novel proteins that were added to Swiss-Prot six years later than the creation date of the training set. GOASVM and Supplementary materials are available online at http://bioinfo.eie.polyu.edu.hk/mGoaSvmServer/GOASVM.html. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Deep RNA-Seq profile reveals biodiversity, plant-microbe interactions and a large family of NBS-LRR resistance genes in walnut (Juglans regia) tissues.

    Science.gov (United States)

    Chakraborty, Sandeep; Britton, Monica; Martínez-García, P J; Dandekar, Abhaya M

    2016-03-01

    Deep RNA-Seq profiling, a revolutionary method used for quantifying transcriptional levels, often includes non-specific transcripts from other co-existing organisms in spite of stringent protocols. Using the recently published walnut genome sequence as a filter, we present a broad analysis of the RNA-Seq derived transcriptome profiles obtained from twenty different tissues to extract the biodiversity and possible plant-microbe interactions in the walnut ecosystem in California. Since the residual nature of the transcripts being analyzed does not provide sufficient information to identify the exact strain, inferences made are constrained to the genus level. The presence of the pathogenic oomycete Phytophthora was detected in the root through the presence of a glyceraldehyde-3-phosphate dehydrogenase. Cryptococcus, the causal agent of cryptococcosis, was found in the catkins and vegetative buds, corroborating previous work indicating that the plant surface supported the sexual cycle of this human pathogen. The RNA-Seq profile revealed several species of the endophytic nitrogen fixing Actinobacteria. Another bacterial species implicated in aerobic biodegradation of methyl tert-butyl ether (Methylibium petroleiphilum) is also found in the root. RNA encoding proteins from the pea aphid were found in the leaves and vegetative buds, while a serine protease from mosquito with significant homology to a female reproductive tract protease from Drosophila mojavensis in the vegetative bud suggests egg-laying activities. The comprehensive analysis of RNA-seq data present also unraveled detailed, tissue-specific information of ~400 transcripts encoded by the largest family of resistance (R) genes (NBS-LRR), which possibly rationalizes the resistance of the specific walnut plant to the pathogens detected. Thus, we elucidate the biodiversity and possible plant-microbe interactions in several walnut (Juglans regia) tissues in California using deep RNA-Seq profiling.

  5. Ontology authoring with Forza

    CSIR Research Space (South Africa)

    Keet, CM

    2014-11-01

    Full Text Available Generic, reusable ontology elements, such as a foundational ontology's categories and part-whole relations, are essential for good and interoperable knowledge representation. Ontology developers, which include domain experts and novices, face...

  6. Ontological Surprises

    DEFF Research Database (Denmark)

    Leahu, Lucian

    2016-01-01

    a hybrid approach where machine learning algorithms are used to identify objects as well as connections between them; finally, it argues for remaining open to ontological surprises in machine learning as they may enable the crafting of different relations with and through technologies.......This paper investigates how we might rethink design as the technological crafting of human-machine relations in the context of a machine learning technique called neural networks. It analyzes Google’s Inceptionism project, which uses neural networks for image recognition. The surprising output...

  7. Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data

    Directory of Open Access Journals (Sweden)

    Tintle Nathan L

    2012-08-01

    Full Text Available Abstract Background Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. Results We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Conclusions Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

  8. Anatomy Ontology Matching Using Markov Logic Networks

    Directory of Open Access Journals (Sweden)

    Chunhua Li

    2016-01-01

    Full Text Available The anatomy of model species is described in ontologies, which are used to standardize the annotations of experimental data, such as gene expression patterns. To compare such data between species, we need to establish relationships between ontologies describing different species. Ontology matching is a kind of solutions to find semantic correspondences between entities of different ontologies. Markov logic networks which unify probabilistic graphical model and first-order logic provide an excellent framework for ontology matching. We combine several different matching strategies through first-order logic formulas according to the structure of anatomy ontologies. Experiments on the adult mouse anatomy and the human anatomy have demonstrated the effectiveness of proposed approach in terms of the quality of result alignment.

  9. InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk

    OpenAIRE

    Cheng, Liang; Jiang, Yue; Ju, Hong; Sun, Jie; Peng, Jiajie; Zhou, Meng; Hu, Yang

    2018-01-01

    Background Since the establishment of the first biomedical ontology Gene Ontology (GO), the number of biomedical ontology has increased dramatically. Nowadays over 300 ontologies have been built including extensively used Disease Ontology (DO) and Human Phenotype Ontology (HPO). Because of the advantage of identifying novel relationships between terms, calculating similarity between ontology terms is one of the major tasks in this research area. Though similarities between terms within each o...

  10. Using Gene Ontology to describe the role of the neurexin-neuroligin-SHANK complex in human, mouse and rat and its relevance to autism.

    Science.gov (United States)

    Patel, Sejal; Roncaglia, Paola; Lovering, Ruth C

    2015-06-06

    People with an autistic spectrum disorder (ASD) display a variety of characteristic behavioral traits, including impaired social interaction, communication difficulties and repetitive behavior. This complex neurodevelopment disorder is known to be associated with a combination of genetic and environmental factors. Neurexins and neuroligins play a key role in synaptogenesis and neurexin-neuroligin adhesion is one of several processes that have been implicated in autism spectrum disorders. In this report we describe the manual annotation of a selection of gene products known to be associated with autism and/or the neurexin-neuroligin-SHANK complex and demonstrate how a focused annotation approach leads to the creation of more descriptive Gene Ontology (GO) terms, as well as an increase in both the number of gene product annotations and their granularity, thus improving the data available in the GO database. The manual annotations we describe will impact on the functional analysis of a variety of future autism-relevant datasets. Comprehensive gene annotation is an essential aspect of genomic and proteomic studies, as the quality of gene annotations incorporated into statistical analysis tools affects the effective interpretation of data obtained through genome wide association studies, next generation sequencing, proteomic and transcriptomic datasets.

  11. Didactical Ontologies

    Directory of Open Access Journals (Sweden)

    Steffen Mencke, Reiner Dumke

    2008-03-01

    Full Text Available Ontologies are a fundamental concept of theSemantic Web envisioned by Tim Berners-Lee [1]. Togetherwith explicit representation of the semantics of data formachine-accessibility such domain theories are the basis forintelligent next generation applications for the web andother areas of interest [2]. Their application for specialaspects within the domain of e-learning is often proposed tosupport the increasing complexity ([3], [4], [5], [6]. So theycan provide a better support for course generation orlearning scenario description [7]. By the modeling ofdidactics-related expertise and their provision for thecreators of courses many improvements like reuse, rapiddevelopment and of course increased learning performancebecome possible due to the separation from other aspects ofe-learning platforms as already proposed in [8].

  12. Gene expression profiling in susceptible interaction of grapevine with its fungal pathogen Eutypa lata: Extending MapMan ontology for grapevine

    Directory of Open Access Journals (Sweden)

    Usadel Björn

    2009-08-01

    Full Text Available Abstract Background Whole genome transcriptomics analysis is a very powerful approach because it gives an overview of the activity of genes in certain cells or tissue types. However, biological interpretation of such results can be rather tedious. MapMan is a software tool that displays large datasets (e.g. gene expression data onto diagrams of metabolic pathways or other processes and thus enables easier interpretation of results. The grapevine (Vitis vinifera genome sequence has recently become available bringing a new dimension into associated research. Two microarray platforms were designed based on the TIGR Gene Index database and used in several physiological studies. Results To enable easy and effective visualization of those and further experiments, annotation of Vitis vinifera Gene Index (VvGI version 5 to MapMan ontology was set up. Due to specificities of grape physiology, we have created new pictorial representations focusing on three selected pathways: carotenoid pathway, terpenoid pathway and phenylpropanoid pathway, the products of these pathways being important for wine aroma, flavour and colour, as well as plant defence against pathogens. This new tool was validated on Affymetrix microarrays data obtained during berry ripening and it allowed the discovery of new aspects in process regulation. We here also present results on transcriptional profiling of grape plantlets after exposal to the fungal pathogen Eutypa lata using Operon microarrays including visualization of results with MapMan. The data show that the genes induced in infected plants, encode pathogenesis related proteins and enzymes of the flavonoid metabolism, which are well known as being responsive to fungal infection. Conclusion The extension of MapMan ontology to grapevine together with the newly constructed pictorial representations for carotenoid, terpenoid and phenylpropanoid metabolism provide an alternative approach to the analysis of grapevine gene expression

  13. Markov Chain Ontology Analysis (MCOA).

    Science.gov (United States)

    Frost, H Robert; McCray, Alexa T

    2012-02-03

    Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data. In this paper, we describe a methodology called Markov Chain Ontology Analysis (MCOA) and illustrate its use through a MCOA-based enrichment analysis application based on a generative model of gene activation. MCOA models the classes in an ontology, the instances from an associated dataset and all directional inter-class, class-to-instance and inter-instance relationships as a single finite ergodic Markov chain. The adjusted transition probability matrix for this Markov chain enables the calculation of eigenvector values that quantify the importance of each ontology class relative to other classes and the associated data set members. On both controlled Gene Ontology (GO) data sets created with Escherichia coli, Drosophila melanogaster and Homo sapiens annotations and real gene expression data extracted from the Gene Expression Omnibus (GEO), the MCOA enrichment analysis approach provides the best performance of comparable state-of-the-art methods. A methodology based on Markov chain models and network analytic metrics can help detect the relevant signal within large, highly interdependent and noisy data sets and, for applications such as enrichment analysis, has been shown to generate superior performance on both real and simulated data relative to existing state-of-the-art approaches.

  14. Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features.

    Science.gov (United States)

    Zhou, Hang; Yang, Yang; Shen, Hong-Bin

    2017-03-15

    Protein subcellular localization prediction has been an important research topic in computational biology over the last decade. Various automatic methods have been proposed to predict locations for large scale protein datasets, where statistical machine learning algorithms are widely used for model construction. A key step in these predictors is encoding the amino acid sequences into feature vectors. Many studies have shown that features extracted from biological domains, such as gene ontology and functional domains, can be very useful for improving the prediction accuracy. However, domain knowledge usually results in redundant features and high-dimensional feature spaces, which may degenerate the performance of machine learning models. In this paper, we propose a new amino acid sequence-based human protein subcellular location prediction approach Hum-mPLoc 3.0, which covers 12 human subcellular localizations. The sequences are represented by multi-view complementary features, i.e. context vocabulary annotation-based gene ontology (GO) terms, peptide-based functional domains, and residue-based statistical features. To systematically reflect the structural hierarchy of the domain knowledge bases, we propose a novel feature representation protocol denoted as HCM (Hidden Correlation Modeling), which will create more compact and discriminative feature vectors by modeling the hidden correlations between annotation terms. Experimental results on four benchmark datasets show that HCM improves prediction accuracy by 5-11% and F 1 by 8-19% compared with conventional GO-based methods. A large-scale application of Hum-mPLoc 3.0 on the whole human proteome reveals proteins co-localization preferences in the cell. www.csbio.sjtu.edu.cn/bioinf/Hum-mPLoc3/. hbshen@sjtu.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

  15. Transcriptome Analysis of Porcine PBMCs Reveals the Immune Cascade Response and Gene Ontology Terms Related to Cell Death and Fibrosis in the Progression of Liver Failure

    Directory of Open Access Journals (Sweden)

    YiMin Zhang

    2018-01-01

    Full Text Available Background. The key gene sets involved in the progression of acute liver failure (ALF, which has a high mortality rate, remain unclear. This study aims to gain a deeper understanding of the transcriptional response of peripheral blood mononuclear cells (PBMCs following ALF. Methods. ALF was induced by D-galactosamine (D-gal in a porcine model. PBMCs were separated at time zero (baseline group, 36 h (failure group, and 60 h (dying group after D-gal injection. Transcriptional profiling was performed using RNA sequencing and analysed using DAVID bioinformatics resources. Results. Compared with the baseline group, 816 and 1,845 differentially expressed genes (DEGs were identified in the failure and dying groups, respectively. A total of five and two gene ontology (GO term clusters were enriched in 107 GO terms in the failure group and 154 GO terms in the dying group. These GO clusters were primarily immune-related, including genes regulating the inflammasome complex and toll-like receptor signalling pathways. Specifically, GO terms related to cell death, including apoptosis, pyroptosis, and autophagy, and those related to fibrosis, coagulation dysfunction, and hepatic encephalopathy were enriched. Seven Kyoto Encyclopedia of Genes and Genomes (KEGG pathways, cytokine-cytokine receptor interaction, hematopoietic cell lineage, lysosome, rheumatoid arthritis, malaria, and phagosome and pertussis pathways were mapped for DEGs in the failure group. All of these seven KEGG pathways were involved in the 19 KEGG pathways mapped in the dying group. Conclusion. We found that the dramatic PBMC transcriptome changes triggered by ALF progression was predominantly related to immune responses. The enriched GO terms related to cell death, fibrosis, and so on, as indicated by PBMC transcriptome analysis, seem to be useful in elucidating potential key gene sets in the progression of ALF. A better understanding of these gene sets might be of preventive or

  16. Oral microbe-host interactions: influence of β-glucans on gene expression of inflammatory cytokines and metabolome profile.

    Science.gov (United States)

    Silva, Viviam de Oliveira; Pereira, Luciano José; Murata, Ramiro Mendonça

    2017-03-07

    The aim of this study was to evaluate the effects of β-glucan on the expression of inflammatory mediators and metabolomic profile of oral cells [keratinocytes (OBA-9) and fibroblasts (HGF-1) in a dual-chamber model] infected by Aggregatibacter actinomycetemcomitans. The periodontopathogen was applied and allowed to cross the top layer of cells (OBA-9) to reach the bottom layer of cells (HGF-1) and induce the synthesis of immune factors and cytokines in the host cells. β-glucan (10 μg/mL or 20 μg/mL) were added, and the transcriptional factors and metabolites produced were quantified in the remaining cell layers and supernatant. The relative expression of interleukin (IL)-1-α and IL-18 genes in HGF-1 decreased with 10 μg/mL or 20 μg/mL of β-glucan, where as the expression of PTGS-2 decreased only with 10 μg/mL. The expression of IL-1-α increased with 20 μg/mL and that of IL-18 increased with 10 μg/mL in OBA-9; the expression of BCL 2, EP 300, and PTGS-2 decreased with the higher dose of β-glucan. The production of the metabolite 4-aminobutyric acid presented lower concentrations under 20 μg/mL, whereas the concentrations of 2-deoxytetronic acid NIST and oxalic acid decreased at both concentrations used. Acetophenone, benzoic acid, and pinitol presented reduced concentrations only when treated with 10 μg/mL of β-glucan. Treatment with β-glucans positively modulated the immune response and production of metabolites.

  17. Witnessing stressful events induces glutamatergic synapse pathway alterations and gene set enrichment of positive EPSP regulation within the VTA of adult mice: An ontology based approach

    Science.gov (United States)

    Brewer, Jacob S.

    It is well known that exposure to severe stress increases the risk for developing mood disorders. Currently, the neurobiological and genetic mechanisms underlying the functional effects of psychological stress are poorly understood. Presenting a major obstacle to the study of psychological stress is the inability of current animal models of stress to distinguish between physical and psychological stressors. A novel paradigm recently developed by Warren et al., is able to tease apart the effects of physical and psychological stress in adult mice by allowing these mice to "witness," the social defeat of another mouse thus removing confounding variables associated with physical stressors. Using this 'witness' model of stress and RNA-Seq technology, the current study aims to study the genetic effects of psychological stress. After, witnessing the social defeat of another mouse, VTA tissue was extracted, sequenced, and analyzed for differential expression. Since genes often work together in complex networks, a pathway and gene ontology (GO) analysis was performed using data from the differential expression analysis. The pathway and GO analyzes revealed a perturbation of the glutamatergic synapse pathway and an enrichment of positive excitatory post-synaptic potential regulation. This is consistent with the excitatory synapse theory of depression. Together these findings demonstrate a dysregulation of the mesolimbic reward pathway at the gene level as a result of psychological stress potentially contributing to depressive like behaviors.

  18. Comparing Relational and Ontological Triple Stores in Healthcare Domain

    Directory of Open Access Journals (Sweden)

    Ozgu Can

    2017-01-01

    Full Text Available Today’s technological improvements have made ubiquitous healthcare systems that converge into smart healthcare applications in order to solve patients’ problems, to communicate effectively with patients, and to improve healthcare service quality. The first step of building a smart healthcare information system is representing the healthcare data as connected, reachable, and sharable. In order to achieve this representation, ontologies are used to describe the healthcare data. Combining ontological healthcare data with the used and obtained data can be maintained by storing the entire health domain data inside big data stores that support both relational and graph-based ontological data. There are several big data stores and different types of big data sets in the healthcare domain. The goal of this paper is to determine the most applicable ontology data store for storing the big healthcare data. For this purpose, AllegroGraph and Oracle 12c data stores are compared based on their infrastructural capacity, loading time, and query response times. Hence, healthcare ontologies (GENE Ontology, Gene Expression Ontology (GEXO, Regulation of Transcription Ontology (RETO, Regulation of Gene Expression Ontology (REXO are used to measure the ontology loading time. Thereafter, various queries are constructed and executed for GENE ontology in order to measure the capacity and query response times for the performance comparison between AllegroGraph and Oracle 12c triple stores.

  19. Construction of ontology augmented networks for protein complex prediction.

    Science.gov (United States)

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian

    2013-01-01

    Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

  20. Topical silver diamine fluoride for dental caries arrest in preschool children: A randomized controlled trial and microbiological analysis of caries associated microbes and resistance gene expression.

    Science.gov (United States)

    Milgrom, Peter; Horst, Jeremy A; Ludwig, Sharity; Rothen, Marilynn; Chaffee, Benjamin W; Lyalina, Svetlana; Pollard, Katherine S; DeRisi, Joseph L; Mancl, Lloyd

    2018-01-01

    The Stopping Cavities Trial investigated effectiveness and safety of 38% silver diamine fluoride in arresting caries lesions. The study was a double-blind randomized placebo-controlled superiority trial with 2 parallel groups. The sites were Oregon preschools. Sixty-six preschool children with ≥1 lesion were enrolled. Silver diamine fluoride (38%) or placebo (blue-tinted water), applied topically to the lesion. The primary endpoint was caries arrest (lesion inactivity, Nyvad criteria) 14-21days post intervention. Dental plaque was collected from all children, and microbial composition was assessed by RNA sequencing from 2 lesions and 1 unaffected surface before treatment and at follow-up for 3 children from each group. Average proportion of arrested caries lesions in the silver diamine fluoride group was higher (0.72; 95% CI; 0.55, 0.84) than in the placebo group (0.05; 95% CI; 0.00, 0.16). Confirmatory analysis using generalized estimating equation log-linear regression, based on the number of arrested lesions and accounting for the number of treated surfaces and length of follow-up, indicates the risk of arrested caries was significantly higher in the treatment group (relative risk, 17.3; 95% CI: 4.3 to 69.4). No harms were observed. RNA sequencing analysis identified no consistent changes in relative abundance of caries-associated microbes, nor emergence of antibiotic or metal resistance gene expression. Topical 38% silver diamine fluoride is effective and safe in arresting cavities in preschool children. The treatment is applicable to primary care practice and may reduce the burden of untreated tooth decay in the population. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  1. XML, Ontologies, and Their Clinical Applications.

    Science.gov (United States)

    Yu, Chunjiang; Shen, Bairong

    2016-01-01

    The development of information technology has resulted in its penetration into every area of clinical research. Various clinical systems have been developed, which produce increasing volumes of clinical data. However, saving, exchanging, querying, and exploiting these data are challenging issues. The development of Extensible Markup Language (XML) has allowed the generation of flexible information formats to facilitate the electronic sharing of structured data via networks, and it has been used widely for clinical data processing. In particular, XML is very useful in the fields of data standardization, data exchange, and data integration. Moreover, ontologies have been attracting increased attention in various clinical fields in recent years. An ontology is the basic level of a knowledge representation scheme, and various ontology repositories have been developed, such as Gene Ontology and BioPortal. The creation of these standardized repositories greatly facilitates clinical research in related fields. In this chapter, we discuss the basic concepts of XML and ontologies, as well as their clinical applications.

  2. Semantic similarity between ontologies at different scales

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Qingpeng; Haglin, David J.

    2016-04-01

    In the past decade, existing and new knowledge and datasets has been encoded in different ontologies for semantic web and biomedical research. The size of ontologies is often very large in terms of number of concepts and relationships, which makes the analysis of ontologies and the represented knowledge graph computational and time consuming. As the ontologies of various semantic web and biomedical applications usually show explicit hierarchical structures, it is interesting to explore the trade-offs between ontological scales and preservation/precision of results when we analyze ontologies. This paper presents the first effort of examining the capability of this idea via studying the relationship between scaling biomedical ontologies at different levels and the semantic similarity values. We evaluate the semantic similarity between three Gene Ontology slims (Plant, Yeast, and Candida, among which the latter two belong to the same kingdom—Fungi) using four popular measures commonly applied to biomedical ontologies (Resnik, Lin, Jiang-Conrath, and SimRel). The results of this study demonstrate that with proper selection of scaling levels and similarity measures, we can significantly reduce the size of ontologies without losing substantial detail. In particular, the performance of Jiang-Conrath and Lin are more reliable and stable than that of the other two in this experiment, as proven by (a) consistently showing that Yeast and Candida are more similar (as compared to Plant) at different scales, and (b) small deviations of the similarity values after excluding a majority of nodes from several lower scales. This study provides a deeper understanding of the application of semantic similarity to biomedical ontologies, and shed light on how to choose appropriate semantic similarity measures for biomedical engineering.

  3. Assessment Applications of Ontologies.

    Science.gov (United States)

    Chung, Gregory K. W. K.; Niemi, David; Bewley, William L.

    This paper discusses the use of ontologies and their applications to assessment. An ontology provides a shared and common understanding of a domain that can be communicated among people and computational systems. The ontology captures one or more experts' conceptual representation of a domain expressed in terms of concepts and the relationships…

  4. Mapping between the OBO and OWL ontology languages.

    Science.gov (United States)

    Tirmizi, Syed Hamid; Aitken, Stuart; Moreira, Dilvan A; Mungall, Chris; Sequeda, Juan; Shah, Nigam H; Miranker, Daniel P

    2011-03-07

    Ontologies are commonly used in biomedicine to organize concepts to describe domains such as anatomies, environments, experiment, taxonomies etc. NCBO BioPortal currently hosts about 180 different biomedical ontologies. These ontologies have been mainly expressed in either the Open Biomedical Ontology (OBO) format or the Web Ontology Language (OWL). OBO emerged from the Gene Ontology, and supports most of the biomedical ontology content. In comparison, OWL is a Semantic Web language, and is supported by the World Wide Web consortium together with integral query languages, rule languages and distributed infrastructure for information interchange. These features are highly desirable for the OBO content as well. A convenient method for leveraging these features for OBO ontologies is by transforming OBO ontologies to OWL. We have developed a methodology for translating OBO ontologies to OWL using the organization of the Semantic Web itself to guide the work. The approach reveals that the constructs of OBO can be grouped together to form a similar layer cake. Thus we were able to decompose the problem into two parts. Most OBO constructs have easy and obvious equivalence to a construct in OWL. A small subset of OBO constructs requires deeper consideration. We have defined transformations for all constructs in an effort to foster a standard common mapping between OBO and OWL. Our mapping produces OWL-DL, a Description Logics based subset of OWL with desirable computational properties for efficiency and correctness. Our Java implementation of the mapping is part of the official Gene Ontology project source. Our transformation system provides a lossless roundtrip mapping for OBO ontologies, i.e. an OBO ontology may be translated to OWL and back without loss of knowledge. In addition, it provides a roadmap for bridging the gap between the two ontology languages in order to enable the use of ontology content in a language independent manner.

  5. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

  6. Toxicology ontology perspectives.

    Science.gov (United States)

    Hardy, Barry; Apic, Gordana; Carthew, Philip; Clark, Dominic; Cook, David; Dix, Ian; Escher, Sylvia; Hastings, Janna; Heard, David J; Jeliazkova, Nina; Judson, Philip; Matis-Mitchell, Sherri; Mitic, Dragana; Myatt, Glenn; Shah, Imran; Spjuth, Ola; Tcheremenskaia, Olga; Toldo, Luca; Watson, David; White, Andrew; Yang, Chihae

    2012-01-01

    The field of predictive toxicology requires the development of open, public, computable, standardized toxicology vocabularies and ontologies to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. In this article we review ontology developments based on a set of perspectives showing how ontologies are being used in predictive toxicology initiatives and applications. Perspectives on resources and initiatives reviewed include OpenTox, eTOX, Pistoia Alliance, ToxWiz, Virtual Liver, EU-ADR, BEL, ToxML, and Bioclipse. We also review existing ontology developments in neighboring fields that can contribute to establishing an ontological framework for predictive toxicology. A significant set of resources is already available to provide a foundation for an ontological framework for 21st century mechanistic-based toxicology research. Ontologies such as ToxWiz provide a basis for application to toxicology investigations, whereas other ontologies under development in the biological, chemical, and biomedical communities could be incorporated in an extended future framework. OpenTox has provided a semantic web framework for the implementation of such ontologies into software applications and linked data resources. Bioclipse developers have shown the benefit of interoperability obtained through ontology by being able to link their workbench application with remote OpenTox web services. Although these developments are promising, an increased international coordination of efforts is greatly needed to develop a more unified, standardized, and open toxicology ontology framework.

  7. Host-microbe and microbe-microbe interactions in the evolution of obligate plant parasitism.

    Science.gov (United States)

    Kemen, Ariane C; Agler, Matthew T; Kemen, Eric

    2015-06-01

    Research on obligate biotrophic plant parasites, which reproduce only on living hosts, has revealed a broad diversity of filamentous microbes that have independently acquired complex morphological structures, such as haustoria. Genome studies have also demonstrated a concerted loss of genes for metabolism and lytic enzymes, and gain of diversity of genes coding for effectors involved in host defense suppression. So far, these traits converge in all known obligate biotrophic parasites, but unexpected genome plasticity remains. This plasticity is manifested as transposable element (TE)-driven increases in genome size, observed to be associated with the diversification of virulence genes under selection pressure. Genome expansion could result from the governing of the pathogen response to ecological selection pressures, such as host or nutrient availability, or to microbial interactions, such as competition, hyperparasitism and beneficial cooperations. Expansion is balanced by alternating sexual and asexual cycles, as well as selfing and outcrossing, which operate to control transposon activity in populations. In turn, the prevalence of these balancing mechanisms seems to be correlated with external biotic factors, suggesting a complex, interconnected evolutionary network in host-pathogen-microbe interactions. Therefore, the next phase of obligate biotrophic pathogen research will need to uncover how this network, including multitrophic interactions, shapes the evolution and diversity of pathogens. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

  8. Integrating phenotype ontologies with PhenomeNET

    KAUST Repository

    Rodriguez-Garcia, Miguel Angel

    2017-12-19

    Background Integration and analysis of phenotype data from humans and model organisms is a key challenge in building our understanding of normal biology and pathophysiology. However, the range of phenotypes and anatomical details being captured in clinical and model organism databases presents complex problems when attempting to match classes across species and across phenotypes as diverse as behaviour and neoplasia. We have previously developed PhenomeNET, a system for disease gene prioritization that includes as one of its components an ontology designed to integrate phenotype ontologies. While not applicable to matching arbitrary ontologies, PhenomeNET can be used to identify related phenotypes in different species, including human, mouse, zebrafish, nematode worm, fruit fly, and yeast. Results Here, we apply the PhenomeNET to identify related classes from two phenotype and two disease ontologies using automated reasoning. We demonstrate that we can identify a large number of mappings, some of which require automated reasoning and cannot easily be identified through lexical approaches alone. Combining automated reasoning with lexical matching further improves results in aligning ontologies. Conclusions PhenomeNET can be used to align and integrate phenotype ontologies. The results can be utilized for biomedical analyses in which phenomena observed in model organisms are used to identify causative genes and mutations underlying human disease.

  9. MEMS and the microbe

    NARCIS (Netherlands)

    Ingham, C.J.; Vlieg, J.E.T.V.H.

    2008-01-01

    In recent years, relatively simple MEMS fabrications have helped accelerate our knowledge of the microbial cell. Current progress and challenges in the application of lab-on-a-chip devices to the viable microbe are reviewed. Furthermore, the degree to which microbiologists are becoming the engineers

  10. Meet the Microbes through the Microbe World Activities with Microbe the Magnificent and Mighty Microbe.

    Science.gov (United States)

    Frame, Kathy, Ed.; Ryan, Karen, Ed.

    The activities presented in this book are the product of the Community Outreach Initiative of the Microbial Literacy Collaborative (MLC). This activity book presents a balanced view of microbes, their benefits, and the diseases they cause. Each activity starts with an interesting introductory statement and includes goals, activity time, time to…

  11. Genetically based location from triploid populations and gene ontology of a 3.3-mb genome region linked to Alternaria brown spot resistance in citrus reveal clusters of resistance genes.

    Directory of Open Access Journals (Sweden)

    José Cuenca

    Full Text Available Genetic analysis of phenotypical traits and marker-trait association in polyploid species is generally considered as a challenge. In the present work, different approaches were combined taking advantage of the particular genetic structures of 2n gametes resulting from second division restitution (SDR to map a genome region linked to Alternaria brown spot (ABS resistance in triploid citrus progeny. ABS in citrus is a serious disease caused by the tangerine pathotype of the fungus Alternaria alternata. This pathogen produces ACT-toxin, which induces necrotic lesions on fruit and young leaves, defoliation and fruit drop in susceptible genotypes. It is a strong concern for triploid breeding programs aiming to produce seedless mandarin cultivars. The monolocus dominant inheritance of susceptibility, proposed on the basis of diploid population studies, was corroborated in triploid progeny. Bulk segregant analysis coupled with genome scan using a large set of genetically mapped SNP markers and targeted genetic mapping by half tetrad analysis, using SSR and SNP markers, allowed locating a 3.3 Mb genomic region linked to ABS resistance near the centromere of chromosome III. Clusters of resistance genes were identified by gene ontology analysis of this genomic region. Some of these genes are good candidates to control the dominant susceptibility to the ACT-toxin. SSR and SNP markers were developed for efficient early marker-assisted selection of ABS resistant hybrids.

  12. Genetically based location from triploid populations and gene ontology of a 3.3-mb genome region linked to Alternaria brown spot resistance in citrus reveal clusters of resistance genes.

    Science.gov (United States)

    Cuenca, José; Aleza, Pablo; Vicent, Antonio; Brunel, Dominique; Ollitrault, Patrick; Navarro, Luis

    2013-01-01

    Genetic analysis of phenotypical traits and marker-trait association in polyploid species is generally considered as a challenge. In the present work, different approaches were combined taking advantage of the particular genetic structures of 2n gametes resulting from second division restitution (SDR) to map a genome region linked to Alternaria brown spot (ABS) resistance in triploid citrus progeny. ABS in citrus is a serious disease caused by the tangerine pathotype of the fungus Alternaria alternata. This pathogen produces ACT-toxin, which induces necrotic lesions on fruit and young leaves, defoliation and fruit drop in susceptible genotypes. It is a strong concern for triploid breeding programs aiming to produce seedless mandarin cultivars. The monolocus dominant inheritance of susceptibility, proposed on the basis of diploid population studies, was corroborated in triploid progeny. Bulk segregant analysis coupled with genome scan using a large set of genetically mapped SNP markers and targeted genetic mapping by half tetrad analysis, using SSR and SNP markers, allowed locating a 3.3 Mb genomic region linked to ABS resistance near the centromere of chromosome III. Clusters of resistance genes were identified by gene ontology analysis of this genomic region. Some of these genes are good candidates to control the dominant susceptibility to the ACT-toxin. SSR and SNP markers were developed for efficient early marker-assisted selection of ABS resistant hybrids.

  13. MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

    Science.gov (United States)

    Zhang, Chengxin; Zheng, Wei; Freddolino, Peter L; Zhang, Yang

    2018-03-10

    Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO, to deduce Gene Ontology attributes of proteins by combining sequence homology-based annotation with low-resolution structure prediction and comparison, and partner's homology-based protein-protein network mapping. The pipeline was tested on a large-scale set of 1000 non-redundant proteins from the CAFA3 experiment. Under the stringent benchmark conditions where templates with >30% sequence identity to the query are excluded, MetaGO achieves average F-measures of 0.487, 0.408, and 0.598, for Molecular Function, Biological Process, and Cellular Component, respectively, which are significantly higher than those achieved by other state-of-the-art function annotations methods. Detailed data analysis shows that the major advantage of the MetaGO lies in the new functional homolog detections from partner's homology-based network mapping and structure-based local and global structure alignments, the confidence scores of which can be optimally combined through logistic regression. These data demonstrate the power of using a hybrid model incorporating protein structure and interaction networks to deduce new functional insights beyond traditional sequence homology-based referrals, especially for proteins that lack homologous function templates. The MetaGO pipeline is available at http://zhanglab.ccmb.med.umich.edu/MetaGO/. Copyright © 2018. Published by Elsevier Ltd.

  14. Constructive Ontology Engineering

    Science.gov (United States)

    Sousan, William L.

    2010-01-01

    The proliferation of the Semantic Web depends on ontologies for knowledge sharing, semantic annotation, data fusion, and descriptions of data for machine interpretation. However, ontologies are difficult to create and maintain. In addition, their structure and content may vary depending on the application and domain. Several methods described in…

  15. A UML profile for the OBO relation ontology

    Science.gov (United States)

    2012-01-01

    Background Ontologies have increasingly been used in the biomedical domain, which has prompted the emergence of different initiatives to facilitate their development and integration. The Open Biological and Biomedical Ontologies (OBO) Foundry consortium provides a repository of life-science ontologies, which are developed according to a set of shared principles. This consortium has developed an ontology called OBO Relation Ontology aiming at standardizing the different types of biological entity classes and associated relationships. Since ontologies are primarily intended to be used by humans, the use of graphical notations for ontology development facilitates the capture, comprehension and communication of knowledge between its users. However, OBO Foundry ontologies are captured and represented basically using text-based notations. The Unified Modeling Language (UML) provides a standard and widely-used graphical notation for modeling computer systems. UML provides a well-defined set of modeling elements, which can be extended using a built-in extension mechanism named Profile. Thus, this work aims at developing a UML profile for the OBO Relation Ontology to provide a domain-specific set of modeling elements that can be used to create standard UML-based ontologies in the biomedical domain. Results We have studied the OBO Relation Ontology, the UML metamodel and the UML profiling mechanism. Based on these studies, we have proposed an extension to the UML metamodel in conformance with the OBO Relation Ontology and we have defined a profile that implements the extended metamodel. Finally, we have applied the proposed UML profile in the development of a number of fragments from different ontologies. Particularly, we have considered the Gene Ontology (GO), the PRotein Ontology (PRO) and the Xenopus Anatomy and Development Ontology (XAO). Conclusions The use of an established and well-known graphical language in the development of biomedical ontologies provides a more

  16. Molecular ecology of aquatic microbes

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-12-31

    Abstracts of reports are presented from a meeting on Molecular Ecology of Aquatic Microbes. Topics included: opportunities offered to aquatic ecology by molecular biology; the role of aquatic microbes in biogeochemical cycles; characterization of the microbial community; the effect of the environment on aquatic microbes; and the targeting of specific biological processes.

  17. Towards Agile Ontology Maintenance

    Science.gov (United States)

    Luczak-Rösch, Markus

    Ontologies are an appropriate means to represent knowledge on the Web. Research on ontology engineering reached practices for an integrative lifecycle support. However, a broader success of ontologies in Web-based information systems remains unreached while the more lightweight semantic approaches are rather successful. We assume, paired with the emerging trend of services and microservices on the Web, new dynamic scenarios gain momentum in which a shared knowledge base is made available to several dynamically changing services with disparate requirements. Our work envisions a step towards such a dynamic scenario in which an ontology adapts to the requirements of the accessing services and applications as well as the user's needs in an agile way and reduces the experts' involvement in ontology maintenance processes.

  18. Conceptual querying through ontologies

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik

    2009-01-01

    is motivated by an obvious need for users to survey huge volumes of objects in query answers. An ontology formalism and a special notion of-instantiated ontology" are introduced. The latter is a structure reflecting the content in the document collection in that; it is a restriction of a general world......We present here ail approach to conceptual querying where the aim is, given a collection of textual database objects or documents, to target an abstraction of the entire database content in terms of the concepts appearing in documents, rather than the documents in the collection. The approach...... knowledge ontology to the concepts instantiated in the collection. The notion of ontology-based similarity is briefly described, language constructs for direct navigation and retrieval of concepts in the ontology are discussed and approaches to conceptual summarization are presented....

  19. Survey on Ontology Mapping

    Science.gov (United States)

    Zhu, Junwu

    To create a sharable semantic space in which the terms from different domain ontology or knowledge system, Ontology mapping become a hot research point in Semantic Web Community. In this paper, motivated factors of ontology mapping research are given firstly, and then 5 dominating theories and methods, such as information accessing technology, machine learning, linguistics, structure graph and similarity, are illustrated according their technology class. Before we analyses the new requirements and takes a long view, the contributions of these theories and methods are summarized in details. At last, this paper suggest to design a group of semantic connector with the ability of migration learning for OWL-2 extended with constrains and the ontology mapping theory of axiom, so as to provide a new methodology for ontology mapping.

  20. Annotating breast cancer microarray samples using ontologies

    Science.gov (United States)

    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

  1. Textiles and Microbes

    Science.gov (United States)

    Freney, Jean; Renaud, François N. R.

    Microbes can be carried by and even multiply on textiles. The first real, premeditated, microbiological warfare happened in 1763, during the Anglo-French wars in North America, when Native American emissaries were given blankets or handkerchiefs contaminated with smallpox. Thus, a small epidemic started and spread rapidly, causing considerable damage to the rank and file of the Native Americans. Nowadays, it could be said that textiles could be vectors of infections in hospitals or communities. The making of antimicrobial textiles could prevent them from becoming a reservoir of microbes in the transmission of infections and in cases of voluntary contamination in a terrorist threat for example. However, methods have to show that textiles are really active and do not attack the cutaneous flora they are in contact with. In this chapter, the role of textiles in the transmission of infections is summarized and the main characteristics of antimicrobial textiles are described.

  2. Quality control for terms and definitions in ontologies and taxonomies

    Directory of Open Access Journals (Sweden)

    Rüegg Alexander

    2006-04-01

    Full Text Available Abstract Background Ontologies and taxonomies are among the most important computational resources for molecular biology and bioinformatics. A series of recent papers has shown that the Gene Ontology (GO, the most prominent taxonomic resource in these fields, is marked by flaws of certain characteristic types, which flow from a failure to address basic ontological principles. As yet, no methods have been proposed which would allow ontology curators to pinpoint flawed terms or definitions in ontologies in a systematic way. Results We present computational methods that automatically identify terms and definitions which are defined in a circular or unintelligible way. We further demonstrate the potential of these methods by applying them to isolate a subset of 6001 problematic GO terms. By automatically aligning GO with other ontologies and taxonomies we were able to propose alternative synonyms and definitions for some of these problematic terms. This allows us to demonstrate that these other resources do not contain definitions superior to those supplied by GO. Conclusion Our methods provide reliable indications of the quality of terms and definitions in ontologies and taxonomies. Further, they are well suited to assist ontology curators in drawing their attention to those terms that are ill-defined. We have further shown the limitations of ontology mapping and alignment in assisting ontology curators in rectifying problems, thus pointing to the need for manual curation.

  3. Practical ontologies for information professionals

    CERN Document Server

    AUTHOR|(CDS)2071712

    2016-01-01

    Practical Ontologies for Information Professionals provides an introduction to ontologies and their development, an essential tool for fighting back against information overload. The development of robust and widely used ontologies is an increasingly important tool in the fight against information overload. The publishing and sharing of explicit explanations for a wide variety of conceptualizations, in a machine readable format, has the power to both improve information retrieval and identify new knowledge. This new book provides an accessible introduction to the following: * What is an ontology? Defining the concept and why it is increasingly important to the information professional * Ontologies and the semantic web * Existing ontologies, such as SKOS, OWL, FOAF, schema.org, and the DBpedia Ontology * Adopting and building ontologies, showing how to avoid repetition of work and how to build a simple ontology with Protege * Interrogating semantic web ontologies * The future of ontologies and the role of the ...

  4. Ontological foundations for evolutionary economics: A Darwinian social ontology

    NARCIS (Netherlands)

    Stoelhorst, J.W.

    2008-01-01

    The purpose of this paper is to further the project of generalized Darwinism by developing a social ontology on the basis of a combined commitment to ontological continuity and ontological commonality. Three issues that are central to the development of a social ontology are addressed: (1) the

  5. The Planteome database: an integrated resource for reference ontologies, plant genomics and phenomics

    Science.gov (United States)

    Cooper, Laurel; Meier, Austin; Laporte, Marie-Angélique; Elser, Justin L; Mungall, Chris; Sinn, Brandon T; Cavaliere, Dario; Carbon, Seth; Dunn, Nathan A; Smith, Barry; Qu, Botong; Preece, Justin; Zhang, Eugene; Todorovic, Sinisa; Gkoutos, Georgios; Doonan, John H; Stevenson, Dennis W; Arnaud, Elizabeth

    2018-01-01

    Abstract The Planteome project (http://www.planteome.org) provides a suite of reference and species-specific ontologies for plants and annotations to genes and phenotypes. Ontologies serve as common standards for semantic integration of a large and growing corpus of plant genomics, phenomics and genetics data. The reference ontologies include the Plant Ontology, Plant Trait Ontology and the Plant Experimental Conditions Ontology developed by the Planteome project, along with the Gene Ontology, Chemical Entities of Biological Interest, Phenotype and Attribute Ontology, and others. The project also provides access to species-specific Crop Ontologies developed by various plant breeding and research communities from around the world. We provide integrated data on plant traits, phenotypes, and gene function and expression from 95 plant taxa, annotated with reference ontology terms. The Planteome project is developing a plant gene annotation platform; Planteome Noctua, to facilitate community engagement. All the Planteome ontologies are publicly available and are maintained at the Planteome GitHub site (https://github.com/Planteome) for sharing, tracking revisions and new requests. The annotated data are freely accessible from the ontology browser (http://browser.planteome.org/amigo) and our data repository. PMID:29186578

  6. Perspectives on ontology learning

    CERN Document Server

    Lehmann, J

    2014-01-01

    Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning.Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the c

  7. Data mining for ontology development.

    Energy Technology Data Exchange (ETDEWEB)

    Davidson, George S.; Strasburg, Jana (Pacific Northwest National Laboratory, Richland, WA); Stampf, David (Brookhaven National Laboratory, Upton, NY); Neymotin,Lev (Brookhaven National Laboratory, Upton, NY); Czajkowski, Carl (Brookhaven National Laboratory, Upton, NY); Shine, Eugene (Savannah River National Laboratory, Aiken, SC); Bollinger, James (Savannah River National Laboratory, Aiken, SC); Ghosh, Vinita (Brookhaven National Laboratory, Upton, NY); Sorokine, Alexandre (Oak Ridge National Laboratory, Oak Ridge, TN); Ferrell, Regina (Oak Ridge National Laboratory, Oak Ridge, TN); Ward, Richard (Oak Ridge National Laboratory, Oak Ridge, TN); Schoenwald, David Alan

    2010-06-01

    A multi-laboratory ontology construction effort during the summer and fall of 2009 prototyped an ontology for counterfeit semiconductor manufacturing. This effort included an ontology development team and an ontology validation methods team. Here the third team of the Ontology Project, the Data Analysis (DA) team reports on their approaches, the tools they used, and results for mining literature for terminology pertinent to counterfeit semiconductor manufacturing. A discussion of the value of ontology-based analysis is presented, with insights drawn from other ontology-based methods regularly used in the analysis of genomic experiments. Finally, suggestions for future work are offered.

  8. Ontology of fractures

    Science.gov (United States)

    Zhong, Jian; Aydina, Atilla; McGuinness, Deborah L.

    2009-03-01

    Fractures are fundamental structures in the Earth's crust and they can impact many societal and industrial activities including oil and gas exploration and production, aquifer management, CO 2 sequestration, waste isolation, the stabilization of engineering structures, and assessing natural hazards (earthquakes, volcanoes, and landslides). Therefore, an ontology which organizes the concepts of fractures could help facilitate a sound education within, and communication among, the highly diverse professional and academic community interested in the problems cited above. We developed a process-based ontology that makes explicit specifications about fractures, their properties, and the deformation mechanisms which lead to their formation and evolution. Our ontology emphasizes the relationships among concepts such as the factors that influence the mechanism(s) responsible for the formation and evolution of specific fracture types. Our ontology is a valuable resource with a potential to applications in a number of fields utilizing recent advances in Information Technology, specifically for digital data and information in computers, grids, and Web services.

  9. A Method for Evaluating and Standardizing Ontologies

    Science.gov (United States)

    Seyed, Ali Patrice

    2012-01-01

    The Open Biomedical Ontology (OBO) Foundry initiative is a collaborative effort for developing interoperable, science-based ontologies. The Basic Formal Ontology (BFO) serves as the upper ontology for the domain-level ontologies of OBO. BFO is an upper ontology of types as conceived by defenders of realism. Among the ontologies developed for OBO…

  10. Manufacturing ontology through templates

    Directory of Open Access Journals (Sweden)

    Diciuc Vlad

    2017-01-01

    Full Text Available The manufacturing industry contains a high volume of knowhow and of high value, much of it being held by key persons in the company. The passing of this know-how is the basis of manufacturing ontology. Among other methods like advanced filtering and algorithm based decision making, one way of handling the manufacturing ontology is via templates. The current paper tackles this approach and highlights the advantages concluding with some recommendations.

  11. The Electronic Notebook Ontology

    OpenAIRE

    Chalk, Stuart

    2016-01-01

    Science is rapidly being brought into the electronic realm and electronic laboratory notebooks (ELN) are a big part of this activity. The representation of the scientific process in the context of an ELN is an important component to making the data recorded in ELNs semantically integrated. This presentation will outline initial developments of an Electronic Notebook Ontology (ENO) that will help tie together the ExptML ontology, HCLS Community Profile data descriptions, and the VIVO-ISF ontol...

  12. Ontology Update in the Cognitive Model of Ontology Learning

    Directory of Open Access Journals (Sweden)

    Zhang De-Hai

    2016-01-01

    Full Text Available Ontology has been used in many hot-spot fields, but most ontology construction methods are semiautomatic, and the construction process of ontology is still a tedious and painstaking task. In this paper, a kind of cognitive models is presented for ontology learning which can simulate human being’s learning from world. In this model, the cognitive strategies are applied with the constrained axioms. Ontology update is a key step when the new knowledge adds into the existing ontology and conflict with old knowledge in the process of ontology learning. This proposal designs and validates the method of ontology update based on the axiomatic cognitive model, which include the ontology update postulates, axioms and operations of the learning model. It is proved that these operators subject to the established axiom system.

  13. Ecological suicide in microbes.

    Science.gov (United States)

    Ratzke, Christoph; Denk, Jonas; Gore, Jeff

    2018-05-01

    The growth and survival of organisms often depend on interactions between them. In many cases, these interactions are positive and caused by a cooperative modification of the environment. Examples are the cooperative breakdown of complex nutrients in microbes or the construction of elaborate architectures in social insects, in which the individual profits from the collective actions of her peers. However, organisms can similarly display negative interactions by changing the environment in ways that are detrimental for them, for example by resource depletion or the production of toxic byproducts. Here we find an extreme type of negative interactions, in which Paenibacillus sp. bacteria modify the environmental pH to such a degree that it leads to a rapid extinction of the whole population, a phenomenon that we call ecological suicide. Modification of the pH is more pronounced at higher population densities, and thus ecological suicide is more likely to occur with increasing bacterial density. Correspondingly, promoting bacterial growth can drive populations extinct whereas inhibiting bacterial growth by the addition of harmful substances-such as antibiotics-can rescue them. Moreover, ecological suicide can cause oscillatory dynamics, even in single-species populations. We found ecological suicide in a wide variety of microbes, suggesting that it could have an important role in microbial ecology and evolution.

  14. Biofuels: from microbes to molecules

    National Research Council Canada - National Science Library

    Lu, Xuefeng

    2014-01-01

    .... The production of different biofuel molecules including hydrogen, methane, ethanol, butanol, higher chain alcohols, isoprenoids and fatty acid derivatives, from genetically engineered microbes...

  15. Microbe-microbe interactions in mixed culture food fermentations

    NARCIS (Netherlands)

    Smid, E.J.; Lacroix, C.

    2013-01-01

    Most known natural and industrial food fermentation processes are driven by either simple or complex communities of microorganisms. Obviously, these fermenting microbes will not only interact with the fermentable substrate but also with each other. These microbe–microbe interactions are complex but

  16. Mining rare associations between biological ontologies.

    Science.gov (United States)

    Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

    2014-01-01

    The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.

  17. Mining rare associations between biological ontologies.

    Directory of Open Access Journals (Sweden)

    Fernando Benites

    Full Text Available The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.

  18. Mining with microbes

    International Nuclear Information System (INIS)

    Rawlings., D.E.; Silver, S.

    1995-01-01

    Microbes are playing increasingly important roles in commercial mining operations, where they are being used in the open-quotes bioleachingclose quotes of copper, uranium, and gold ores. Direct leaching is when microbial metabolism changes the redox state of the metal being harvested, rendering it more soluble. Indirect leaching includes redox chemistry of other metal cations that are then coupled in chemical oxidation or reduction of the harvested metal ion and microbial attack upon and solubilization of the mineral matrix in which the metal is physically embedded. In addition, bacterial cells are used to detoxify the waste cyanide solution from gold-mining operations and as open-quotes absorbantsclose quotes of the mineral cations. Bacterial cells may replace activated carbon or alternative biomass. With an increasing understanding of microbial physiology, biochemistry and molecular genetics, rational approaches to improving these microbial activities become possible. 40 refs., 3 figs

  19. DeMO: An Ontology for Discrete-event Modeling and Simulation

    Science.gov (United States)

    Silver, Gregory A; Miller, John A; Hybinette, Maria; Baramidze, Gregory; York, William S

    2011-01-01

    Several fields have created ontologies for their subdomains. For example, the biological sciences have developed extensive ontologies such as the Gene Ontology, which is considered a great success. Ontologies could provide similar advantages to the Modeling and Simulation community. They provide a way to establish common vocabularies and capture knowledge about a particular domain with community-wide agreement. Ontologies can support significantly improved (semantic) search and browsing, integration of heterogeneous information sources, and improved knowledge discovery capabilities. This paper discusses the design and development of an ontology for Modeling and Simulation called the Discrete-event Modeling Ontology (DeMO), and it presents prototype applications that demonstrate various uses and benefits that such an ontology may provide to the Modeling and Simulation community. PMID:22919114

  20. Prioritising lexical patterns to increase axiomatisation in biomedical ontologies. The role of localisation and modularity.

    Science.gov (United States)

    Quesada-Martínez, M; Fernández-Breis, J T; Stevens, R; Mikroyannidi, E

    2015-01-01

    This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". In previous work, we have defined methods for the extraction of lexical patterns from labels as an initial step towards semi-automatic ontology enrichment methods. Our previous findings revealed that many biomedical ontologies could benefit from enrichment methods using lexical patterns as a starting point.Here, we aim to identify which lexical patterns are appropriate for ontology enrichment, driving its analysis by metrics to prioritised the patterns. We propose metrics for suggesting which lexical regularities should be the starting point to enrich complex ontologies. Our method determines the relevance of a lexical pattern by measuring its locality in the ontology, that is, the distance between the classes associated with the pattern, and the distribution of the pattern in a certain module of the ontology. The methods have been applied to four significant biomedical ontologies including the Gene Ontology and SNOMED CT. The metrics provide information about the engineering of the ontologies and the relevance of the patterns. Our method enables the suggestion of links between classes that are not made explicit in the ontology. We propose a prioritisation of the lexical patterns found in the analysed ontologies. The locality and distribution of lexical patterns offer insights into the further engineering of the ontology. Developers can use this information to improve the axiomatisation of their ontologies.

  1. 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

  2. OpenDMAP: An open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression

    Directory of Open Access Journals (Sweden)

    Johnson Helen L

    2008-01-01

    Full Text Available Abstract Background Information extraction (IE efforts are widely acknowledged to be important in harnessing the rapid advance of biomedical knowledge, particularly in areas where important factual information is published in a diverse literature. Here we report on the design, implementation and several evaluations of OpenDMAP, an ontology-driven, integrated concept analysis system. It significantly advances the state of the art in information extraction by leveraging knowledge in ontological resources, integrating diverse text processing applications, and using an expanded pattern language that allows the mixing of syntactic and semantic elements and variable ordering. Results OpenDMAP information extraction systems were produced for extracting protein transport assertions (transport, protein-protein interaction assertions (interaction and assertions that a gene is expressed in a cell type (expression. Evaluations were performed on each system, resulting in F-scores ranging from .26 – .72 (precision .39 – .85, recall .16 – .85. Additionally, each of these systems was run over all abstracts in MEDLINE, producing a total of 72,460 transport instances, 265,795 interaction instances and 176,153 expression instances. Conclusion OpenDMAP advances the performance standards for extracting protein-protein interaction predications from the full texts of biomedical research articles. Furthermore, this level of performance appears to generalize to other information extraction tasks, including extracting information about predicates of more than two arguments. The output of the information extraction system is always constructed from elements of an ontology, ensuring that the knowledge representation is grounded with respect to a carefully constructed model of reality. The results of these efforts can be used to increase the efficiency of manual curation efforts and to provide additional features in systems that integrate multiple sources for

  3. Microbe Phobia and Kitchen Microbiology.

    Science.gov (United States)

    Williams, Robert P.; Gillen, Alan L.

    1991-01-01

    The authors present an exercise designed to help students overcome the misconception that most microbes make people sick. The activity helps students of all ages understand the important benefits of microbes such as in making bread, soy sauce, cheese, and wine. The role of microorganisms in processing cocoa and coffee and growing plants is also…

  4. Ontology: ambiguity and accuracy

    Directory of Open Access Journals (Sweden)

    Marcelo Schiessl

    2012-08-01

    Full Text Available Ambiguity is a major obstacle to information retrieval. It is source of several researches in Information Science. Ontologies have been studied in order to solve problems related to ambiguities. Paradoxically, “ontology” term is also ambiguous and it is understood according to the use by the community. Philosophy and Computer Science seems to have the most accentuated difference related to the term sense. The former holds undisputed tradition and authority. The latter, in despite of being quite recent, holds an informal sense, but pragmatic. Information Science acts ranging from philosophical to computational approaches so as to get organized collections based on balance between users’ necessities and available information. The semantic web requires informational cycle automation and demands studies related to ontologies. Consequently, revisiting relevant approaches for the study of ontologies plays a relevant role as a way to provide useful ideas to researchers maintaining philosophical rigor, and convenience provided by computers.

  5. Ontological engineering versus metaphysics

    Science.gov (United States)

    Tataj, Emanuel; Tomanek, Roman; Mulawka, Jan

    2011-10-01

    It has been recognized that ontologies are a semantic version of world wide web and can be found in knowledge-based systems. A recent time survey of this field also suggest that practical artificial intelligence systems may be motivated by this research. Especially strong artificial intelligence as well as concept of homo computer can also benefit from their use. The main objective of this contribution is to present and review already created ontologies and identify the main advantages which derive such approach for knowledge management systems. We would like to present what ontological engineering borrows from metaphysics and what a feedback it can provide to natural language processing, simulations and modelling. The potential topics of further development from philosophical point of view is also underlined.

  6. The Microbe Directory: An annotated, searchable inventory of microbes' characteristics.

    Science.gov (United States)

    Shaaban, Heba; Westfall, David A; Mohammad, Rawhi; Danko, David; Bezdan, Daniela; Afshinnekoo, Ebrahim; Segata, Nicola; Mason, Christopher E

    2018-01-05

    The Microbe Directory is a collective research effort to profile and annotate more than 7,500 unique microbial species from the MetaPhlAn2 database that includes bacteria, archaea, viruses, fungi, and protozoa. By collecting and summarizing data on various microbes' characteristics, the project comprises a database that can be used downstream of large-scale metagenomic taxonomic analyses, allowing one to interpret and explore their taxonomic classifications to have a deeper understanding of the microbial ecosystem they are studying. Such characteristics include, but are not limited to: optimal pH, optimal temperature, Gram stain, biofilm-formation, spore-formation, antimicrobial resistance, and COGEM class risk rating. The database has been manually curated by trained student-researchers from Weill Cornell Medicine and CUNY-Hunter College, and its analysis remains an ongoing effort with open-source capabilities so others can contribute. Available in SQL, JSON, and CSV (i.e. Excel) formats, the Microbe Directory can be queried for the aforementioned parameters by a microorganism's taxonomy. In addition to the raw database, The Microbe Directory has an online counterpart ( https://microbe.directory/) that provides a user-friendly interface for storage, retrieval, and analysis into which other microbial database projects could be incorporated. The Microbe Directory was primarily designed to serve as a resource for researchers conducting metagenomic analyses, but its online web interface should also prove useful to any individual who wishes to learn more about any particular microbe.

  7. A Method for Building Personalized Ontology Summaries

    OpenAIRE

    Queiroz-Sousa, Paulo Orlando; Salgado, Ana Carolina; Pires, Carlos Eduardo

    2013-01-01

    In the context of ontology engineering, the ontology understanding is the basis for its further developmentand reuse. One intuitive eective approach to support ontology understanding is the process of ontology summarizationwhich highlights the most important concepts of an ontology. Ontology summarization identies an excerpt from anontology that contains the most relevant concepts and produces an abridged ontology. In this article, we present amethod for summarizing ontologies that represent ...

  8. Ontology and medical diagnosis.

    Science.gov (United States)

    Bertaud-Gounot, Valérie; Duvauferrier, Régis; Burgun, Anita

    2012-03-01

    Ontology and associated generic tools are appropriate for knowledge modeling and reasoning, but most of the time, disease definitions in existing description logic (DL) ontology are not sufficient to classify patient's characteristics under a particular disease because they do not formalize operational definitions of diseases (association of signs and symptoms=diagnostic criteria). The main objective of this study is to propose an ontological representation which takes into account the diagnostic criteria on which specific patient conditions may be classified under a specific disease. This method needs as a prerequisite a clear list of necessary and sufficient diagnostic criteria as defined for lots of diseases by learned societies. It does not include probability/uncertainty which Web Ontology Language (OWL 2.0) cannot handle. We illustrate it with spondyloarthritis (SpA). Ontology has been designed in Protégé 4.1 OWL-DL2.0. Several kinds of criteria were formalized: (1) mandatory criteria, (2) picking two criteria among several diagnostic criteria, (3) numeric criteria. Thirty real patient cases were successfully classified with the reasoner. This study shows that it is possible to represent operational definitions of diseases with OWL and successfully classify real patient cases. Representing diagnostic criteria as descriptive knowledge (instead of rules in Semantic Web Rule Language or Prolog) allows us to take advantage of tools already available for OWL. While we focused on Assessment of SpondyloArthritis international Society SpA criteria, we believe that many of the representation issues addressed here are relevant to using OWL-DL for operational definition of other diseases in ontology.

  9. Core Semantics for Public Ontologies

    National Research Council Canada - National Science Library

    Suni, Niranjan

    2005-01-01

    ... (schemas or ontologies) with respect to objects. The DARPA Agent Markup Language (DAML) through the use of ontologies provides a very powerful way to describe objects and their relationships to other objects...

  10. Learning expressive ontologies

    CERN Document Server

    Völker, J

    2009-01-01

    This publication advances the state-of-the-art in ontology learning by presenting a set of novel approaches to the semi-automatic acquisition, refinement and evaluation of logically complex axiomatizations. It has been motivated by the fact that the realization of the semantic web envisioned by Tim Berners-Lee is still hampered by the lack of ontological resources, while at the same time more and more applications of semantic technologies emerge from fast-growing areas such as e-business or life sciences. Such knowledge-intensive applications, requiring large scale reasoning over complex domai

  11. ONTOLOGY IN PHARMACY

    Directory of Open Access Journals (Sweden)

    L. Yu. Babintseva

    2015-05-01

    Full Text Available It’s considered ontological models for formalization of knowledge in pharmacy. There is emphasized the view that the possibility of rapid exchange of information in the pharmaceutical industry, it is necessary to create a single information space. This means not only the establishment of uniform standards for the presentation of information on pharmaceutical groups pharmacotherapeutic classifications, but also the creation of a unified and standardized system for the transfer and renewal of knowledge. It is the organization of information in the ontology helps quickly in the future to build expert systems and applications to work with data.

  12. Summarization by domain ontology navigation

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik

    2013-01-01

    of the subject. In between these two extremes, conceptual summaries encompass selected concepts derived using background knowledge. We address in this paper an approach where conceptual summaries are provided through a conceptualization as given by an ontology. The ontology guiding the summarization can...... be a simple taxonomy or a generative domain ontology. A domain ontology can be provided by a preanalysis of a domain corpus and can be used to condense improved summaries that better reflects the conceptualization of a given domain....

  13. InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk.

    Science.gov (United States)

    Cheng, Liang; Jiang, Yue; Ju, Hong; Sun, Jie; Peng, Jiajie; Zhou, Meng; Hu, Yang

    2018-01-19

    Since the establishment of the first biomedical ontology Gene Ontology (GO), the number of biomedical ontology has increased dramatically. Nowadays over 300 ontologies have been built including extensively used Disease Ontology (DO) and Human Phenotype Ontology (HPO). Because of the advantage of identifying novel relationships between terms, calculating similarity between ontology terms is one of the major tasks in this research area. Though similarities between terms within each ontology have been studied with in silico methods, term similarities across different ontologies were not investigated as deeply. The latest method took advantage of gene functional interaction network (GFIN) to explore such inter-ontology similarities of terms. However, it only used gene interactions and failed to make full use of the connectivity among gene nodes of the network. In addition, all existent methods are particularly designed for GO and their performances on the extended ontology community remain unknown. We proposed a method InfAcrOnt to infer similarities between terms across ontologies utilizing the entire GFIN. InfAcrOnt builds a term-gene-gene network which comprised ontology annotations and GFIN, and acquires similarities between terms across ontologies through modeling the information flow within the network by random walk. In our benchmark experiments on sub-ontologies of GO, InfAcrOnt achieves a high average area under the receiver operating characteristic curve (AUC) (0.9322 and 0.9309) and low standard deviations (1.8746e-6 and 3.0977e-6) in both human and yeast benchmark datasets exhibiting superior performance. Meanwhile, comparisons of InfAcrOnt results and prior knowledge on pair-wise DO-HPO terms and pair-wise DO-GO terms show high correlations. The experiment results show that InfAcrOnt significantly improves the performance of inferring similarities between terms across ontologies in benchmark set.

  14. Biomedical ontologies: toward scientific debate.

    Science.gov (United States)

    Maojo, V; Crespo, J; García-Remesal, M; de la Iglesia, D; Perez-Rey, D; Kulikowski, C

    2011-01-01

    Biomedical ontologies have been very successful in structuring knowledge for many different applications, receiving widespread praise for their utility and potential. Yet, the role of computational ontologies in scientific research, as opposed to knowledge management applications, has not been extensively discussed. We aim to stimulate further discussion on the advantages and challenges presented by biomedical ontologies from a scientific perspective. We review various aspects of biomedical ontologies going beyond their practical successes, and focus on some key scientific questions in two ways. First, we analyze and discuss current approaches to improve biomedical ontologies that are based largely on classical, Aristotelian ontological models of reality. Second, we raise various open questions about biomedical ontologies that require further research, analyzing in more detail those related to visual reasoning and spatial ontologies. We outline significant scientific issues that biomedical ontologies should consider, beyond current efforts of building practical consensus between them. For spatial ontologies, we suggest an approach for building "morphospatial" taxonomies, as an example that could stimulate research on fundamental open issues for biomedical ontologies. Analysis of a large number of problems with biomedical ontologies suggests that the field is very much open to alternative interpretations of current work, and in need of scientific debate and discussion that can lead to new ideas and research directions.

  15. Biofuels from microbes

    Energy Technology Data Exchange (ETDEWEB)

    Antoni, D. [Technische Univ. Muenchen, Freising-Weihenstephan (Germany). Inst. of Resource and Energy Technology; Zverlov, V.V.; Schwarz, W.H. [Technische Univ. Muenchen, Freising-Weihenstephan (Germany). Dept. of Microbiology

    2007-11-15

    Today, biomass covers about 10% of the world's primary energy demand. Against a backdrop of rising crude oil prices, depletion of resources, political instability in producing countries and environmental challenges, besides efficiency and intelligent use, only biomass has the potential to replace the supply of an energy hungry civilisation. Plant biomass is an abundant and renewable source of energy-rich carbohydrates which can be efficiently converted by microbes into biofuels, of which, only bioethanol is produced on an industrial scale today. Biomethane is produced on a large scale, but is not yet utilised for transportation. Biobutanol is on the agenda of several companies and may be used in the near future as a supplement for gasoline, diesel and kerosene, as well as contributing to the partially biological production of butyl-t-butylether, BTBE as does bioethanol today with ETBE. Biohydrogen, biomethanol and microbially made biodiesel still require further development. This paper reviews microbially made biofuels which have potential to replace our present day fuels, either alone, by blending, or by chemical conversion. It also summarises the history of biofuels and provides insight into the actual production in various countries, reviewing their policies and adaptivity to the energy challenges of foreseeable future. (orig.)

  16. Using a Foundational Ontology for Reengineering a Software Enterprise Ontology

    Science.gov (United States)

    Perini Barcellos, Monalessa; de Almeida Falbo, Ricardo

    The knowledge about software organizations is considerably relevant to software engineers. The use of a common vocabulary for representing the useful knowledge about software organizations involved in software projects is important for several reasons, such as to support knowledge reuse and to allow communication and interoperability between tools. Domain ontologies can be used to define a common vocabulary for sharing and reuse of knowledge about some domain. Foundational ontologies can be used for evaluating and re-designing domain ontologies, giving to these real-world semantics. This paper presents an evaluating of a Software Enterprise Ontology that was reengineered using the Unified Foundation Ontology (UFO) as basis.

  17. The design ontology

    DEFF Research Database (Denmark)

    Storga, Mario; Andreasen, Mogens Myrup; Marjanovic, Dorian

    2010-01-01

    The article presents the research of the nature, building and practical role of a Design Ontology as a potential framework for the more efficient product development (PD) data-, information- and knowledge- description, -explanation, -understanding and -reusing. In the methodology for development ...

  18. Dahlbeck and Pure Ontology

    Science.gov (United States)

    Mackenzie, Jim

    2016-01-01

    This article responds to Johan Dahlbeck's "Towards a pure ontology: Children's bodies and morality" ["Educational Philosophy and Theory," vol. 46 (1), 2014, pp. 8-23 (EJ1026561)]. His arguments from Nietzsche and Spinoza do not carry the weight he supposes, and the conclusions he draws from them about pedagogy would be…

  19. Audit Validation Using Ontologies

    Directory of Open Access Journals (Sweden)

    Ion IVAN

    2015-01-01

    Full Text Available Requirements to increase quality audit processes in enterprises are defined. It substantiates the need for assessment and management audit processes using ontologies. Sets of rules, ways to assess the consistency of rules and behavior within the organization are defined. Using ontologies are obtained qualifications that assess the organization's audit. Elaboration of the audit reports is a perfect algorithm-based activity characterized by generality, determinism, reproducibility, accuracy and a well-established. The auditors obtain effective levels. Through ontologies obtain the audit calculated level. Because the audit report is qualitative structure of information and knowledge it is very hard to analyze and interpret by different groups of users (shareholders, managers or stakeholders. Developing ontology for audit reports validation will be a useful instrument for both auditors and report users. In this paper we propose an instrument for validation of audit reports contain a lot of keywords that calculates indicators, a lot of indicators for each key word there is an indicator, qualitative levels; interpreter who builds a table of indicators, levels of actual and calculated levels.

  20. Biomedicine: an ontological dissection.

    Science.gov (United States)

    Baronov, David

    2008-01-01

    Though ubiquitous across the medical social sciences literature, the term "biomedicine" as an analytical concept remains remarkably slippery. It is argued here that this imprecision is due in part to the fact that biomedicine is comprised of three interrelated ontological spheres, each of which frames biomedicine as a distinct subject of investigation. This suggests that, depending upon one's ontological commitment, the meaning of biomedicine will shift. From an empirical perspective, biomedicine takes on the appearance of a scientific enterprise and is defined as a derivative category of Western science more generally. From an interpretive perspective, biomedicine represents a symbolic-cultural expression whose adherence to the principles of scientific objectivity conceals an ideological agenda. From a conceptual perspective, biomedicine represents an expression of social power that reflects structures of power and privilege within capitalist society. No one perspective exists in isolation and so the image of biomedicine from any one presents an incomplete understanding. It is the mutually-conditioning interrelations between these ontological spheres that account for biomedicine's ongoing development. Thus, the ontological dissection of biomedicine that follows, with particular emphasis on the period of its formal crystallization in the latter nineteenth and early twentieth century, is intended to deepen our understanding of biomedicine as an analytical concept across the medical social sciences literature.

  1. Epistemology and ontology in core ontologies: FOLaw and LRI-Core, two core ontologies for law

    NARCIS (Netherlands)

    Breukers, J.A.P.J.; Hoekstra, R.J.

    2004-01-01

    For more than a decade constructing ontologies for legal domains, we, at the Leibniz Center for Law, felt really the need to develop a core ontology for law that would enable us to re-use the common denominator of the various legal domains. In this paper we present two core ontologies for law. The

  2. Development of an Ontology for Periodontitis.

    Science.gov (United States)

    Suzuki, Asami; Takai-Igarashi, Takako; Nakaya, Jun; Tanaka, Hiroshi

    2015-01-01

    In the clinical dentists and periodontal researchers' community, there is an obvious demand for a systems model capable of linking the clinical presentation of periodontitis to underlying molecular knowledge. A computer-readable representation of processes on disease development will give periodontal researchers opportunities to elucidate pathways and mechanisms of periodontitis. An ontology for periodontitis can be a model for integration of large variety of factors relating to a complex disease such as chronic inflammation in different organs accompanied by bone remodeling and immune system disorders, which has recently been referred to as osteoimmunology. Terms characteristic of descriptions related to the onset and progression of periodontitis were manually extracted from 194 review articles and PubMed abstracts by experts in periodontology. We specified all the relations between the extracted terms and constructed them into an ontology for periodontitis. We also investigated matching between classes of our ontology and that of Gene Ontology Biological Process. We developed an ontology for periodontitis called Periodontitis-Ontology (PeriO). The pathological progression of periodontitis is caused by complex, multi-factor interrelationships. PeriO consists of all the required concepts to represent the pathological progression and clinical treatment of periodontitis. The pathological processes were formalized with reference to Basic Formal Ontology and Relation Ontology, which accounts for participants in the processes realized by biological objects such as molecules and cells. We investigated the peculiarity of biological processes observed in pathological progression and medical treatments for the disease in comparison with Gene Ontology Biological Process (GO-BP) annotations. The results indicated that peculiarities of Perio existed in 1) granularity and context dependency of both the conceptualizations, and 2) causality intrinsic to the pathological processes

  3. Benchmarking ontologies: bigger or better?

    Directory of Open Access Journals (Sweden)

    Lixia Yao

    2011-01-01

    Full Text Available A scientific ontology is a formal representation of knowledge within a domain, typically including central concepts, their properties, and relations. With the rise of computers and high-throughput data collection, ontologies have become essential to data mining and sharing across communities in the biomedical sciences. Powerful approaches exist for testing the internal consistency of an ontology, but not for assessing the fidelity of its domain representation. We introduce a family of metrics that describe the breadth and depth with which an ontology represents its knowledge domain. We then test these metrics using (1 four of the most common medical ontologies with respect to a corpus of medical documents and (2 seven of the most popular English thesauri with respect to three corpora that sample language from medicine, news, and novels. Here we show that our approach captures the quality of ontological representation and guides efforts to narrow the breach between ontology and collective discourse within a domain. Our results also demonstrate key features of medical ontologies, English thesauri, and discourse from different domains. Medical ontologies have a small intersection, as do English thesauri. Moreover, dialects characteristic of distinct domains vary strikingly as many of the same words are used quite differently in medicine, news, and novels. As ontologies are intended to mirror the state of knowledge, our methods to tighten the fit between ontology and domain will increase their relevance for new areas of biomedical science and improve the accuracy and power of inferences computed across them.

  4. Ontology-based Information Retrieval

    DEFF Research Database (Denmark)

    Styltsvig, Henrik Bulskov

    In this thesis, we will present methods for introducing ontologies in information retrieval. The main hypothesis is that the inclusion of conceptual knowledge such as ontologies in the information retrieval process can contribute to the solution of major problems currently found in information...... retrieval. This utilization of ontologies has a number of challenges. Our focus is on the use of similarity measures derived from the knowledge about relations between concepts in ontologies, the recognition of semantic information in texts and the mapping of this knowledge into the ontologies in use......, as well as how to fuse together the ideas of ontological similarity and ontological indexing into a realistic information retrieval scenario. To achieve the recognition of semantic knowledge in a text, shallow natural language processing is used during indexing that reveals knowledge to the level of noun...

  5. Ontology Design Patterns for Combining Pathology and Anatomy: Application to Study Aging and Longevity in Inbred Mouse Strains

    KAUST Repository

    Alghamdi, Sarah M.

    2018-05-13

    In biomedical research, ontologies are widely used to represent knowledge as well as to annotate datasets. Many of the existing ontologies cover a single type of phenomena, such as a process, cell type, gene, pathological entity or anatomical structure. Consequently, there is a requirement to use multiple ontologies to fully characterize the observations in the datasets. Although this allows precise annotation of different aspects of a given dataset, it limits our ability to use the ontologies in data analysis, as the ontologies are usually disconnected and their combinations cannot be exploited. Motivated by this, here we present novel ontology design methods for combining pathology and anatomy concepts. To this end, we use a dataset of mouse models which has been characterized through two ontologies: one of them is the mouse pathology ontology (MPATH) covering pathological lesions while the other is the mouse anatomy ontology (MA) covering the anatomical site of the lesions. We propose four novel ontology design patterns for combining these ontologies, and use these patterns to generate four ontologies in a data-driven way. To evaluate the generated ontologies, we utilize these in ontology-based data analysis, including ontology enrichment analysis and computation of semantic similarity. We demonstrate that there are significant differences between the four ontologies in different analysis approaches. In addition, when using semantic similarity to confirm the hypothesis that genetically identical mice should develop more similar diseases, the generated combined ontologies lead to significantly better analysis results compared to using each ontology individually. Our results reveal that using ontology design patterns to combine different facets characterizing a dataset can improve established analysis methods.

  6. Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies.

    Science.gov (United States)

    Lamy, Jean-Baptiste

    2017-07-01

    Ontologies are widely used in the biomedical domain. While many tools exist for the edition, alignment or evaluation of ontologies, few solutions have been proposed for ontology programming interface, i.e. for accessing and modifying an ontology within a programming language. Existing query languages (such as SPARQL) and APIs (such as OWLAPI) are not as easy-to-use as object programming languages are. Moreover, they provide few solutions to difficulties encountered with biomedical ontologies. Our objective was to design a tool for accessing easily the entities of an OWL ontology, with high-level constructs helping with biomedical ontologies. From our experience on medical ontologies, we identified two difficulties: (1) many entities are represented by classes (rather than individuals), but the existing tools do not permit manipulating classes as easily as individuals, (2) ontologies rely on the open-world assumption, whereas the medical reasoning must consider only evidence-based medical knowledge as true. We designed a Python module for ontology-oriented programming. It allows access to the entities of an OWL ontology as if they were objects in the programming language. We propose a simple high-level syntax for managing classes and the associated "role-filler" constraints. We also propose an algorithm for performing local closed world reasoning in simple situations. We developed Owlready, a Python module for a high-level access to OWL ontologies. The paper describes the architecture and the syntax of the module version 2. It details how we integrated the OWL ontology model with the Python object model. The paper provides examples based on Gene Ontology (GO). We also demonstrate the interest of Owlready in a use case focused on the automatic comparison of the contraindications of several drugs. This use case illustrates the use of the specific syntax proposed for manipulating classes and for performing local closed world reasoning. Owlready has been successfully

  7. A molecular study of microbe transfer between distant environments.

    Science.gov (United States)

    Hooper, Sean D; Raes, Jeroen; Foerstner, Konrad U; Harrington, Eoghan D; Dalevi, Daniel; Bork, Peer

    2008-07-09

    Environments and their organic content are generally not static and isolated, but in a constant state of exchange and interaction with each other. Through physical or biological processes, organisms, especially microbes, may be transferred between environments whose characteristics may be quite different. The transferred microbes may not survive in their new environment, but their DNA will be deposited. In this study, we compare two environmental sequencing projects to find molecular evidence of transfer of microbes over vast geographical distances. By studying synonymous nucleotide composition, oligomer frequency and orthology between predicted genes in metagenomics data from two environments, terrestrial and aquatic, and by correlating with phylogenetic mappings, we find that both environments are likely to contain trace amounts of microbes which have been far removed from their original habitat. We also suggest a bias in direction from soil to sea, which is consistent with the cycles of planetary wind and water. Our findings support the Baas-Becking hypothesis formulated in 1934, which states that due to dispersion and population sizes, microbes are likely to be found in widely disparate environments. Furthermore, the availability of genetic material from distant environments is a possible font of novel gene functions for lateral gene transfer.

  8. A molecular study of microbe transfer between distant environments.

    Directory of Open Access Journals (Sweden)

    Sean D Hooper

    Full Text Available BACKGROUND: Environments and their organic content are generally not static and isolated, but in a constant state of exchange and interaction with each other. Through physical or biological processes, organisms, especially microbes, may be transferred between environments whose characteristics may be quite different. The transferred microbes may not survive in their new environment, but their DNA will be deposited. In this study, we compare two environmental sequencing projects to find molecular evidence of transfer of microbes over vast geographical distances. METHODOLOGY: By studying synonymous nucleotide composition, oligomer frequency and orthology between predicted genes in metagenomics data from two environments, terrestrial and aquatic, and by correlating with phylogenetic mappings, we find that both environments are likely to contain trace amounts of microbes which have been far removed from their original habitat. We also suggest a bias in direction from soil to sea, which is consistent with the cycles of planetary wind and water. CONCLUSIONS: Our findings support the Baas-Becking hypothesis formulated in 1934, which states that due to dispersion and population sizes, microbes are likely to be found in widely disparate environments. Furthermore, the availability of genetic material from distant environments is a possible font of novel gene functions for lateral gene transfer.

  9. Completeness, supervenience and ontology

    International Nuclear Information System (INIS)

    Maudlin, Tim W E

    2007-01-01

    In 1935, Einstein, Podolsky and Rosen raised the issue of the completeness of the quantum description of a physical system. What they had in mind is whether or not the quantum description is informationally complete, in that all physical features of a system can be recovered from it. In a collapse theory such as the theory of Ghirardi, Rimini and Weber, the quantum wavefunction is informationally complete, and this has often been taken to suggest that according to that theory the wavefunction is all there is. If we distinguish the ontological completeness of a description from its informational completeness, we can see that the best interpretations of the GRW theory must postulate more physical ontology than just the wavefunction

  10. Completeness, supervenience and ontology

    Energy Technology Data Exchange (ETDEWEB)

    Maudlin, Tim W E [Department of Philosophy, Rutgers University, 26 Nichol Avenue, New Brunswick, NJ 08901-1411 (United States)

    2007-03-23

    In 1935, Einstein, Podolsky and Rosen raised the issue of the completeness of the quantum description of a physical system. What they had in mind is whether or not the quantum description is informationally complete, in that all physical features of a system can be recovered from it. In a collapse theory such as the theory of Ghirardi, Rimini and Weber, the quantum wavefunction is informationally complete, and this has often been taken to suggest that according to that theory the wavefunction is all there is. If we distinguish the ontological completeness of a description from its informational completeness, we can see that the best interpretations of the GRW theory must postulate more physical ontology than just the wavefunction.

  11. LOGISTICS OPTIMIZATION USING ONTOLOGIES

    OpenAIRE

    Hendi , Hayder; Ahmad , Adeel; Bouneffa , Mourad; Fonlupt , Cyril

    2014-01-01

    International audience; Logistics processes involve complex physical flows and integration of different elements. It is widely observed that the uncontrolled processes can decline the state of logistics. The optimization of logistic processes can support the desired growth and consistent continuity of logistics. In this paper, we present a software framework for logistic processes optimization. It primarily defines logistic ontologies and then optimize them. It intends to assist the design of...

  12. A unified anatomy ontology of the vertebrate skeletal system.

    Directory of Open Access Journals (Sweden)

    Wasila M Dahdul

    Full Text Available The skeleton is of fundamental importance in research in comparative vertebrate morphology, paleontology, biomechanics, developmental biology, and systematics. Motivated by research questions that require computational access to and comparative reasoning across the diverse skeletal phenotypes of vertebrates, we developed a module of anatomical concepts for the skeletal system, the Vertebrate Skeletal Anatomy Ontology (VSAO, to accommodate and unify the existing skeletal terminologies for the species-specific (mouse, the frog Xenopus, zebrafish and multispecies (teleost, amphibian vertebrate anatomy ontologies. Previous differences between these terminologies prevented even simple queries across databases pertaining to vertebrate morphology. This module of upper-level and specific skeletal terms currently includes 223 defined terms and 179 synonyms that integrate skeletal cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages, and subdivisions of the skeletal system. The VSAO is designed to integrate with other ontologies, including the Common Anatomy Reference Ontology (CARO, Gene Ontology (GO, Uberon, and Cell Ontology (CL, and it is freely available to the community to be updated with additional terms required for research. Its structure accommodates anatomical variation among vertebrate species in development, structure, and composition. Annotation of diverse vertebrate phenotypes with this ontology will enable novel inquiries across the full spectrum of phenotypic diversity.

  13. A unified anatomy ontology of the vertebrate skeletal system.

    Science.gov (United States)

    Dahdul, Wasila M; Balhoff, James P; Blackburn, David C; Diehl, Alexander D; Haendel, Melissa A; Hall, Brian K; Lapp, Hilmar; Lundberg, John G; Mungall, Christopher J; Ringwald, Martin; Segerdell, Erik; Van Slyke, Ceri E; Vickaryous, Matthew K; Westerfield, Monte; Mabee, Paula M

    2012-01-01

    The skeleton is of fundamental importance in research in comparative vertebrate morphology, paleontology, biomechanics, developmental biology, and systematics. Motivated by research questions that require computational access to and comparative reasoning across the diverse skeletal phenotypes of vertebrates, we developed a module of anatomical concepts for the skeletal system, the Vertebrate Skeletal Anatomy Ontology (VSAO), to accommodate and unify the existing skeletal terminologies for the species-specific (mouse, the frog Xenopus, zebrafish) and multispecies (teleost, amphibian) vertebrate anatomy ontologies. Previous differences between these terminologies prevented even simple queries across databases pertaining to vertebrate morphology. This module of upper-level and specific skeletal terms currently includes 223 defined terms and 179 synonyms that integrate skeletal cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages), and subdivisions of the skeletal system. The VSAO is designed to integrate with other ontologies, including the Common Anatomy Reference Ontology (CARO), Gene Ontology (GO), Uberon, and Cell Ontology (CL), and it is freely available to the community to be updated with additional terms required for research. Its structure accommodates anatomical variation among vertebrate species in development, structure, and composition. Annotation of diverse vertebrate phenotypes with this ontology will enable novel inquiries across the full spectrum of phenotypic diversity.

  14. A Unified Anatomy Ontology of the Vertebrate Skeletal System

    Science.gov (United States)

    Dahdul, Wasila M.; Balhoff, James P.; Blackburn, David C.; Diehl, Alexander D.; Haendel, Melissa A.; Hall, Brian K.; Lapp, Hilmar; Lundberg, John G.; Mungall, Christopher J.; Ringwald, Martin; Segerdell, Erik; Van Slyke, Ceri E.; Vickaryous, Matthew K.; Westerfield, Monte; Mabee, Paula M.

    2012-01-01

    The skeleton is of fundamental importance in research in comparative vertebrate morphology, paleontology, biomechanics, developmental biology, and systematics. Motivated by research questions that require computational access to and comparative reasoning across the diverse skeletal phenotypes of vertebrates, we developed a module of anatomical concepts for the skeletal system, the Vertebrate Skeletal Anatomy Ontology (VSAO), to accommodate and unify the existing skeletal terminologies for the species-specific (mouse, the frog Xenopus, zebrafish) and multispecies (teleost, amphibian) vertebrate anatomy ontologies. Previous differences between these terminologies prevented even simple queries across databases pertaining to vertebrate morphology. This module of upper-level and specific skeletal terms currently includes 223 defined terms and 179 synonyms that integrate skeletal cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages), and subdivisions of the skeletal system. The VSAO is designed to integrate with other ontologies, including the Common Anatomy Reference Ontology (CARO), Gene Ontology (GO), Uberon, and Cell Ontology (CL), and it is freely available to the community to be updated with additional terms required for research. Its structure accommodates anatomical variation among vertebrate species in development, structure, and composition. Annotation of diverse vertebrate phenotypes with this ontology will enable novel inquiries across the full spectrum of phenotypic diversity. PMID:23251424

  15. Feasibility of automated foundational ontology interchangeability

    CSIR Research Space (South Africa)

    Khan, ZC

    2014-11-01

    Full Text Available the Source Domain Ontology (sOd), with the domain knowledge com- ponent of the source ontology, the Source Foundational Ontology (sOf ) that is the foundational ontology component of the source ontology that is to be interchanged, and any equivalence... or subsumption mappings between enti- ties in sOd and sOf . – The Target Ontology (tO) which has been interchanged, which comprises the Target Domain Ontology (tOd), with the domain knowledge component of the target ontology, and the Target Foundational Ontology...

  16. An Ontology for Software Engineering Education

    Science.gov (United States)

    Ling, Thong Chee; Jusoh, Yusmadi Yah; Adbullah, Rusli; Alwi, Nor Hayati

    2013-01-01

    Software agents communicate using ontology. It is important to build an ontology for specific domain such as Software Engineering Education. Building an ontology from scratch is not only hard, but also incur much time and cost. This study aims to propose an ontology through adaptation of the existing ontology which is originally built based on a…

  17. Drug target ontology to classify and integrate drug discovery data

    DEFF Research Database (Denmark)

    Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande

    2017-01-01

    using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem...... of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target...... characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. CONCLUSIONS: DTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein...

  18. Interaction between leptin and leptin receptor in gastric carcinoma: Gene ontology analysis Interacción entre la leptina y su receptor en el carcinoma gástrico: análisis de ontología genética

    Directory of Open Access Journals (Sweden)

    V. Wiwanitkit

    2007-04-01

    Full Text Available Gastric carcinoma is a rare but important malignancy. The link between leptin, a cytokine that is elevated in obese individuals, and cancer development has been proposed. It is noted that leptin and its receptor may play a positive role in the progression in gastric cancer. However, the exact mechanism resulting form the interaction between leptin and leptin receptor has never been clarified. Here, the author used a new gene ontology technology to predict the molecular function and biological process due to the interaction between leptin and leptin receptor. Comparing to leptin and leptin receptor, the leptin-leptin receptor poses the same function and biological process as leptin receptor. This can confirm that leptin receptor has a significant suppressive effect on the expression of leptin. Loss of hormone activity and disturbance of normal cell signaling pathway of leptin can be seen. Blocking of receptor might be rational therapeutic strategy.El carcinoma gástrico es un cáncer muy poco frecuente pero importante. Se ha postulado que la leptina, una citocina que aparece elevada en las personas obesas, está relacionada con el cáncer. Se sabe que la leptina y su receptor pueden desempeñar un papel positivo en la progresión del cáncer gástrico. Sin embargo, nunca se ha dilucidado el mecanismo exacto al que daría lugar la interacción entre la leptina y el receptor de leptina. Aquí, el autor empleó una nueva tecnología de ontología genética para predecir la función molecular y el proceso biológico resultantes de la interacción entre la leptina y su receptor. Frente a la leptina y su receptor, el compuesto leptina-receptor realiza la misma función y el mismo proceso biológico que el receptor de leptina. Esto puede confirmar que el receptor de leptina ejerce un importante efecto supresor sobre la expresión de leptina. Pueden observarse una pérdida de actividad hormonal y la alteración de la vía normal de señalización celular

  19. Principles of Plant-Microbe Interactions - Microbes for Sustainable Agriculture

    Science.gov (United States)

    Crops lack resistance to many soilborne pathogens and rely on antagonistic microbes recruited from the soil microbiome to protect their roots. Disease-suppressive soils, the best examples of microbial-based defense, are soils in which a pathogen does not establish or persist, establishes but causes ...

  20. ONSET: Automated foundational ontology selection and explanation

    CSIR Research Space (South Africa)

    Khan, Z

    2012-10-01

    Full Text Available It has been shown that using a foundational ontology for domain ontology development is beneficial in theory and practice. However, developers have difficulty with choosing the appropriate foundational ontology, and why. In order to solve...

  1. The Ontology for Biomedical Investigations.

    Science.gov (United States)

    Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H; Bug, Bill; Chibucos, Marcus C; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H; Schober, Daniel; Smith, Barry; Soldatova, Larisa N; Stoeckert, Christian J; Taylor, Chris F; Torniai, Carlo; Turner, Jessica A; Vita, Randi; Whetzel, Patricia L; Zheng, Jie

    2016-01-01

    The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed

  2. Ontology Based Model Transformation Infrastructure

    NARCIS (Netherlands)

    Göknil, Arda; Topaloglu, N.Y.

    2005-01-01

    Using MDA in ontology development has been investigated in several works recently. The mappings and transformations between the UML constructs and the OWL elements to develop ontologies are the main concern of these research projects. We propose another approach in order to achieve the collaboration

  3. Ontology through a Mindfulness Process

    Science.gov (United States)

    Bearance, Deborah; Holmes, Kimberley

    2015-01-01

    Traditionally, when ontology is taught in a graduate studies course on social research, there is a tendency for this concept to be examined through the process of lectures and readings. Such an approach often leaves graduate students to grapple with a personal embodiment of this concept and to comprehend how ontology can ground their research.…

  4. The foundational ontology library ROMULUS

    CSIR Research Space (South Africa)

    Khan, ZC

    2013-09-01

    Full Text Available . We present here a basic step in that direction with the Repository of Ontologies for MULtiple USes, ROMULUS, which is the first online library of machine-processable, modularised, aligned, and logic-based merged foundational ontologies. In addition...

  5. Tracking Changes during Ontology Evolution

    NARCIS (Netherlands)

    Noy, Natalya F.; Kunnatur, Sandhya; Klein, Michel; Musen, Mark A.

    2004-01-01

    As ontology development becomes a collaborative process, developers face the problem of maintaining versions of ontologies akin to maintaining versions of software code or versions of documents in large projects. Traditional versioning systems enable users to compare versions, examine changes, and

  6. PDON: Parkinson's disease ontology for representation and modeling of the Parkinson's disease knowledge domain.

    Science.gov (United States)

    Younesi, Erfan; Malhotra, Ashutosh; Gündel, Michaela; Scordis, Phil; Kodamullil, Alpha Tom; Page, Matt; Müller, Bernd; Springstubbe, Stephan; Wüllner, Ullrich; Scheller, Dieter; Hofmann-Apitius, Martin

    2015-09-22

    Despite the unprecedented and increasing amount of data, relatively little progress has been made in molecular characterization of mechanisms underlying Parkinson's disease. In the area of Parkinson's research, there is a pressing need to integrate various pieces of information into a meaningful context of presumed disease mechanism(s). Disease ontologies provide a novel means for organizing, integrating, and standardizing the knowledge domains specific to disease in a compact, formalized and computer-readable form and serve as a reference for knowledge exchange or systems modeling of disease mechanism. The Parkinson's disease ontology was built according to the life cycle of ontology building. Structural, functional, and expert evaluation of the ontology was performed to ensure the quality and usability of the ontology. A novelty metric has been introduced to measure the gain of new knowledge using the ontology. Finally, a cause-and-effect model was built around PINK1 and two gene expression studies from the Gene Expression Omnibus database were re-annotated to demonstrate the usability of the ontology. The Parkinson's disease ontology with a subclass-based taxonomic hierarchy covers the broad spectrum of major biomedical concepts from molecular to clinical features of the disease, and also reflects different views on disease features held by molecular biologists, clinicians and drug developers. The current version of the ontology contains 632 concepts, which are organized under nine views. The structural evaluation showed the balanced dispersion of concept classes throughout the ontology. The functional evaluation demonstrated that the ontology-driven literature search could gain novel knowledge not present in the reference Parkinson's knowledge map. The ontology was able to answer specific questions related to Parkinson's when evaluated by experts. Finally, the added value of the Parkinson's disease ontology is demonstrated by ontology-driven modeling of PINK1

  7. Identification of protein features encoded by alternative exons using Exon Ontology.

    Science.gov (United States)

    Tranchevent, Léon-Charles; Aubé, Fabien; Dulaurier, Louis; Benoit-Pilven, Clara; Rey, Amandine; Poret, Arnaud; Chautard, Emilie; Mortada, Hussein; Desmet, François-Olivier; Chakrama, Fatima Zahra; Moreno-Garcia, Maira Alejandra; Goillot, Evelyne; Janczarski, Stéphane; Mortreux, Franck; Bourgeois, Cyril F; Auboeuf, Didier

    2017-06-01

    Transcriptomic genome-wide analyses demonstrate massive variation of alternative splicing in many physiological and pathological situations. One major challenge is now to establish the biological contribution of alternative splicing variation in physiological- or pathological-associated cellular phenotypes. Toward this end, we developed a computational approach, named "Exon Ontology," based on terms corresponding to well-characterized protein features organized in an ontology tree. Exon Ontology is conceptually similar to Gene Ontology-based approaches but focuses on exon-encoded protein features instead of gene level functional annotations. Exon Ontology describes the protein features encoded by a selected list of exons and looks for potential Exon Ontology term enrichment. By applying this strategy to exons that are differentially spliced between epithelial and mesenchymal cells and after extensive experimental validation, we demonstrate that Exon Ontology provides support to discover specific protein features regulated by alternative splicing. We also show that Exon Ontology helps to unravel biological processes that depend on suites of coregulated alternative exons, as we uncovered a role of epithelial cell-enriched splicing factors in the AKT signaling pathway and of mesenchymal cell-enriched splicing factors in driving splicing events impacting on autophagy. Freely available on the web, Exon Ontology is the first computational resource that allows getting a quick insight into the protein features encoded by alternative exons and investigating whether coregulated exons contain the same biological information. © 2017 Tranchevent et al.; Published by Cold Spring Harbor Laboratory Press.

  8. Knowledge retrieval from PubMed abstracts and electronic medical records with the Multiple Sclerosis Ontology.

    Science.gov (United States)

    Malhotra, Ashutosh; Gündel, Michaela; Rajput, Abdul Mateen; Mevissen, Heinz-Theodor; Saiz, Albert; Pastor, Xavier; Lozano-Rubi, Raimundo; Martinez-Lapiscina, Elena H; Martinez-Lapsicina, Elena H; Zubizarreta, Irati; Mueller, Bernd; Kotelnikova, Ekaterina; Toldo, Luca; Hofmann-Apitius, Martin; Villoslada, Pablo

    2015-01-01

    In order to retrieve useful information from scientific literature and electronic medical records (EMR) we developed an ontology specific for Multiple Sclerosis (MS). The MS Ontology was created using scientific literature and expert review under the Protégé OWL environment. We developed a dictionary with semantic synonyms and translations to different languages for mining EMR. The MS Ontology was integrated with other ontologies and dictionaries (diseases/comorbidities, gene/protein, pathways, drug) into the text-mining tool SCAIView. We analyzed the EMRs from 624 patients with MS using the MS ontology dictionary in order to identify drug usage and comorbidities in MS. Testing competency questions and functional evaluation using F statistics further validated the usefulness of MS ontology. Validation of the lexicalized ontology by means of named entity recognition-based methods showed an adequate performance (F score = 0.73). The MS Ontology retrieved 80% of the genes associated with MS from scientific abstracts and identified additional pathways targeted by approved disease-modifying drugs (e.g. apoptosis pathways associated with mitoxantrone, rituximab and fingolimod). The analysis of the EMR from patients with MS identified current usage of disease modifying drugs and symptomatic therapy as well as comorbidities, which are in agreement with recent reports. The MS Ontology provides a semantic framework that is able to automatically extract information from both scientific literature and EMR from patients with MS, revealing new pathogenesis insights as well as new clinical information.

  9. The microbe-free plant: fact or artefact?

    Directory of Open Access Journals (Sweden)

    Laila P. Pamela Partida-Martinez

    2011-12-01

    Full Text Available Plant-microbe interactions are ubiquitous. Plants are often colonized by pathogens but even more commonly engaged in neutral or mutualistic interactions with microbes: below-ground microbial plant associates are mycorrhizal fungi, Rhizobia and rhizosphere bacteria, above-ground plant parts are colonized by bacterial and fungal endophytes and by microbes in the phyllosphere. We emphasize here that a completely microbe-free plant is an exotic exception rather than the biologically relevant rule. The complex interplay of such microbial communities with the host plant affects plant nutrition, growth rate, resistance to biotic and abiotic stress, and plant survival and distribution. The mechanisms involved reach from nutrient acquisition, the production of plant hormones or direct antibiosis to effects on host resistance genes or interactions at higher trophic levels. Plant-associated microbes are heterotrophic and cause costs to their host plant, whereas the benefits depend on the environment. Thus, the outcome of the interaction is highly context-dependent. Considering the microbe-free plant as the ‘normal’ or control stage significantly impairs research into important phenomena such as (1 phenotypic and epigenetic plasticity, (2 the ‘normal’ ecological outcome of a given interaction and (3 the evolution of plants. For the future, we suggest cultivation-independent screening methods using direct PCR from plant tissue of more than one fungal and bacterial gene to collect data on the true microbial diversity in wild plants. The patterns found could be correlated to host species and environmental conditions, in order to formulate testable hypotheses on the biological roles of plant endophytes in nature. Experimental approaches should compare different host-endophyte combinations under various environmental conditions and study at the genetic, transcriptional and physiological level the parameters that shift the interaction along the mutualism

  10. Logic and Ontology

    Directory of Open Access Journals (Sweden)

    Newton C. A. da Costa

    2002-12-01

    Full Text Available In view of the present state of development of non classical logic, especially of paraconsistent logic, a new stand regarding the relations between logic and ontology is defended In a parody of a dictum of Quine, my stand May be summarized as follows. To be is to be the value of a variable a specific language with a given underlying logic Yet my stand differs from Quine’s, because, among other reasons, I accept some first order heterodox logics as genuine alternatives to classical logic I also discuss some questions of non classical logic to substantiate my argument, and suggest that may position complements and extends some ideas advanced by L Apostel.

  11. Building a developmental toxicity ontology.

    Science.gov (United States)

    Baker, Nancy; Boobis, Alan; Burgoon, Lyle; Carney, Edward; Currie, Richard; Fritsche, Ellen; Knudsen, Thomas; Laffont, Madeleine; Piersma, Aldert H; Poole, Alan; Schneider, Steffen; Daston, George

    2018-04-03

    As more information is generated about modes of action for developmental toxicity and more data are generated using high-throughput and high-content technologies, it is becoming necessary to organize that information. This report discussed the need for a systematic representation of knowledge about developmental toxicity (i.e., an ontology) and proposes a method to build one based on knowledge of developmental biology and mode of action/ adverse outcome pathways in developmental toxicity. This report is the result of a consensus working group developing a plan to create an ontology for developmental toxicity that spans multiple levels of biological organization. This report provide a description of some of the challenges in building a developmental toxicity ontology and outlines a proposed methodology to meet those challenges. As the ontology is built on currently available web-based resources, a review of these resources is provided. Case studies on one of the most well-understood morphogens and developmental toxicants, retinoic acid, are presented as examples of how such an ontology might be developed. This report outlines an approach to construct a developmental toxicity ontology. Such an ontology will facilitate computer-based prediction of substances likely to induce human developmental toxicity. © 2018 Wiley Periodicals, Inc.

  12. There is no quantum ontology without classical ontology

    Energy Technology Data Exchange (ETDEWEB)

    Fink, Helmut [Institut fuer Theoretische Physik, Univ. Erlangen-Nuernberg (Germany)

    2011-07-01

    The relation between quantum physics and classical physics is still under debate. In his recent book ''Rational Reconstructions of Modern Physics'', Peter Mittelstaedt explores a route from classical to quantum mechanics by reduction and elimination of (some of) the ontological hypotheses underlying classical mechanics. While, according to Mittelstaedt, classical mechanics describes a fictitious world that does not exist in reality, he claims to achieve a universal quantum ontology that can be improved by incorporating unsharp properties and equipped with Planck's constant without any need to refer to classical concepts. In this talk, we argue that quantum ontology in Mittelstaedt's sense is not enough. Quantum ontology can never be universal as long as the difference between potential and real properties is not represented adequately. Quantum properties are potential, not (yet) real, be they sharp or unsharp. Hence, preparation and measurement presuppose classical concepts, even in quantum theory. We end up with a classical-quantum sandwich ontology, which is still less extravagant than Bohmian or many-worlds ontologies are.

  13. development of ontological knowledge representation

    African Journals Online (AJOL)

    Preferred Customer

    ABSTRACT. This paper presents the development of an ontological knowledge organization and .... intelligence in order to facilitate knowledge sharing and reuse of acquired knowledge (15). Soon, ..... Water Chemistry, AJCE, 1(2), 50-58. 25.

  14. A Mobile Army of Ontologies

    DEFF Research Database (Denmark)

    Juul, Jesper

    2015-01-01

    Presentation at the Ludo-ontologies panel. Do we need ludo-ontologies, and what are they? In this event several scholars of games and videogames discuss these questions from a variety of perspectives. What different game and videogame ontologies exist and could exist, and why they are important...... for game and videogame research? The round table is designed to promote ludo-ontological dialogue in order to make these questions visible and debated. A series of short presentations (approximately 10 minutes each) will be followed by an intense debate through freeform dialogue. After the industrial...... commercialization of games and videogames their study has shifted between approaches focused on players (ludic processes) and artifacts (ludic objects). Some attempts to analyze the relationship between the process and the object have occasionally been done in terms of ‘ontology’ (Zagal 2005; Leino 2010; Gualeni...

  15. Building a Chemical Ontology using Methontology and the Ontology Design Environment

    OpenAIRE

    Fernández López, Mariano; Gómez-Pérez, A.; Pazos Sierra, Alejandro; Pazos Sierra, Juan

    1999-01-01

    METHONTOLOGY PROVIDES GUIDELINES FOR SPECIFYING ONTOLOGIES AT THE KNOWLEDGE LEVEL, AS A SPECIFICATION OF A CONCEPTUALIZATION. ODE ENABLES ONTOLOGY CONSTRUCTION, COVERING THE ENTIRE LIFE CYCLE AND AUTOMATICALLY IMPLEMENTING ONTOLOGIES

  16. ``Force,'' ontology, and language

    Science.gov (United States)

    Brookes, David T.; Etkina, Eugenia

    2009-06-01

    We introduce a linguistic framework through which one can interpret systematically students’ understanding of and reasoning about force and motion. Some researchers have suggested that students have robust misconceptions or alternative frameworks grounded in everyday experience. Others have pointed out the inconsistency of students’ responses and presented a phenomenological explanation for what is observed, namely, knowledge in pieces. We wish to present a view that builds on and unifies aspects of this prior research. Our argument is that many students’ difficulties with force and motion are primarily due to a combination of linguistic and ontological difficulties. It is possible that students are primarily engaged in trying to define and categorize the meaning of the term “force” as spoken about by physicists. We found that this process of negotiation of meaning is remarkably similar to that engaged in by physicists in history. In this paper we will describe a study of the historical record that reveals an analogous process of meaning negotiation, spanning multiple centuries. Using methods from cognitive linguistics and systemic functional grammar, we will present an analysis of the force and motion literature, focusing on prior studies with interview data. We will then discuss the implications of our findings for physics instruction.

  17. NetCooperate: a network-based tool for inferring host-microbe and microbe-microbe cooperation

    OpenAIRE

    Levy, Roie; Carr, Rogan; Kreimer, Anat; Freilich, Shiri; Borenstein, Elhanan

    2015-01-01

    Background Host-microbe and microbe-microbe interactions are often governed by the complex exchange of metabolites. Such interactions play a key role in determining the way pathogenic and commensal species impact their host and in the assembly of complex microbial communities. Recently, several studies have demonstrated how such interactions are reflected in the organization of the metabolic networks of the interacting species, and introduced various graph theory-based methods to predict host...

  18. NetCooperate: a network-based tool for inferring host-microbe and microbe-microbe cooperation.

    Science.gov (United States)

    Levy, Roie; Carr, Rogan; Kreimer, Anat; Freilich, Shiri; Borenstein, Elhanan

    2015-05-17

    Host-microbe and microbe-microbe interactions are often governed by the complex exchange of metabolites. Such interactions play a key role in determining the way pathogenic and commensal species impact their host and in the assembly of complex microbial communities. Recently, several studies have demonstrated how such interactions are reflected in the organization of the metabolic networks of the interacting species, and introduced various graph theory-based methods to predict host-microbe and microbe-microbe interactions directly from network topology. Using these methods, such studies have revealed evolutionary and ecological processes that shape species interactions and community assembly, highlighting the potential of this reverse-ecology research paradigm. NetCooperate is a web-based tool and a software package for determining host-microbe and microbe-microbe cooperative potential. It specifically calculates two previously developed and validated metrics for species interaction: the Biosynthetic Support Score which quantifies the ability of a host species to supply the nutritional requirements of a parasitic or a commensal species, and the Metabolic Complementarity Index which quantifies the complementarity of a pair of microbial organisms' niches. NetCooperate takes as input a pair of metabolic networks, and returns the pairwise metrics as well as a list of potential syntrophic metabolic compounds. The Biosynthetic Support Score and Metabolic Complementarity Index provide insight into host-microbe and microbe-microbe metabolic interactions. NetCooperate determines these interaction indices from metabolic network topology, and can be used for small- or large-scale analyses. NetCooperate is provided as both a web-based tool and an open-source Python module; both are freely available online at http://elbo.gs.washington.edu/software_netcooperate.html.

  19. Use of the CIM Ontology

    Energy Technology Data Exchange (ETDEWEB)

    Neumann, Scott; Britton, Jay; Devos, Arnold N.; Widergren, Steven E.

    2006-02-08

    There are many uses for the Common Information Model (CIM), an ontology that is being standardized through Technical Committee 57 of the International Electrotechnical Commission (IEC TC57). The most common uses to date have included application modeling, information exchanges, information management and systems integration. As one should expect, there are many issues that become apparent when the CIM ontology is applied to any one use. Some of these issues are shortcomings within the current draft of the CIM, and others are a consequence of the different ways in which the CIM can be applied using different technologies. As the CIM ontology will and should evolve, there are several dangers that need to be recognized. One is overall consistency and impact upon applications when extending the CIM for a specific need. Another is that a tight coupling of the CIM to specific technologies could limit the value of the CIM in the longer term as an ontology, which becomes a larger issue over time as new technologies emerge. The integration of systems is one specific area of interest for application of the CIM ontology. This is an area dominated by the use of XML for the definition of messages. While this is certainly true when using Enterprise Application Integration (EAI) products, it is even more true with the movement towards the use of Web Services (WS), Service-Oriented Architectures (SOA) and Enterprise Service Buses (ESB) for integration. This general IT industry trend is consistent with trends seen within the IEC TC57 scope of power system management and associated information exchange. The challenge for TC57 is how to best leverage the CIM ontology using the various XML technologies and standards for integration. This paper will provide examples of how the CIM ontology is used and describe some specific issues that should be addressed within the CIM in order to increase its usefulness as an ontology. It will also describe some of the issues and challenges that will

  20. MicrobesOnline: an integrated portal for comparative and functional genomics

    Energy Technology Data Exchange (ETDEWEB)

    Dehal, Paramvir; Joachimiak, Marcin; Price, Morgan; Bates, John; Baumohl, Jason; Chivian, Dylan; Friedland, Greg; Huang, Kathleen; Keller, Keith; Novichkov, Pavel; Dubchak, Inna; Alm, Eric; Arkin, Adam

    2011-07-14

    Since 2003, MicrobesOnline (http://www.microbesonline.org) has been providing a community resource for comparative and functional genome analysis. The portal includes over 1000 complete genomes of bacteria, archaea and fungi and thousands of expression microarrays from diverse organisms ranging from model organisms such as Escherichia coli and Saccharomyces cerevisiae to environmental microbes such as Desulfovibrio vulgaris and Shewanella oneidensis. To assist in annotating genes and in reconstructing their evolutionary history, MicrobesOnline includes a comparative genome browser based on phylogenetic trees for every gene family as well as a species tree. To identify co-regulated genes, MicrobesOnline can search for genes based on their expression profile, and provides tools for identifying regulatory motifs and seeing if they are conserved. MicrobesOnline also includes fast phylogenetic profile searches, comparative views of metabolic pathways, operon predictions, a workbench for sequence analysis and integration with RegTransBase and other microbial genome resources. The next update of MicrobesOnline will contain significant new functionality, including comparative analysis of metagenomic sequence data. Programmatic access to the database, along with source code and documentation, is available at http://microbesonline.org/programmers.html.

  1. MicrobesOnline: an integrated portal for comparative and functional genomics

    Energy Technology Data Exchange (ETDEWEB)

    Dehal, Paramvir S.; Joachimiak, Marcin P.; Price, Morgan N.; Bates, John T.; Baumohl, Jason K.; Chivian, Dylan; Friedland, Greg D.; Huang, Katherine H.; Keller, Keith; Novichkov, Pavel S.; Dubchak, Inna L.; Alm, Eric J.; Arkin, Adam P.

    2009-09-17

    Since 2003, MicrobesOnline (http://www.microbesonline.org) has been providing a community resource for comparative and functional genome analysis. The portal includes over 1000 complete genomes of bacteria, archaea and fungi and thousands of expression microarrays from diverse organisms ranging from model organisms such as Escherichia coli and Saccharomyces cerevisiae to environmental microbes such as Desulfovibrio vulgaris and Shewanella oneidensis. To assist in annotating genes and in reconstructing their evolutionary history, MicrobesOnline includes a comparative genome browser based on phylogenetic trees for every gene family as well as a species tree. To identify co-regulated genes, MicrobesOnline can search for genes based on their expression profile, and provides tools for identifying regulatory motifs and seeing if they are conserved. MicrobesOnline also includes fast phylogenetic profile searches, comparative views of metabolic pathways, operon predictions, a workbench for sequence analysis and integration with RegTransBase and other microbial genome resources. The next update of MicrobesOnline will contain significant new functionality, including comparative analysis of metagenomic sequence data. Programmatic access to the database, along with source code and documentation, is available at http://microbesonline.org/programmers.html.

  2. Protein complex prediction in large ontology attributed protein-protein interaction networks.

    Science.gov (United States)

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

    2013-01-01

    Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.

  3. Toward semantic interoperability with linked foundational ontologies in ROMULUS

    CSIR Research Space (South Africa)

    Khan, ZC

    2013-06-01

    Full Text Available A purpose of a foundational ontology is to solve interoperability issues among ontologies. Many foundational ontologies have been developed, reintroducing the ontology interoperability problem. We address this with the new online foundational...

  4. Drug target ontology to classify and integrate drug discovery data.

    Science.gov (United States)

    Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande; Turner, John Paul; Vidovic, Dusica; Forlin, Michele; Koleti, Amar; Nguyen, Dac-Trung; Jensen, Lars Juhl; Guha, Rajarshi; Mathias, Stephen L; Ursu, Oleg; Stathias, Vasileios; Duan, Jianbin; Nabizadeh, Nooshin; Chung, Caty; Mader, Christopher; Visser, Ubbo; Yang, Jeremy J; Bologa, Cristian G; Oprea, Tudor I; Schürer, Stephan C

    2017-11-09

    model for druggable targets including various related information such as protein, gene, protein domain, protein structure, binding site, small molecule drug, mechanism of action, protein tissue localization, disease association, and many other types of information. DTO will further facilitate the otherwise challenging integration and formal linking to biological assays, phenotypes, disease models, drug poly-pharmacology, binding kinetics and many other processes, functions and qualities that are at the core of drug discovery. The first version of DTO is publically available via the website http://drugtargetontology.org/ , Github ( http://github.com/DrugTargetOntology/DTO ), and the NCBO Bioportal ( http://bioportal.bioontology.org/ontologies/DTO ). The long-term goal of DTO is to provide such an integrative framework and to populate the ontology with this information as a community resource.

  5. Complex Topographic Feature Ontology Patterns

    Science.gov (United States)

    Varanka, Dalia E.; Jerris, Thomas J.

    2015-01-01

    Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

  6. Geographic Ontologies, Gazetteers and Multilingualism

    Directory of Open Access Journals (Sweden)

    Robert Laurini

    2015-01-01

    Full Text Available Different languages imply different visions of space, so that terminologies are different in geographic ontologies. In addition to their geometric shapes, geographic features have names, sometimes different in diverse languages. In addition, the role of gazetteers, as dictionaries of place names (toponyms, is to maintain relations between place names and location. The scope of geographic information retrieval is to search for geographic information not against a database, but against the whole Internet: but the Internet stores information in different languages, and it is of paramount importance not to remain stuck to a unique language. In this paper, our first step is to clarify the links between geographic objects as computer representations of geographic features, ontologies and gazetteers designed in various languages. Then, we propose some inference rules for matching not only types, but also relations in geographic ontologies with the assistance of gazetteers.

  7. Ontology Matching with Semantic Verification.

    Science.gov (United States)

    Jean-Mary, Yves R; Shironoshita, E Patrick; Kabuka, Mansur R

    2009-09-01

    ASMOV (Automated Semantic Matching of Ontologies with Verification) is a novel algorithm that uses lexical and structural characteristics of two ontologies to iteratively calculate a similarity measure between them, derives an alignment, and then verifies it to ensure that it does not contain semantic inconsistencies. In this paper, we describe the ASMOV algorithm, and then present experimental results that measure its accuracy using the OAEI 2008 tests, and that evaluate its use with two different thesauri: WordNet, and the Unified Medical Language System (UMLS). These results show the increased accuracy obtained by combining lexical, structural and extensional matchers with semantic verification, and demonstrate the advantage of using a domain-specific thesaurus for the alignment of specialized ontologies.

  8. Cooperation and cheating in microbes

    Science.gov (United States)

    Gore, Jeff

    2011-03-01

    Understanding the cooperative and competitive dynamics within and between species is a central challenge in evolutionary biology. Microbial model systems represent a unique opportunity to experimentally test fundamental theories regarding the evolution of cooperative behaviors. In this talk I will describe our experiments probing cooperation in microbes. In particular, I will compare the cooperative growth of yeast in sucrose and the cooperative inactivation of antibiotics by bacteria. In both cases we find that cheater strains---which don't contribute to the public welfare---are able to take advantage of the cooperator strains. However, this ability of cheaters to out-compete cooperators occurs only when cheaters are present at low frequency, thus leading to steady-state coexistence. These microbial experiments provide fresh insight into the evolutionary origin of cooperation.

  9. An ontology approach to comparative phenomics in plants

    KAUST Repository

    Oellrich, Anika

    2015-02-25

    Background: Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and details tailored to investigators with different research objectives and backgrounds. Although phenotype comparisons across datasets have long been possible on a small scale, comprehensive queries and analyses that span a broad set of reference species, research disciplines, and knowledge domains continue to be severely limited by the absence of a common semantic framework. Results: We developed a workflow to curate and standardize existing phenotype datasets for six plant species, encompassing both model species and crop plants with established genetic resources. Our effort focused on mutant phenotypes associated with genes of known sequence in Arabidopsis thaliana (L.) Heynh. (Arabidopsis), Zea mays L. subsp. mays (maize), Medicago truncatula Gaertn. (barrel medic or Medicago), Oryza sativa L. (rice), Glycine max (L.) Merr. (soybean), and Solanum lycopersicum L. (tomato). We applied the same ontologies, annotation standards, formats, and best practices across all six species, thereby ensuring that the shared dataset could be used for cross-species querying and semantic similarity analyses. Curated phenotypes were first converted into a common format using taxonomically broad ontologies such as the Plant Ontology, Gene Ontology, and Phenotype and Trait Ontology. We then compared ontology-based phenotypic descriptions with an existing classification system for plant phenotypes and evaluated our semantic similarity dataset for its ability to enhance predictions of gene families, protein functions, and shared metabolic pathways that underlie informative plant phenotypes. Conclusions: The use of ontologies, annotation standards, shared formats, and best practices for cross-taxon phenotype data analyses represents a novel approach to plant phenomics

  10. An ontology approach to comparative phenomics in plants

    KAUST Repository

    Oellrich, Anika; Walls, Ramona L; Cannon, Ethalinda KS; Cannon, Steven B; Cooper, Laurel; Gardiner, Jack; Gkoutos, Georgios V; Harper, Lisa; He, Mingze; Hoehndorf, Robert; Jaiswal, Pankaj; Kalberer, Scott R; Lloyd, John P; Meinke, David; Menda, Naama; Moore, Laura; Nelson, Rex T; Pujar, Anuradha; Lawrence, Carolyn J; Huala, Eva

    2015-01-01

    Background: Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and details tailored to investigators with different research objectives and backgrounds. Although phenotype comparisons across datasets have long been possible on a small scale, comprehensive queries and analyses that span a broad set of reference species, research disciplines, and knowledge domains continue to be severely limited by the absence of a common semantic framework. Results: We developed a workflow to curate and standardize existing phenotype datasets for six plant species, encompassing both model species and crop plants with established genetic resources. Our effort focused on mutant phenotypes associated with genes of known sequence in Arabidopsis thaliana (L.) Heynh. (Arabidopsis), Zea mays L. subsp. mays (maize), Medicago truncatula Gaertn. (barrel medic or Medicago), Oryza sativa L. (rice), Glycine max (L.) Merr. (soybean), and Solanum lycopersicum L. (tomato). We applied the same ontologies, annotation standards, formats, and best practices across all six species, thereby ensuring that the shared dataset could be used for cross-species querying and semantic similarity analyses. Curated phenotypes were first converted into a common format using taxonomically broad ontologies such as the Plant Ontology, Gene Ontology, and Phenotype and Trait Ontology. We then compared ontology-based phenotypic descriptions with an existing classification system for plant phenotypes and evaluated our semantic similarity dataset for its ability to enhance predictions of gene families, protein functions, and shared metabolic pathways that underlie informative plant phenotypes. Conclusions: The use of ontologies, annotation standards, shared formats, and best practices for cross-taxon phenotype data analyses represents a novel approach to plant phenomics

  11. 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

  12. Inferring ontology graph structures using OWL reasoning

    KAUST Repository

    Rodriguez-Garcia, Miguel Angel; Hoehndorf, Robert

    2018-01-01

    ' semantic content remains a challenge.We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies

  13. Ontologies, Knowledge Bases and Knowledge Management

    National Research Council Canada - National Science Library

    Chalupsky, Hans

    2002-01-01

    ...) an application called Strategy Development Assistant (SDA) that uses that ontology. The JFACC ontology served as a basis for knowledge sharing among several applications in the domain of air campaign planning...

  14. Addressing issues in foundational ontology mediation

    CSIR Research Space (South Africa)

    Khan, ZC

    2013-09-01

    Full Text Available An approach in achieving semantic interoperability among heterogeneous systems is to offer infrastructure to assist with linking and integration using a foundational ontology. Due to the creation of multiple foundational ontologies, this also means...

  15. Technique for designing a domain ontology

    OpenAIRE

    Palagin, A. V.; Petrenko, N. G.; Malakhov, K. S.

    2018-01-01

    The article describes the technique for designing a domain ontology, shows the flowchart of algorithm design and example of constructing a fragment of the ontology of the subject area of Computer Science is considered.

  16. Platonic wholes and quantum ontology

    CERN Document Server

    Woszczek, Marek

    2015-01-01

    The subject of the book is a reconsideration of the internalistic model of composition of the Platonic type, more radical than traditional, post-Aristotelian externalistic compositionism, and its application in the field of the ontology of quantum theory. At the centre of quantum ontology is nonseparability. Quantum wholes are atemporal wholes governed by internalistic logic and they are primitive, global physical entities, requiring an extreme relativization of the fundamental notions of mechanics. That ensures quantum theory to be fully consistent with the relativistic causal structure, with

  17. Multimedia ontology representation and applications

    CERN Document Server

    Chaudhury, Santanu; Ghosh, Hiranmay

    2015-01-01

    The result of more than 15 years of collective research, Multimedia Ontology: Representation and Applications provides a theoretical foundation for understanding the nature of media data and the principles involved in its interpretation. The book presents a unified approach to recent advances in multimedia and explains how a multimedia ontology can fill the semantic gap between concepts and the media world. It relays real-life examples of implementations in different domains to illustrate how this gap can be filled.The book contains information that helps with building semantic, content-based

  18. Root justifications for ontology repair

    CSIR Research Space (South Africa)

    Moodley, K

    2011-08-01

    Full Text Available stream_source_info Moodley_2011.pdf.txt stream_content_type text/plain stream_size 32328 Content-Encoding ISO-8859-1 stream_name Moodley_2011.pdf.txt Content-Type text/plain; charset=ISO-8859-1 Root Justi cations... the ontology, based on the no- tion of root justi cations [8, 9]. In Section 5, we discuss the implementation of a Prot eg e3 plugin which demonstrates our approach to ontology repair. In this section we also discuss some experimental results comparing...

  19. Towards ontology based search and knowledgesharing using domain ontologies

    DEFF Research Database (Denmark)

    Zambach, Sine

    verbs for relations in the ontology modeling. For this work we use frequency lists from a biomedical text corpus of different genres as well as a study of the relations used in other biomedical text mining tools. In addition, we discuss how these relations can be used in broarder perspective....

  20. An Ontology for Knowledge Representation and Applications

    OpenAIRE

    Nhon Do

    2008-01-01

    Ontology is a terminology which is used in artificial intelligence with different meanings. Ontology researching has an important role in computer science and practical applications, especially distributed knowledge systems. In this paper we present an ontology which is called Computational Object Knowledge Base Ontology. It has been used in designing some knowledge base systems for solving problems such as the system that supports studying knowledge and solving analytic ...

  1. On Algebraic Spectrum of Ontology Evaluation

    OpenAIRE

    Adekoya Adebayo Felix; kinwale Adio Taofiki; Sofoluwe Adetokunbo

    2011-01-01

    Ontology evaluation remains an important open problem in the area of its application. The ontology structure evaluation framework for benchmarking the internal graph structures was proposed. The framework was used in transport and biochemical ontology. The corresponding adjacency, incidence matrices and other structural properties due to the class hierarchical structure of the transport and biochemical ontology were computed using MATLAB. The results showed that the choice of suitable choice ...

  2. BiNChE: a web tool and library for chemical enrichment analysis based on the ChEBI ontology.

    Science.gov (United States)

    Moreno, Pablo; Beisken, Stephan; Harsha, Bhavana; Muthukrishnan, Venkatesh; Tudose, Ilinca; Dekker, Adriano; Dornfeldt, Stefanie; Taruttis, Franziska; Grosse, Ivo; Hastings, Janna; Neumann, Steffen; Steinbeck, Christoph

    2015-02-21

    Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein sets annotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis. We describe BiNChE, an enrichment analysis tool for small molecules based on the ChEBI Ontology. BiNChE displays an interactive graph that can be exported as a high-resolution image or in network formats. The tool provides plain, weighted and fragment analysis based on either the ChEBI Role Ontology or the ChEBI Structural Ontology. BiNChE aids in the exploration of large sets of small molecules produced within Metabolomics or other Systems Biology research contexts. The open-source tool provides easy and highly interactive web access to enrichment analysis with the ChEBI ontology tool and is additionally available as a standalone library.

  3. An ontological approach to domain engineering

    NARCIS (Netherlands)

    Falbo, R.A.; Guizzardi, G.; Duarte, K.

    2002-01-01

    Domain engineering aims to support systematic reuse, focusing on modeling common knowledge in a problem domain. Ontologies have also been pointed as holding great promise for software reuse. In this paper, we present ODE (Ontology-based Domain Engineering), an ontological approach for domain

  4. Aspects of ontology visualization and integration

    NARCIS (Netherlands)

    Dmitrieva, Joelia Borisovna

    2011-01-01

    In this thesis we will describe and discuss methodologies for ontology visualization and integration. Two visualization methods will be elaborated. In one method the ontology is visualized with the node-link technique, and with the other method the ontology is visualized with the containment

  5. Alignment of ICNP? 2.0 Ontology and a proposed INCP? Brazilian Ontology1

    OpenAIRE

    Carvalho, Carina Maris Gaspar; Cubas, Marcia Regina; Malucelli, Andreia; da N?brega, Maria Miriam Lima

    2014-01-01

    OBJECTIVE: to align the International Classification for Nursing Practice (ICNP®) Version 2.0 ontology and a proposed INCP® Brazilian Ontology.METHOD: document-based, exploratory and descriptive study, the empirical basis of which was provided by the ICNP® 2.0 Ontology and the INCP® Brazilian Ontology. The ontology alignment was performed using a computer tool with algorithms to identify correspondences between concepts, which were organized and analyzed according to their presence or absence...

  6. CLO : The cell line ontology

    NARCIS (Netherlands)

    Sarntivijai, Sirarat; Lin, Yu; Xiang, Zuoshuang; Meehan, Terrence F.; Diehl, Alexander D.; Vempati, Uma D.; Schuerer, Stephan C.; Pang, Chao; Malone, James; Parkinson, Helen; Liu, Yue; Takatsuki, Terue; Saijo, Kaoru; Masuya, Hiroshi; Nakamura, Yukio; Brush, Matthew H.; Haendel, Melissa A.; Zheng, Jie; Stoeckert, Christian J.; Peters, Bjoern; Mungall, Christopher J.; Carey, Thomas E.; States, David J.; Athey, Brian D.; He, Yongqun

    2014-01-01

    Background: Cell lines have been widely used in biomedical research. The community-based Cell Line Ontology (CLO) is a member of the OBO Foundry library that covers the domain of cell lines. Since its publication two years ago, significant updates have been made, including new groups joining the CLO

  7. Emotion Education without Ontological Commitment?

    Science.gov (United States)

    Kristjansson, Kristjan

    2010-01-01

    Emotion education is enjoying new-found popularity. This paper explores the "cosy consensus" that seems to have developed in education circles, according to which approaches to emotion education are immune from metaethical considerations such as contrasting rationalist and sentimentalist views about the moral ontology of emotions. I spell out five…

  8. Quantum physics and relational ontology

    Energy Technology Data Exchange (ETDEWEB)

    Cordovil, Joao [Center of Philosophy of Sciences of University of Lisbon (Portugal)

    2013-07-01

    The discovery of the quantum domain of reality put a serious ontological challenge, a challenge that is still well present in the recent developments of Quantum Physics. Physics was conceived from an atomistic conception of the world, reducing it, in all its diversity, to two types of entities: simple, individual and immutable entities (atoms, in metaphysical sense) and composite entities, resulting solely from combinations. Linear combinations, additive, indifferent to the structure or to the context. However, the discovery of wave-particle dualism and the developments in Quantum Field Theories and in Quantum Nonlinear Physical, showed that quantum entities are not, in metaphysical sense, neither simple, nor merely the result of linear (or additive) combinations. In other words, the ontological foundations of Physics revealed as inadequate to account for the nature of quantum entities. Then a fundamental challenge arises: How to think the ontic nature of these entities? In my view, this challenge appeals to a relational and dynamist ontology of physical entities. This is the central hypothesis of this communication. In this sense, this communication has two main intentions: 1) positively characterize this relational and dynamist ontology; 2) show some elements of its metaphysical suitability to contemporary Quantum Physics.

  9. Ontological problems of contemporary linguistics

    Directory of Open Access Journals (Sweden)

    А В Бондаренко

    2009-03-01

    Full Text Available The article studies linguistic ontology problems such as evolution of essential-existential views of language, interrelation within Being-Language-Man triad, linguistics gnosiological principles, language essence localization, and «expression» as language metalinguistic unit as well as architectonics of language personality et alia.

  10. An ontological approach to logistics

    NARCIS (Netherlands)

    Daniele, L.M.; Ferreira Pires, Luis; Zelm, M.; van Sinderen, Marten J.; Doumeingts, G.

    2013-01-01

    In today’s global market, the competitiveness of enterprises is strongly dictated by their ability to collaborate with other enterprises. Ontologies enable common understanding of concepts and have been acknowledged as a powerful means to foster collaboration, both within the boundaries of an

  11. Acetaldehyde production by major oral microbes.

    Science.gov (United States)

    Moritani, K; Takeshita, T; Shibata, Y; Ninomiya, T; Kiyohara, Y; Yamashita, Y

    2015-09-01

    To assess acetaldehyde (ACH) production by bacteria constituting the oral microbiota and the inhibitory effects of sugar alcohols on ACH production. The predominant bacterial components of the salivary microbiota of 166 orally healthy subjects were determined by barcoded pyrosequencing analysis of the 16S rRNA gene. Bacterial ACH production from ethanol or glucose was measured using gas chromatography. In addition, inhibition by four sugars and five sugar alcohols of ACH production was assayed. Forty-one species from 16 genera were selected as predominant and prevalent bacteria based on the following criteria: identification in ≥95% of the subjects, ≥1% of mean relative abundance or ≥5% of maximum relative abundance. All Neisseria species tested produced conspicuous amounts of ACH from ethanol, as did Rothia mucilaginosa, Streptococcus mitis and Prevotella histicola exhibited the ability to produce ACH. In addition, xylitol and sorbitol inhibited ACH production by Neisseria mucosa by more than 90%. The oral microbiota of orally healthy subjects comprises considerable amounts of bacteria possessing the ability to produce ACH, an oral carcinogen. Consumption of sugar alcohols may regulate ACH production by oral microbes. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  12. Flowers and Wild Megachilid Bees Share Microbes.

    Science.gov (United States)

    McFrederick, Quinn S; Thomas, Jason M; Neff, John L; Vuong, Hoang Q; Russell, Kaleigh A; Hale, Amanda R; Mueller, Ulrich G

    2017-01-01

    Transmission pathways have fundamental influence on microbial symbiont persistence and evolution. For example, the core gut microbiome of honey bees is transmitted socially and via hive surfaces, but some non-core bacteria associated with honey bees are also found on flowers, and these bacteria may therefore be transmitted indirectly between bees via flowers. Here, we test whether multiple flower and wild megachilid bee species share microbes, which would suggest that flowers may act as hubs of microbial transmission. We sampled the microbiomes of flowers (either bagged to exclude bees or open to allow bee visitation), adults, and larvae of seven megachilid bee species and their pollen provisions. We found a Lactobacillus operational taxonomic unit (OTU) in all samples but in the highest relative and absolute abundances in adult and larval bee guts and pollen provisions. The presence of the same bacterial types in open and bagged flowers, pollen provisions, and bees supports the hypothesis that flowers act as hubs of transmission of these bacteria between bees. The presence of bee-associated bacteria in flowers that have not been visited by bees suggests that these bacteria may also be transmitted to flowers via plant surfaces, the air, or minute insect vectors such as thrips. Phylogenetic analyses of nearly full-length 16S rRNA gene sequences indicated that the Lactobacillus OTU dominating in flower- and megachilid-associated microbiomes is monophyletic, and we propose the name Lactobacillus micheneri sp. nov. for this bacterium.

  13. Gradient Learning Algorithms for Ontology Computing

    Science.gov (United States)

    Gao, Wei; Zhu, Linli

    2014-01-01

    The gradient learning model has been raising great attention in view of its promising perspectives for applications in statistics, data dimensionality reducing, and other specific fields. In this paper, we raise a new gradient learning model for ontology similarity measuring and ontology mapping in multidividing setting. The sample error in this setting is given by virtue of the hypothesis space and the trick of ontology dividing operator. Finally, two experiments presented on plant and humanoid robotics field verify the efficiency of the new computation model for ontology similarity measure and ontology mapping applications in multidividing setting. PMID:25530752

  14. Gradient Learning Algorithms for Ontology Computing

    Directory of Open Access Journals (Sweden)

    Wei Gao

    2014-01-01

    Full Text Available The gradient learning model has been raising great attention in view of its promising perspectives for applications in statistics, data dimensionality reducing, and other specific fields. In this paper, we raise a new gradient learning model for ontology similarity measuring and ontology mapping in multidividing setting. The sample error in this setting is given by virtue of the hypothesis space and the trick of ontology dividing operator. Finally, two experiments presented on plant and humanoid robotics field verify the efficiency of the new computation model for ontology similarity measure and ontology mapping applications in multidividing setting.

  15. History Matters: Incremental Ontology Reasoning Using Modules

    Science.gov (United States)

    Cuenca Grau, Bernardo; Halaschek-Wiener, Christian; Kazakov, Yevgeny

    The development of ontologies involves continuous but relatively small modifications. Existing ontology reasoners, however, do not take advantage of the similarities between different versions of an ontology. In this paper, we propose a technique for incremental reasoning—that is, reasoning that reuses information obtained from previous versions of an ontology—based on the notion of a module. Our technique does not depend on a particular reasoning calculus and thus can be used in combination with any reasoner. We have applied our results to incremental classification of OWL DL ontologies and found significant improvement over regular classification time on a set of real-world ontologies.

  16. The MICROBE Project, A Report from the Interagency Working Group on Microbial Genomics

    Science.gov (United States)

    2001-01-01

    functional genomics tools (gene chips, technologies, etc.), comparative genomics, proteomics tools, novel culture techniques, in situ analyses, and...interested in supporting microarray/chip development for gene expression analysis for agricultural microbes, bioinformatics, and proteomics , and the...including one fungus ) in various stages of progress. The closely integrated Natural and Accelerated Bioremediation Research Program in the Office of

  17. Biomedical word sense disambiguation with ontologies and metadata: automation meets accuracy

    Directory of Open Access Journals (Sweden)

    Hakenberg Jörg

    2009-01-01

    Full Text Available Abstract Background Ontology term labels can be ambiguous and have multiple senses. While this is no problem for human annotators, it is a challenge to automated methods, which identify ontology terms in text. Classical approaches to word sense disambiguation use co-occurring words or terms. However, most treat ontologies as simple terminologies, without making use of the ontology structure or the semantic similarity between terms. Another useful source of information for disambiguation are metadata. Here, we systematically compare three approaches to word sense disambiguation, which use ontologies and metadata, respectively. Results The 'Closest Sense' method assumes that the ontology defines multiple senses of the term. It computes the shortest path of co-occurring terms in the document to one of these senses. The 'Term Cooc' method defines a log-odds ratio for co-occurring terms including co-occurrences inferred from the ontology structure. The 'MetaData' approach trains a classifier on metadata. It does not require any ontology, but requires training data, which the other methods do not. To evaluate these approaches we defined a manually curated training corpus of 2600 documents for seven ambiguous terms from the Gene Ontology and MeSH. All approaches over all conditions achieve 80% success rate on average. The 'MetaData' approach performed best with 96%, when trained on high-quality data. Its performance deteriorates as quality of the training data decreases. The 'Term Cooc' approach performs better on Gene Ontology (92% success than on MeSH (73% success as MeSH is not a strict is-a/part-of, but rather a loose is-related-to hierarchy. The 'Closest Sense' approach achieves on average 80% success rate. Conclusion Metadata is valuable for disambiguation, but requires high quality training data. Closest Sense requires no training, but a large, consistently modelled ontology, which are two opposing conditions. Term Cooc achieves greater 90

  18. Building a biomedical ontology recommender web service

    Directory of Open Access Journals (Sweden)

    Jonquet Clement

    2010-06-01

    Full Text Available Abstract Background Researchers in biomedical informatics use ontologies and terminologies to annotate their data in order to facilitate data integration and translational discoveries. As the use of ontologies for annotation of biomedical datasets has risen, a common challenge is to identify ontologies that are best suited to annotating specific datasets. The number and variety of biomedical ontologies is large, and it is cumbersome for a researcher to figure out which ontology to use. Methods We present the Biomedical Ontology Recommender web service. The system uses textual metadata or a set of keywords describing a domain of interest and suggests appropriate ontologies for annotating or representing the data. The service makes a decision based on three criteria. The first one is coverage, or the ontologies that provide most terms covering the input text. The second is connectivity, or the ontologies that are most often mapped to by other ontologies. The final criterion is size, or the number of concepts in the ontologies. The service scores the ontologies as a function of scores of the annotations created using the National Center for Biomedical Ontology (NCBO Annotator web service. We used all the ontologies from the UMLS Metathesaurus and the NCBO BioPortal. Results We compare and contrast our Recommender by an exhaustive functional comparison to previously published efforts. We evaluate and discuss the results of several recommendation heuristics in the context of three real world use cases. The best recommendations heuristics, rated ‘very relevant’ by expert evaluators, are the ones based on coverage and connectivity criteria. The Recommender service (alpha version is available to the community and is embedded into BioPortal.

  19. Alignment of ICNP® 2.0 ontology and a proposed INCP® Brazilian ontology.

    Science.gov (United States)

    Carvalho, Carina Maris Gaspar; Cubas, Marcia Regina; Malucelli, Andreia; Nóbrega, Maria Miriam Lima da

    2014-01-01

    to align the International Classification for Nursing Practice (ICNP®) Version 2.0 ontology and a proposed INCP® Brazilian Ontology. document-based, exploratory and descriptive study, the empirical basis of which was provided by the ICNP® 2.0 Ontology and the INCP® Brazilian Ontology. The ontology alignment was performed using a computer tool with algorithms to identify correspondences between concepts, which were organized and analyzed according to their presence or absence, their names, and their sibling, parent, and child classes. there were 2,682 concepts present in the ICNP® 2.0 Ontology that were missing in the Brazilian Ontology; 717 concepts present in the Brazilian Ontology were missing in the ICNP® 2.0 Ontology; and there were 215 pairs of matching concepts. it is believed that the correspondences identified in this study might contribute to the interoperability between the representations of nursing practice elements in ICNP®, thus allowing the standardization of nursing records based on this classification system.

  20. The MGED Ontology: A Framework for Describing Functional Genomics Experiments

    OpenAIRE

    Stoeckert, Christian J.; Parkinson, Helen

    2003-01-01

    The Microarray Gene Expression Data (MGED) society was formed with an initial focus on experiments involving microarray technology. Despite the diversity of applications, there are common concepts used and a common need to capture experimental information in a standardized manner. In building the MGED ontology, it was recognized that it would be impractical to cover all the different types of experiments on all the different types of organisms by listing and defining all the types of organism...

  1. Ontological realism: A methodology for coordinated evolution of scientific ontologies.

    Science.gov (United States)

    Smith, Barry; Ceusters, Werner

    2010-11-15

    Since 2002 we have been testing and refining a methodology for ontology development that is now being used by multiple groups of researchers in different life science domains. Gary Merrill, in a recent paper in this journal, describes some of the reasons why this methodology has been found attractive by researchers in the biological and biomedical sciences. At the same time he assails the methodology on philosophical grounds, focusing specifically on our recommendation that ontologies developed for scientific purposes should be constructed in such a way that their terms are seen as referring to what we call universals or types in reality. As we show, Merrill's critique is of little relevance to the success of our realist project, since it not only reveals no actual errors in our work but also criticizes views on universals that we do not in fact hold. However, it nonetheless provides us with a valuable opportunity to clarify the realist methodology, and to show how some of its principles are being applied, especially within the framework of the OBO (Open Biomedical Ontologies) Foundry initiative.

  2. Effects of microbes on the immune system

    National Research Council Canada - National Science Library

    Fujinami, Robert S; Cunningham, Madeleine W

    2000-01-01

    .... The book synthesizes recent discoveries on the various mechanisms by which microbes subvert the immune response and on the role of these immunologic mechanisms in the pathogenesis of infectious diseases...

  3. A global census of marine microbes

    Digital Repository Service at National Institute of Oceanography (India)

    Amaral-Zettler, L.; Artigas, L.F.; Baross, J.; LokaBharathi, P.A; Boetius, A; Chandramohan, D.; Herndl, G.; Kogure, K.; Neal, P.; Pedros-Alio, C.; Ramette, A; Schouten, S.; Stal, L.; Thessen, A; De Leeuw, J.; Sogin, M.

    In this chapter we provide a brief history of what is known about marine microbial diversity, summarize our achievements in performing a global census of marine microbes, and reflect on the questions and priorities for the future of the marine...

  4. Microbes safely, effectively bioremediate oil field pits

    International Nuclear Information System (INIS)

    Shaw, B.; Block, C.S.; Mills, C.H.

    1995-01-01

    Natural and augmented bioremediation provides a safe, environmental, fast, and effective solution for removing hydrocarbon stains from soil. In 1992, Amoco sponsored a study with six bioremediation companies, which evaluated 14 different techniques. From this study, Amoco continued using Environmental Protection Co.'s (EPC) microbes for bioremediating more than 145 sites near Farmington, NM. EPC's microbes proved effective on various types of hydrocarbon molecules found in petroleum stained soils from heavy crude and paraffin to volatiles such as BTEX (benzene, toluene, ethylbenzene, xylene) compounds. Controlled laboratory tests have shown that these microbes can digest the hydrocarbon molecules with or without free oxygen present. It is believed that this adaptation gives these microbes their resilience. The paper describes the bioremediation process, environmental advantages, in situ and ex situ bioremediation, goals of bioremediation, temperature effects, time, cost, and example sites that were treated

  5. Formal Ontologies and Uncertainty. In Geographical Knowledge

    Directory of Open Access Journals (Sweden)

    Matteo Caglioni

    2014-05-01

    Full Text Available Formal ontologies have proved to be a very useful tool to manage interoperability among data, systems and knowledge. In this paper we will show how formal ontologies can evolve from a crisp, deterministic framework (ontologies of hard knowledge to new probabilistic, fuzzy or possibilistic frameworks (ontologies of soft knowledge. This can considerably enlarge the application potential of formal ontologies in geographic analysis and planning, where soft knowledge is intrinsically linked to the complexity of the phenomena under study.  The paper briefly presents these new uncertainty-based formal ontologies. It then highlights how ontologies are formal tools to define both concepts and relations among concepts. An example from the domain of urban geography finally shows how the cause-to-effect relation between household preferences and urban sprawl can be encoded within a crisp, a probabilistic and a possibilistic ontology, respectively. The ontology formalism will also determine the kind of reasoning that can be developed from available knowledge. Uncertain ontologies can be seen as the preliminary phase of more complex uncertainty-based models. The advantages of moving to uncertainty-based models is evident: whether it is in the analysis of geographic space or in decision support for planning, reasoning on geographic space is almost always reasoning with uncertain knowledge of geographic phenomena.

  6. Knowledge Portals: Ontologies at Work

    OpenAIRE

    Staab, Steffen; Maedche, Alexander

    2001-01-01

    Knowledge portals provide views onto domain-specific information on the World Wide Web, thus helping their users find relevant, domain-specific information. The construction of intelligent access and the contribution of information to knowledge portals, however, remained an ad hoc task, requiring extensive manual editing and maintenance by the knowledge portal providers. To diminish these efforts, we use ontologies as a conceptual backbone for providing, accessing, and structuring information...

  7. The Christological Ontology of Reason

    DEFF Research Database (Denmark)

    Nissen, Ulrik Becker

    2006-01-01

    Taking the startingpoint in an assertion of an ambiguity in the Lutheran tradition’s assessment of reason, the essay argues that the Kantian unreserved confidence in reason is criticised in Bonhoeffer. Based upon a Christological understanding of reason, Bonhoeffer endorses a view of reason which...... is treated in the essay. Here it is argued that Bonhoeffer may be appropriated in attempting to outline a Christological ontology of reason holding essential implications for the sources and conditions of public discourse....

  8. Emotion Ontology for Context Awareness

    OpenAIRE

    Berthelon , Franck; Sander , Peter

    2013-01-01

    International audience; We present an emotion ontology for describing and reasoning on emotion context in order to improve emotion detection based on bodily expression. We incorporate context into the two-factor theory of emotion (bodily reaction plus cognitive input) and demonstrate the importance of context in the emotion experience. In attempting to determine emotion felt by another person, the bodily expresson of their emotion is the only evidence directly available, eg, ''John looks angr...

  9. Towards an Ontology of Software

    OpenAIRE

    Wang, Xiaowei

    2016-01-01

    Software is permeating every aspect of our personal and social life. And yet, the cluster of concepts around the notion of software, such as the notions of a software product, software requirements, software specifications, are still poorly understood with no consensus on the horizon. For many, software is just code, something intangible best defined in contrast with hardware, but it is not particularly illuminating. This erroneous notion, software is just code, presents both in the ontology ...

  10. Ontology Maintenance using Textual Analysis

    Directory of Open Access Journals (Sweden)

    Yassine Gargouri

    2003-10-01

    Full Text Available Ontologies are continuously confronted to evolution problem. Due to the complexity of the changes to be made, a maintenance process, at least a semi-automatic one, is more and more necessary to facilitate this task and to ensure its reliability. In this paper, we propose a maintenance ontology model for a domain, whose originality is to be language independent and based on a sequence of text processing in order to extract highly related terms from corpus. Initially, we deploy the document classification technique using GRAMEXCO to generate classes of texts segments having a similar information type and identify their shared lexicon, agreed as highly related to a unique topic. This technique allows a first general and robust exploration of the corpus. Further, we apply the Latent Semantic Indexing method to extract from this shared lexicon, the most associated terms that has to be seriously considered by an expert to eventually confirm their relevance and thus updating the current ontology. Finally, we show how the complementarity between these two techniques, based on cognitive foundation, constitutes a powerful refinement process.

  11. Database Concepts in a Domain Ontology

    Directory of Open Access Journals (Sweden)

    Gorskis Henrihs

    2017-12-01

    Full Text Available There are multiple approaches for mapping from a domain ontology to a database in the task of ontology-based data access. For that purpose, external mapping documents are most commonly used. These documents describe how the data necessary for the description of ontology individuals and other values, are to be obtained from the database. The present paper investigates the use of special database concepts. These concepts are not separated from the domain ontology; they are mixed with domain concepts to form a combined application ontology. By creating natural relationships between database concepts and domain concepts, mapping can be implemented more easily and with a specific purpose. The paper also investigates how the use of such database concepts in addition to domain concepts impacts ontology building and data retrieval.

  12. Ontology-aided Data Fusion (Invited)

    Science.gov (United States)

    Raskin, R.

    2009-12-01

    An ontology provides semantic descriptions that are analogous to those in a dictionary, but are readable by both computers and humans. A data or service is semantically annotated when it is formally associated with elements of an ontology. The ESIP Federation Semantic Web Cluster has developed a set of ontologies to describe datatypes and data services that can be used to support automated data fusion. The service ontology includes descriptors of the service function, its inputs/outputs, and its invocation method. The datatype descriptors resemble typical metadata fields (data format, data model, data structure, originator, etc.) augmented with descriptions of the meaning of the data. These ontologies, in combination with the SWEET science ontology, enable a registered data fusion service to be chained together and implemented that is scientifically meaningful based on machine understanding of the associated data and services. This presentation describes initial results and experiences in automated data fusion.

  13. Environmental restoration using plant-microbe bioaugmentation

    International Nuclear Information System (INIS)

    Kingsley, M.T.; Fredrickson, J.K.; Metting, F.B.; Seidler, R.J.

    1993-04-01

    Land farming, for the purpose of bioremediation, refers traditionally to the spreading of contaminated soil, sediments, or other material over land; mechanically mixing it; incorporating various amendments, such as fertilizer or mulch; and sometimes inoculating with degradative microorganisms. Populations of bacteria added to soils often decline rapidly and become metabolically inactive. To efficiently degrade contaminants, microorganisms must be metabolically active. Thus, a significant obstacle to the successful use of microorganisms for environmental applications is their long-term survival and the expression of their degradative genes in situ. Rhizosphere microorganisms are known to be more metabolically active than those in bulk soil, because they obtain carbon and energy from root exudates and decaying root matter. Rhizosphere populations are also more abundant, often containing 10 8 or more culturable bacteria per gram of soil, and bacterial populations on the rhizoplane can exceed 10 9 /g root. Many of the critical parameters that influence the competitive ability of rhizosphere bacteria have not been identified, but microorganisms have frequently been introduced into soil (bioaugmentation) as part of routine or novel agronomic practices. However, the use of rhizosphere bacteria and their in situ stimulation by plant roots for degrading organic contaminants has received little attention. Published studies have demonstrated the feasibility of using rhizobacteria (Pseudomonas putida) for the rapid removal of chlorinated pesticides from contaminated soil, and to promote germination of radish seeds in the presence of otherwise phytotoxic levels of the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D), and phenoxyacetic acid (PAA). The present investigation was undertaken to determine if these strains (Pseudomonas putida PPO301/pRO101 and PPO301/pRO103) could be used to bioremediate 2,4-D-amended soil via plant-microbe bioaugmentation

  14. An Ontological Architecture for Orbital Debris Data

    OpenAIRE

    Rovetto, Robert J.

    2017-01-01

    The orbital debris problem presents an opportunity for inter-agency and international cooperation toward the mutually beneficial goals of debris prevention, mitigation, remediation, and improved space situational awareness (SSA). Achieving these goals requires sharing orbital debris and other SSA data. Toward this, I present an ontological architecture for the orbital debris domain, taking steps in the creation of an orbital debris ontology (ODO). The purpose of this ontological system is to ...

  15. Versioning System for Distributed Ontology Development

    Science.gov (United States)

    2016-03-15

    Framework for Grid Computing and Semantic Web Services,” Trust Management, Springer Berlin Heidelberg (2004), pp. 16−26. [TIME] W3C, “Time Ontology in...Distributed Ontology Development S.K. Damodaran 15 March 2016 This material is based on work supported by the Assistant Secretary of Defense for...Distributed Ontology Development S.K. Damodaran Formerly Group 59 15 March 2016 Massachusetts Institute of Technology Lincoln Laboratory

  16. Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns.

    Science.gov (United States)

    Xiang, Zuoshuang; Zheng, Jie; Lin, Yu; He, Yongqun

    2015-01-01

    It is time-consuming to build an ontology with many terms and axioms. Thus it is desired to automate the process of ontology development. Ontology Design Patterns (ODPs) provide a reusable solution to solve a recurrent modeling problem in the context of ontology engineering. Because ontology terms often follow specific ODPs, the Ontology for Biomedical Investigations (OBI) developers proposed a Quick Term Templates (QTTs) process targeted at generating new ontology classes following the same pattern, using term templates in a spreadsheet format. Inspired by the ODPs and QTTs, the Ontorat web application is developed to automatically generate new ontology terms, annotations of terms, and logical axioms based on a specific ODP(s). The inputs of an Ontorat execution include axiom expression settings, an input data file, ID generation settings, and a target ontology (optional). The axiom expression settings can be saved as a predesigned Ontorat setting format text file for reuse. The input data file is generated based on a template file created by a specific ODP (text or Excel format). Ontorat is an efficient tool for ontology expansion. Different use cases are described. For example, Ontorat was applied to automatically generate over 1,000 Japan RIKEN cell line cell terms with both logical axioms and rich annotation axioms in the Cell Line Ontology (CLO). Approximately 800 licensed animal vaccines were represented and annotated in the Vaccine Ontology (VO) by Ontorat. The OBI team used Ontorat to add assay and device terms required by ENCODE project. Ontorat was also used to add missing annotations to all existing Biobank specific terms in the Biobank Ontology. A collection of ODPs and templates with examples are provided on the Ontorat website and can be reused to facilitate ontology development. With ever increasing ontology development and applications, Ontorat provides a timely platform for generating and annotating a large number of ontology terms by following

  17. Towards Process-Ontology: A Critical Study of Substance-Ontological Premises

    DEFF Research Database (Denmark)

    Seibt, Johanna

    The thesis proposes therapeutic revision of fundamental assumptions in contemporary ontological thought. I show that non of the prevalent theories of objects, by virtue of certain implicit substance-ontological assumptions provides a viable account of the numerical, qualitative, and trans-tempora......-ontological presuppositions, I finally explore the result of rejecting all of them and sketch a scheme basic on dynamic masses which promises to yield coherent explanation of the ontological features of those complex processes that we commonly call objects....

  18. OntologyWidget – a reusable, embeddable widget for easily locating ontology terms

    OpenAIRE

    Beauheim, Catherine C; Wymore, Farrell; Nitzberg, Michael; Zachariah, Zachariah K; Jin, Heng; Skene, JH Pate; Ball, Catherine A; Sherlock, Gavin

    2007-01-01

    Abstract Background Biomedical ontologies are being widely used to annotate biological data in a computer-accessible, consistent and well-defined manner. However, due to their size and complexity, annotating data with appropriate terms from an ontology is often challenging for experts and non-experts alike, because there exist few tools that allow one to quickly find relevant ontology terms to easily populate a web form. Results We have produced a tool, OntologyWidget, which allows users to r...

  19. Towards refactoring the Molecular Function Ontology with a UML profile for function modeling.

    Science.gov (United States)

    Burek, Patryk; Loebe, Frank; Herre, Heinrich

    2017-10-04

    Gene Ontology (GO) is the largest resource for cataloging gene products. This resource grows steadily and, naturally, this growth raises issues regarding the structure of the ontology. Moreover, modeling and refactoring large ontologies such as GO is generally far from being simple, as a whole as well as when focusing on certain aspects or fragments. It seems that human-friendly graphical modeling languages such as the Unified Modeling Language (UML) could be helpful in connection with these tasks. We investigate the use of UML for making the structural organization of the Molecular Function Ontology (MFO), a sub-ontology of GO, more explicit. More precisely, we present a UML dialect, called the Function Modeling Language (FueL), which is suited for capturing functions in an ontologically founded way. FueL is equipped, among other features, with language elements that arise from studying patterns of subsumption between functions. We show how to use this UML dialect for capturing the structure of molecular functions. Furthermore, we propose and discuss some refactoring options concerning fragments of MFO. FueL enables the systematic, graphical representation of functions and their interrelations, including making information explicit that is currently either implicit in MFO or is mainly captured in textual descriptions. Moreover, the considered subsumption patterns lend themselves to the methodical analysis of refactoring options with respect to MFO. On this basis we argue that the approach can increase the comprehensibility of the structure of MFO for humans and can support communication, for example, during revision and further development.

  20. The NASA Air Traffic Management Ontology (atmonto)

    Data.gov (United States)

    National Aeronautics and Space Administration — The NASA ATM (Air Traffic Management) Ontology describes classes, properties, and relationships relevant to the domain of air traffic management, and represents...

  1. Ontology Enabled Generation of Embedded Web Services

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius; Zhang, Weishan; Soares, Goncalo Teofilo Afonso Pinheiro

    2008-01-01

    and software platforms, and of devices state and context changes. To address these challenges, we developed a Web service compiler, Limbo, in which Web Ontology Language (OWL) ontologies are used to make the Limbo compiler aware of its compilation context, such as targeted hardware and software. At the same...... time, knowledge on device details, platform dependencies, and resource/power consumption is built into the supporting ontologies, which are used to configure Limbo for generating resource efficient web service code. A state machine ontology is used to generate stub code to facilitate handling of state...

  2. Scientific Digital Libraries, Interoperability, and Ontologies

    Science.gov (United States)

    Hughes, J. Steven; Crichton, Daniel J.; Mattmann, Chris A.

    2009-01-01

    Scientific digital libraries serve complex and evolving research communities. Justifications for the development of scientific digital libraries include the desire to preserve science data and the promises of information interconnectedness, correlative science, and system interoperability. Shared ontologies are fundamental to fulfilling these promises. We present a tool framework, some informal principles, and several case studies where shared ontologies are used to guide the implementation of scientific digital libraries. The tool framework, based on an ontology modeling tool, was configured to develop, manage, and keep shared ontologies relevant within changing domains and to promote the interoperability, interconnectedness, and correlation desired by scientists.

  3. Finding the best visualization of an ontology

    DEFF Research Database (Denmark)

    Fabritius, Christina; Madsen, Nadia; Clausen, Jens

    2006-01-01

    An ontology is a classification model for a given domain.In information retrieval ontologies are used to perform broad searches.An ontology can be visualized as nodes and edges. Each node represents an element and each edge a relation between a parent and a child element. Working with an ontology....... One method uses a discrete location model to create an initial solution and we propose heuristic methods to further improve the visual result. We evaluate the visual results according to our success criteria and the feedback from users. Running times of the heuristic indicate that an improved version...

  4. Finding the best visualization of an ontology

    DEFF Research Database (Denmark)

    Fabritius, Christina Valentin; Madsen, Nadia Lyngaa; Clausen, Jens

    2004-01-01

    An ontology is a classification model for a given domain. In information retrieval ontologies are used to perform broad searches. An ontology can be visualized as nodes and edges. Each node represents an element and each edge a relation between a parent and a child element. Working with an ontology....... One method uses a discrete location model to create an initial solution and we propose heuristic methods to further improve the visual result. We evaluate the visual results according to our success criteria and the feedback from users. Running times of the heuristic indicate that an improved version...

  5. The current landscape of pitfalls in Ontologies

    CSIR Research Space (South Africa)

    Keet, CM

    2013-09-01

    Full Text Available 2Ontology Engineering Group, Departamento de Inteligencia Artificial, Universidad Polite´cnica de Madrid, Madrid, Spain keet@ukzn.ac.za, {mcsuarez,mpoveda}@fi.upm.es Keywords: Ontology Development : Ontology Quality : Pitfall Abstract: A growing... in Ontologies C. Maria Keet1, Mari Carmen Sua´rez-Figueroa2 and Marı´a Poveda-Villalo´n2 1School of Mathematics, Statistics, and Computer Science, University of KwaZulu-Natal, and UKZN/CSIR-Meraka Centre for Artificial Intelligence Research, Durban, South Africa...

  6. DEPONTO: A Reusable Dependability Domain Ontology

    Directory of Open Access Journals (Sweden)

    Teodora Sanislav

    2015-08-01

    Full Text Available This paper proposes a dependability reusable ontology for knowledge representation. The fundamental knowledge related to dependability follows its taxonomy. Thus, this paper gives an analysis of what is the dependability domain ontology andof its components.The dependability domain ontology plays an important role in ensuring the dependability of information systems by providing support for their diagnosis in case of faults, errors and failures.The proposed ontology is used as a dependability framework in two case study Cyber-Physical Systemswhich demonstrate its reusability within this category of systems.

  7. Learning Resources Organization Using Ontological Framework

    Science.gov (United States)

    Gavrilova, Tatiana; Gorovoy, Vladimir; Petrashen, Elena

    The paper describes the ontological approach to the knowledge structuring for the e-learning portal design as it turns out to be efficient and relevant to current domain conditions. It is primarily based on the visual ontology-based description of the content of the learning materials and this helps to provide productive and personalized access to these materials. The experience of ontology developing for Knowledge Engineering coursetersburg State University is discussed and “OntolingeWiki” tool for creating ontology-based e-learning portals is described.

  8. Ontological Engineering for the Cadastral Domain

    DEFF Research Database (Denmark)

    Stubkjær, Erik; Stuckenschmidt, Heiner

    2000-01-01

    conceptualization of the world is that much information remains implicit. Ontologies have set out to overcome the problem of implicit and hidden knowledge by making the conceptualization of a domain (e.g. mathematics) explicit. Ontological engineering is thus an approach to achieve a conceptual rigor...... that characterizes established academic disciplines, like geodesy. Many university courses address more application oriented fields, like cadastral law, and spatial planning, and they may benefit from the ontological engineering approach. The paper provides an introduction to the field of ontological engineering...

  9. Vaccine and Drug Ontology Studies (VDOS 2014).

    Science.gov (United States)

    Tao, Cui; He, Yongqun; Arabandi, Sivaram

    2016-01-01

    The "Vaccine and Drug Ontology Studies" (VDOS) international workshop series focuses on vaccine- and drug-related ontology modeling and applications. Drugs and vaccines have been critical to prevent and treat human and animal diseases. Work in both (drugs and vaccines) areas is closely related - from preclinical research and development to manufacturing, clinical trials, government approval and regulation, and post-licensure usage surveillance and monitoring. Over the last decade, tremendous efforts have been made in the biomedical ontology community to ontologically represent various areas associated with vaccines and drugs - extending existing clinical terminology systems such as SNOMED, RxNorm, NDF-RT, and MedDRA, developing new models such as the Vaccine Ontology (VO) and Ontology of Adverse Events (OAE), vernacular medical terminologies such as the Consumer Health Vocabulary (CHV). The VDOS workshop series provides a platform for discussing innovative solutions as well as the challenges in the development and applications of biomedical ontologies for representing and analyzing drugs and vaccines, their administration, host immune responses, adverse events, and other related topics. The five full-length papers included in this 2014 thematic issue focus on two main themes: (i) General vaccine/drug-related ontology development and exploration, and (ii) Interaction and network-related ontology studies.

  10. OntologyWidget – a reusable, embeddable widget for easily locating ontology terms

    Directory of Open Access Journals (Sweden)

    Skene JH Pate

    2007-09-01

    Full Text Available Abstract Background Biomedical ontologies are being widely used to annotate biological data in a computer-accessible, consistent and well-defined manner. However, due to their size and complexity, annotating data with appropriate terms from an ontology is often challenging for experts and non-experts alike, because there exist few tools that allow one to quickly find relevant ontology terms to easily populate a web form. Results We have produced a tool, OntologyWidget, which allows users to rapidly search for and browse ontology terms. OntologyWidget can easily be embedded in other web-based applications. OntologyWidget is written using AJAX (Asynchronous JavaScript and XML and has two related elements. The first is a dynamic auto-complete ontology search feature. As a user enters characters into the search box, the appropriate ontology is queried remotely for terms that match the typed-in text, and the query results populate a drop-down list with all potential matches. Upon selection of a term from the list, the user can locate this term within a generic and dynamic ontology browser, which comprises the second element of the tool. The ontology browser shows the paths from a selected term to the root as well as parent/child tree hierarchies. We have implemented web services at the Stanford Microarray Database (SMD, which provide the OntologyWidget with access to over 40 ontologies from the Open Biological Ontology (OBO website 1. Each ontology is updated weekly. Adopters of the OntologyWidget can either use SMD's web services, or elect to rely on their own. Deploying the OntologyWidget can be accomplished in three simple steps: (1 install Apache Tomcat 2 on one's web server, (2 download and install the OntologyWidget servlet stub that provides access to the SMD ontology web services, and (3 create an html (HyperText Markup Language file that refers to the OntologyWidget using a simple, well-defined format. Conclusion We have developed Ontology

  11. Turning the table: plants consume microbes as a source of nutrients.

    Directory of Open Access Journals (Sweden)

    Chanyarat Paungfoo-Lonhienne

    Full Text Available Interactions between plants and microbes in soil, the final frontier of ecology, determine the availability of nutrients to plants and thereby primary production of terrestrial ecosystems. Nutrient cycling in soils is considered a battle between autotrophs and heterotrophs in which the latter usually outcompete the former, although recent studies have questioned the unconditional reign of microbes on nutrient cycles and the plants' dependence on microbes for breakdown of organic matter. Here we present evidence indicative of a more active role of plants in nutrient cycling than currently considered. Using fluorescent-labeled non-pathogenic and non-symbiotic strains of a bacterium and a fungus (Escherichia coli and Saccharomyces cerevisiae, respectively, we demonstrate that microbes enter root cells and are subsequently digested to release nitrogen that is used in shoots. Extensive modifications of root cell walls, as substantiated by cell wall outgrowth and induction of genes encoding cell wall synthesizing, loosening and degrading enzymes, may facilitate the uptake of microbes into root cells. Our study provides further evidence that the autotrophy of plants has a heterotrophic constituent which could explain the presence of root-inhabiting microbes of unknown ecological function. Our discovery has implications for soil ecology and applications including future sustainable agriculture with efficient nutrient cycles.

  12. Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration

    Science.gov (United States)

    Ong, Edison; Xiang, Zuoshuang; Zhao, Bin; Liu, Yue; Lin, Yu; Zheng, Jie; Mungall, Chris; Courtot, Mélanie; Ruttenberg, Alan; He, Yongqun

    2017-01-01

    Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies. PMID:27733503

  13. Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration.

    Science.gov (United States)

    Ong, Edison; Xiang, Zuoshuang; Zhao, Bin; Liu, Yue; Lin, Yu; Zheng, Jie; Mungall, Chris; Courtot, Mélanie; Ruttenberg, Alan; He, Yongqun

    2017-01-04

    Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. How Ontologies are Made: Studying the Hidden Social Dynamics Behind Collaborative Ontology Engineering Projects.

    Science.gov (United States)

    Strohmaier, Markus; Walk, Simon; Pöschko, Jan; Lamprecht, Daniel; Tudorache, Tania; Nyulas, Csongor; Musen, Mark A; Noy, Natalya F

    2013-05-01

    Traditionally, evaluation methods in the field of semantic technologies have focused on the end result of ontology engineering efforts, mainly, on evaluating ontologies and their corresponding qualities and characteristics. This focus has led to the development of a whole arsenal of ontology-evaluation techniques that investigate the quality of ontologies as a product . In this paper, we aim to shed light on the process of ontology engineering construction by introducing and applying a set of measures to analyze hidden social dynamics. We argue that especially for ontologies which are constructed collaboratively, understanding the social processes that have led to its construction is critical not only in understanding but consequently also in evaluating the ontology. With the work presented in this paper, we aim to expose the texture of collaborative ontology engineering processes that is otherwise left invisible. Using historical change-log data, we unveil qualitative differences and commonalities between different collaborative ontology engineering projects. Explaining and understanding these differences will help us to better comprehend the role and importance of social factors in collaborative ontology engineering projects. We hope that our analysis will spur a new line of evaluation techniques that view ontologies not as the static result of deliberations among domain experts, but as a dynamic, collaborative and iterative process that needs to be understood, evaluated and managed in itself. We believe that advances in this direction would help our community to expand the existing arsenal of ontology evaluation techniques towards more holistic approaches.

  15. Sample ontology, GOstat and ontology term enrichment - FANTOM5 | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data List Contact us FANTOM....biosciencedbc.jp/archive/fantom5/datafiles/LATEST/extra/Ontology/ File size: 1.8 MB Simple search URL - Dat...t Us Sample ontology, GOstat and ontology term enrichment - FANTOM5 | LSDB Archive ...

  16. How Ontologies are Made: Studying the Hidden Social Dynamics Behind Collaborative Ontology Engineering Projects

    Science.gov (United States)

    Strohmaier, Markus; Walk, Simon; Pöschko, Jan; Lamprecht, Daniel; Tudorache, Tania; Nyulas, Csongor; Musen, Mark A.; Noy, Natalya F.

    2013-01-01

    Traditionally, evaluation methods in the field of semantic technologies have focused on the end result of ontology engineering efforts, mainly, on evaluating ontologies and their corresponding qualities and characteristics. This focus has led to the development of a whole arsenal of ontology-evaluation techniques that investigate the quality of ontologies as a product. In this paper, we aim to shed light on the process of ontology engineering construction by introducing and applying a set of measures to analyze hidden social dynamics. We argue that especially for ontologies which are constructed collaboratively, understanding the social processes that have led to its construction is critical not only in understanding but consequently also in evaluating the ontology. With the work presented in this paper, we aim to expose the texture of collaborative ontology engineering processes that is otherwise left invisible. Using historical change-log data, we unveil qualitative differences and commonalities between different collaborative ontology engineering projects. Explaining and understanding these differences will help us to better comprehend the role and importance of social factors in collaborative ontology engineering projects. We hope that our analysis will spur a new line of evaluation techniques that view ontologies not as the static result of deliberations among domain experts, but as a dynamic, collaborative and iterative process that needs to be understood, evaluated and managed in itself. We believe that advances in this direction would help our community to expand the existing arsenal of ontology evaluation techniques towards more holistic approaches. PMID:24311994

  17. Where to Publish and Find Ontologies? A Survey of Ontology Libraries

    Science.gov (United States)

    d'Aquin, Mathieu; Noy, Natalya F.

    2011-01-01

    One of the key promises of the Semantic Web is its potential to enable and facilitate data interoperability. The ability of data providers and application developers to share and reuse ontologies is a critical component of this data interoperability: if different applications and data sources use the same set of well defined terms for describing their domain and data, it will be much easier for them to “talk” to one another. Ontology libraries are the systems that collect ontologies from different sources and facilitate the tasks of finding, exploring, and using these ontologies. Thus ontology libraries can serve as a link in enabling diverse users and applications to discover, evaluate, use, and publish ontologies. In this paper, we provide a survey of the growing—and surprisingly diverse—landscape of ontology libraries. We highlight how the varying scope and intended use of the libraries a ects their features, content, and potential exploitation in applications. From reviewing eleven ontology libraries, we identify a core set of questions that ontology practitioners and users should consider in choosing an ontology library for finding ontologies or publishing their own. We also discuss the research challenges that emerge from this survey, for the developers of ontology libraries to address. PMID:22408576

  18. Surreptitious, Evolving and Participative Ontology Development: An End-User Oriented Ontology Development Methodology

    Science.gov (United States)

    Bachore, Zelalem

    2012-01-01

    Ontology not only is considered to be the backbone of the semantic web but also plays a significant role in distributed and heterogeneous information systems. However, ontology still faces limited application and adoption to date. One of the major problems is that prevailing engineering-oriented methodologies for building ontologies do not…

  19. Towards Ontology-Driven Information Systems: Guidelines to the Creation of New Methodologies to Build Ontologies

    Science.gov (United States)

    Soares, Andrey

    2009-01-01

    This research targeted the area of Ontology-Driven Information Systems, where ontology plays a central role both at development time and at run time of Information Systems (IS). In particular, the research focused on the process of building domain ontologies for IS modeling. The motivation behind the research was the fact that researchers have…

  20. NCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendation.

    Science.gov (United States)

    Martínez-Romero, Marcos; Jonquet, Clement; O'Connor, Martin J; Graybeal, John; Pazos, Alejandro; Musen, Mark A

    2017-06-07

    Ontologies and controlled terminologies have become increasingly important in biomedical research. Researchers use ontologies to annotate their data with ontology terms, enabling better data integration and interoperability across disparate datasets. However, the number, variety and complexity of current biomedical ontologies make it cumbersome for researchers to determine which ones to reuse for their specific needs. To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms. We developed a new version of the NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a novel recommendation approach that evaluates the relevance of an ontology to biomedical text data according to four different criteria: (1) the extent to which the ontology covers the input data; (2) the acceptance of the ontology in the biomedical community; (3) the level of detail of the ontology classes that cover the input data; and (4) the specialization of the ontology to the domain of the input data. Our evaluation shows that the enhanced recommender provides higher quality suggestions than the original approach, providing better coverage of the input data, more detailed information about their concepts, increased specialization for the domain of the input data, and greater acceptance and use in the community. In addition, it provides users with more explanatory information, along with suggestions of not only individual ontologies but also groups of ontologies to use together. It also can be customized to fit the needs of different ontology recommendation scenarios. Ontology Recommender 2.0 suggests relevant ontologies for annotating biomedical text data. It combines the strengths of its predecessor with a range of adjustments and new features that improve its reliability

  1. A high-resolution anatomical ontology of the developing murine genitourinary tract

    Science.gov (United States)

    Little, Melissa H.; Brennan, Jane; Georgas, Kylie; Davies, Jamie A.; Davidson, Duncan R.; Baldock, Richard A.; Beverdam, Annemiek; Bertram, John F.; Capel, Blanche; Chiu, Han Sheng; Clements, Dave; Cullen-McEwen, Luise; Fleming, Jean; Gilbert, Thierry; Houghton, Derek; Kaufman, Matt H.; Kleymenova, Elena; Koopman, Peter A.; Lewis, Alfor G.; McMahon, Andrew P.; Mendelsohn, Cathy L.; Mitchell, Eleanor K.; Rumballe, Bree A.; Sweeney, Derina E.; Valerius, M. Todd; Yamada, Gen; Yang, Yiya; Yu., Jing

    2007-01-01

    Cataloguing gene expression during development of the genitourinary tract will increase our understanding not only of this process but also of congenital defects and disease affecting this organ system. We have developed a high-resolution ontology with which to describe the subcompartments of the developing murine genitourinary tract. This ontology incorporates what can be defined histologically and begins to encompass other structures and cell types already identified at the molecular level. The ontology is being used to annotate in situ hybridisation data generated as part of the Genitourinary Development Molecular Anatomy Project (GUDMAP), a publicly available data resource on gene and protein expression during genitourinary development. The GUDMAP ontology encompasses Theiler stage (TS) 17 to 27 of development as well as the sexually mature adult. It has been written as a partonomic, text-based, hierarchical ontology that, for the embryological stages, has been developed as a high-resolution expansion of the existing Edinburgh Mouse Atlas Project (EMAP) ontology. It also includes group terms for well-characterised structural and/or functional units comprising several sub-structures, such as the nephron and juxtaglomerular complex. Each term has been assigned a unique identification number. Synonyms have been used to improve the success of query searching and maintain wherever possible existing EMAP terms relating to this organ system. We describe here the principles and structure of the ontology and provide representative diagrammatic, histological, and whole mount and section RNA in situ hybridisation images to clarify the terms used within the ontology. Visual examples of how terms appear in different specimen types are also provided. PMID:17452023

  2. Deep learning meets ontologies: experiments to anchor the cardiovascular disease ontology in the biomedical literature.

    Science.gov (United States)

    Arguello Casteleiro, Mercedes; Demetriou, George; Read, Warren; Fernandez Prieto, Maria Jesus; Maroto, Nava; Maseda Fernandez, Diego; Nenadic, Goran; Klein, Julie; Keane, John; Stevens, Robert

    2018-04-12

    Automatic identification of term variants or acceptable alternative free-text terms for gene and protein names from the millions of biomedical publications is a challenging task. Ontologies, such as the Cardiovascular Disease Ontology (CVDO), capture domain knowledge in a computational form and can provide context for gene/protein names as written in the literature. This study investigates: 1) if word embeddings from Deep Learning algorithms can provide a list of term variants for a given gene/protein of interest; and 2) if biological knowledge from the CVDO can improve such a list without modifying the word embeddings created. We have manually annotated 105 gene/protein names from 25 PubMed titles/abstracts and mapped them to 79 unique UniProtKB entries corresponding to gene and protein classes from the CVDO. Using more than 14 M PubMed articles (titles and available abstracts), word embeddings were generated with CBOW and Skip-gram. We setup two experiments for a synonym detection task, each with four raters, and 3672 pairs of terms (target term and candidate term) from the word embeddings created. For Experiment I, the target terms for 64 UniProtKB entries were those that appear in the titles/abstracts; Experiment II involves 63 UniProtKB entries and the target terms are a combination of terms from PubMed titles/abstracts with terms (i.e. increased context) from the CVDO protein class expressions and labels. In Experiment I, Skip-gram finds term variants (full and/or partial) for 89% of the 64 UniProtKB entries, while CBOW finds term variants for 67%. In Experiment II (with the aid of the CVDO), Skip-gram finds term variants for 95% of the 63 UniProtKB entries, while CBOW finds term variants for 78%. Combining the results of both experiments, Skip-gram finds term variants for 97% of the 79 UniProtKB entries, while CBOW finds term variants for 81%. This study shows performance improvements for both CBOW and Skip-gram on a gene/protein synonym detection task by

  3. Concepts, ontologies, and knowledge representation

    CERN Document Server

    Jakus, Grega; Omerovic, Sanida; Tomažic, Sašo

    2013-01-01

    Recording knowledge in a common framework that would make it possible to seamlessly share global knowledge remains an important challenge for researchers. This brief examines several ideas about the representation of knowledge addressing this challenge. A widespread general agreement is followed that states uniform knowledge representation should be achievable by using ontologies populated with concepts. A separate chapter is dedicated to each of the three introduced topics, following a uniform outline: definition, organization, and use. This brief is intended for those who want to get to know

  4. Nosology, ontology and promiscuous realism.

    Science.gov (United States)

    Binney, Nicholas

    2015-06-01

    Medics may consider worrying about their metaphysics and ontology to be a waste of time. I will argue here that this is not the case. Promiscuous realism is a metaphysical position which holds that multiple, equally valid, classification schemes should be applied to objects (such as patients) to capture different aspects of their complex and heterogeneous nature. As medics at the bedside may need to capture different aspects of their patients' problems, they may need to use multiple classification schemes (multiple nosologies), and thus consider adopting a different metaphysics to the one commonly in use. © 2014 John Wiley & Sons, Ltd.

  5. Semantics and metaphysics in informatics: toward an ontology of tasks.

    Science.gov (United States)

    Figdor, Carrie

    2011-04-01

    This article clarifies three principles that should guide the development of any cognitive ontology. First, that an adequate cognitive ontology depends essentially on an adequate task ontology; second, that the goal of developing a cognitive ontology is independent of the goal of finding neural implementations of the processes referred to in the ontology; and third, that cognitive ontologies are neutral regarding the metaphysical relationship between cognitive and neural processes. Copyright © 2011 Cognitive Science Society, Inc.

  6. Merged ontology for engineering design: Contrasting empirical and theoretical approaches to develop engineering ontologies

    DEFF Research Database (Denmark)

    Ahmed, Saeema; Storga, M

    2009-01-01

    to developing the ontology engineering design integrated taxonomies (EDIT) with a theoretical approach in which concepts and relations are elicited from engineering design theories ontology (DO) The limitations and advantages of each approach are discussed. The research methodology adopted is to map......This paper presents a comparison of two previous and separate efforts to develop an ontology in the engineering design domain, together with an ontology proposal from which ontologies for a specific application may be derived. The research contrasts an empirical, user-centered approach...

  7. MicrobeWorld Radio and Communications Initiative

    Energy Technology Data Exchange (ETDEWEB)

    Barbara Hyde

    2006-11-22

    MicrobeWorld is a 90-second feature broadcast daily on more than 90 public radio stations and available from several sources as a podcast, including www.microbeworld.org. The feature has a strong focus on the use and adapatbility of microbes as alternative sources of energy, in bioremediation, their role in climate, and especially the many benefits and scientific advances that have resulting from decoding microbial genomes. These audio features are permanantly archived on an educational outreach site, microbeworld.org, where they are linked to the National Science Education Standards. They are also being used by instructors at all levels to introduce students to the multiple roles and potential of microbes, including a pilot curriculum program for middle-school students in New York.

  8. An ontological case base engineering methodology for diabetes management.

    Science.gov (United States)

    El-Sappagh, Shaker H; El-Masri, Samir; Elmogy, Mohammed; Riad, A M; Saddik, Basema

    2014-08-01

    Ontology engineering covers issues related to ontology development and use. In Case Based Reasoning (CBR) system, ontology plays two main roles; the first as case base and the second as domain ontology. However, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. This paper proposes an ontology engineering methodology to generate case bases in the medical domain. It mainly focuses on the research of case representation in the form of ontology to support the case semantic retrieval and enhance all knowledge intensive CBR processes. A case study on diabetes diagnosis case base will be provided to evaluate the proposed methodology.

  9. University of Texas Southwestern Medical Center (UTSW): Functional Signature Ontology Tool: Triplicate Measurements of Reporter Gene Expression in Response to Individual Genetic and Chemical Perturbations in HCT116 Cells | Office of Cancer Genomics

    Science.gov (United States)

    The goal of this project is to use an eight-gene expression profile to define functional signatures for small molecules and natural products with heretofore undefined mechanism of action. Two genes in the eight gene set are used as internal controls and do not vary across gene expression array data collected from the public domain. The remaining six genes are found to vary independently across a large collection of publically available gene expression array datasets.  Read the abstract

  10. University of Texas Southwestern Medical Center: Functional Signature Ontology Tool: Triplicate Measurements of Reporter Gene Expression in Response to Individual Genetic and Chemical Perturbations in HCT116 Cells | Office of Cancer Genomics

    Science.gov (United States)

    The goal of this project is to use an eight-gene expression profile to define functional signatures for small molecules and natural products with heretofore undefined mechanism of action. Two genes in the eight gene set are used as internal controls and do not vary across gene expression array data collected from the public domain. The remaining six genes are found to vary independently across a large collection of publically available gene expression array datasets.  Read the abstract

  11. The eXtensible ontology development (XOD) principles and tool implementation to support ontology interoperability.

    Science.gov (United States)

    He, Yongqun; Xiang, Zuoshuang; Zheng, Jie; Lin, Yu; Overton, James A; Ong, Edison

    2018-01-12

    Ontologies are critical to data/metadata and knowledge standardization, sharing, and analysis. With hundreds of biological and biomedical ontologies developed, it has become critical to ensure ontology interoperability and the usage of interoperable ontologies for standardized data representation and integration. The suite of web-based Ontoanimal tools (e.g., Ontofox, Ontorat, and Ontobee) support different aspects of extensible ontology development. By summarizing the common features of Ontoanimal and other similar tools, we identified and proposed an "eXtensible Ontology Development" (XOD) strategy and its associated four principles. These XOD principles reuse existing terms and semantic relations from reliable ontologies, develop and apply well-established ontology design patterns (ODPs), and involve community efforts to support new ontology development, promoting standardized and interoperable data and knowledge representation and integration. The adoption of the XOD strategy, together with robust XOD tool development, will greatly support ontology interoperability and robust ontology applications to support data to be Findable, Accessible, Interoperable and Reusable (i.e., FAIR).

  12. Introduction to Semantic Web Ontology Languages

    NARCIS (Netherlands)

    Antoniou, Grigoris; Franconi, Enrico; Van Harmelen, Frank

    2005-01-01

    The aim of this chapter is to give a general introduction to some of the ontology languages that play a prominent role on the Semantic Web, and to discuss the formal foundations of these languages. Web ontology languages will be the main carriers of the information that we will want to share and

  13. 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.

  14. 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.

  15. Fuzzy knowledge bases integration based on ontology

    OpenAIRE

    Ternovoy, Maksym; Shtogrina, Olena

    2012-01-01

    the paper describes the approach for fuzzy knowledge bases integration with the usage of ontology. This approach is based on metadata-base usage for integration of different knowledge bases with common ontology. The design process of metadata-base is described.

  16. C2 Domain Ontology within Our Lifetime

    Science.gov (United States)

    2009-06-01

    25] Masolo, C., et al: The WonderWeb Library of Foundational Ontologies Prelimary Report, WonderWeb Deliverable D17, ISTC -CNR, May 2003. [26...www.ifomis.org/bfo/BFO  [25] Masolo, C., et al: The WonderWeb Library of Foundational Ontologies Prelimary Report, WonderWeb Deliverable D17, ISTC -CNR

  17. Recent changes in the Building Topology Ontology

    DEFF Research Database (Denmark)

    Rasmussen, Mads Holten; Pauwels, Pieter; Lefrancois, Maxime

    The Building Topology Ontology (BOT) was in early 2017 suggested to the W3C community group for Linked Building Data as a simple ontology covering the core concepts of a building. Since it was first announced it has been extended to cover a building site, elements hosted by other elements, zones...

  18. Critical Ontology for an Enactive Music Pedagogy

    Science.gov (United States)

    van der Schyff, Dylan; Schiavio, Andrea; Elliott, David J.

    2016-01-01

    An enactive approach to music education is explored through the lens of critical ontology. Assumptions central to Western academic music culture are critically discussed; and the concept of "ontological education" is introduced as an alternative framework. We argue that this orientation embraces more primordial ways of knowing and being,…

  19. Integrity and change in modular ontologies

    NARCIS (Netherlands)

    Stuckenschmidt, Heiner; Klein, Michel

    2003-01-01

    The benefits of modular representations arc well known from many areas of computer science. In this paper, we concentrate on the benefits of modular ontologies with respect to local containment of terminological reasoning. We define an architecture for modular ontologies that supports local

  20. Ontologies and Information Systems: A Literature Survey

    Science.gov (United States)

    2011-06-01

    Falcon-AO (LMO + GMO ) [146], and RiMOM [317]. Meta-matching systems include APFEL [76] and eTuner [286]. There also exist frameworks that provide a set...Jian, N., Qu, Y. and Wang, Q. 2005. GMO : A graph matching for ontologies. In Proceedings of the K-CAPWorkshop on Integrating Ontologies, Banff

  1. Collaborative ontology development for the geosciences

    NARCIS (Netherlands)

    Kalbasi Khoramdashti, R.; Janowicz, K.; Reitsma, F.; Boerboom, L.G.J.; Alasheikh, A.

    2014-01-01

    Ontology-based information publishing, retrieval, reuse, and integration have become popular research topics to address the challenges involved in exchanging data between heterogeneous sources. However, in most cases ontologies are still developed in a centralized top-down manner by a few knowledge

  2. An ontology roadmap for crowdsourcing innovation intermediaries

    OpenAIRE

    Silva, Cândida; Ramos, Isabel

    2014-01-01

    Ontologies have proliferated in the last years, essentially justified by the need of achieving a consensus in the multiple representations of reality inside computers, and therefore the accomplishment of interoperability between machines and systems. Ontologies provide an explicit conceptualization that describes the semantics of the data. Crowdsourcing innovation intermediaries are organizations that mediate the communication and relationship between companies that aspire to solv...

  3. Ontology Assisted Formal Specification Extraction from Text

    Directory of Open Access Journals (Sweden)

    Andreea Mihis

    2010-12-01

    Full Text Available In the field of knowledge processing, the ontologies are the most important mean. They make possible for the computer to understand better the natural language and to make judgments. In this paper, a method which use ontologies in the semi-automatic extraction of formal specifications from a natural language text is proposed.

  4. [Towards a structuring fibrillar ontology].

    Science.gov (United States)

    Guimberteau, J-C

    2012-10-01

    Over previous decades and centuries, the difficulty encountered in the manner in which the tissue of our bodies is organised, and structured, is clearly explained by the impossibility of exploring it in detail. Since the creation of the microscope, the perception of the basic unity, which is the cell, has been essential in understanding the functioning of reproduction and of transmission, but has not been able to explain the notion of form; since the cells are not everywhere and are not distributed in an apparently balanced manner. The problems that remain are those of form and volume and also of connection. The concept of multifibrillar architecture, shaping the interfibrillar microvolumes in space, represents a solution to all these questions. The architectural structures revealed, made up of fibres, fibrils and microfibrils, from the mesoscopic to the microscopic level, provide the concept of a living form with structural rationalism that permits the association of psychochemical molecular biodynamics and quantum physics: the form can thus be described and interpreted, and a true structural ontology is elaborated from a basic functional unity, which is the microvacuole, the intra and interfibrillar volume of the fractal organisation, and the chaotic distribution. Naturally, new, less linear, less conclusive, and less specific concepts will be implied by this ontology, leading one to believe that the emergence of life takes place under submission to forces that the original form will have imposed and oriented the adaptive finality. Copyright © 2012. Published by Elsevier SAS.

  5. Knowledge Management Framework for Emerging Infectious Diseases Preparedness and Response: Design and Development of Public Health Document Ontology.

    Science.gov (United States)

    Zhang, Zhizun; Gonzalez, Mila C; Morse, Stephen S; Venkatasubramanian, Venkat

    2017-10-11

    There are increasing concerns about our preparedness and timely coordinated response across the globe to cope with emerging infectious diseases (EIDs). This poses practical challenges that require exploiting novel knowledge management approaches effectively. This work aims to develop an ontology-driven knowledge management framework that addresses the existing challenges in sharing and reusing public health knowledge. We propose a systems engineering-inspired ontology-driven knowledge management approach. It decomposes public health knowledge into concepts and relations and organizes the elements of knowledge based on the teleological functions. Both knowledge and semantic rules are stored in an ontology and retrieved to answer queries regarding EID preparedness and response. A hybrid concept extraction was implemented in this work. The quality of the ontology was evaluated using the formal evaluation method Ontology Quality Evaluation Framework. Our approach is a potentially effective methodology for managing public health knowledge. Accuracy and comprehensiveness of the ontology can be improved as more knowledge is stored. In the future, a survey will be conducted to collect queries from public health practitioners. The reasoning capacity of the ontology will be evaluated using the queries and hypothetical outbreaks. We suggest the importance of developing a knowledge sharing standard like the Gene Ontology for the public health domain. ©Zhizun Zhang, Mila C Gonzalez, Stephen S Morse, Venkat Venkatasubramanian. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 11.10.2017.

  6. GFVO: the Genomic Feature and Variation Ontology

    KAUST Repository

    Baran, Joachim; Durgahee, Bibi Sehnaaz Begum; Eilbeck, Karen; Antezana, Erick; Hoehndorf, Robert; Dumontier, Michel

    2015-01-01

    Availability and implementation. The latest stable release of the ontology is available via its base URI; previous and development versions are available at the ontology’s GitHub repository: https://github.com/BioInterchange/Ontologies; versions of the ontology are indexed through BioPortal (without external class-/property-equivalences due to BioPortal release 4.10 limitations); examples and reference documentation is provided on a separate web-page: http://www.biointerchange.org/ontologies.html. GFVO version 1.0.2 is licensed under the CC0 1.0 Universal license (https://creativecommons.org/publicdomain/zero/1.0) and therefore de facto within the public domain; the ontology can be appropriated without attribution for commercial and non-commercial use.

  7. Ontology modeling in physical asset integrity management

    CERN Document Server

    Yacout, Soumaya

    2015-01-01

    This book presents cutting-edge applications of, and up-to-date research on, ontology engineering techniques in the physical asset integrity domain. Though a survey of state-of-the-art theory and methods on ontology engineering, the authors emphasize essential topics including data integration modeling, knowledge representation, and semantic interpretation. The book also reflects novel topics dealing with the advanced problems of physical asset integrity applications such as heterogeneity, data inconsistency, and interoperability existing in design and utilization. With a distinctive focus on applications relevant in heavy industry, Ontology Modeling in Physical Asset Integrity Management is ideal for practicing industrial and mechanical engineers working in the field, as well as researchers and graduate concerned with ontology engineering in physical systems life cycles. This book also: Introduces practicing engineers, research scientists, and graduate students to ontology engineering as a modeling techniqu...

  8. Model Driven Engineering with Ontology Technologies

    Science.gov (United States)

    Staab, Steffen; Walter, Tobias; Gröner, Gerd; Parreiras, Fernando Silva

    Ontologies constitute formal models of some aspect of the world that may be used for drawing interesting logical conclusions even for large models. Software models capture relevant characteristics of a software artifact to be developed, yet, most often these software models have limited formal semantics, or the underlying (often graphical) software language varies from case to case in a way that makes it hard if not impossible to fix its semantics. In this contribution, we survey the use of ontology technologies for software modeling in order to carry over advantages from ontology technologies to the software modeling domain. It will turn out that ontology-based metamodels constitute a core means for exploiting expressive ontology reasoning in the software modeling domain while remaining flexible enough to accommodate varying needs of software modelers.

  9. A priorean approach to time ontologies

    DEFF Research Database (Denmark)

    Øhrstrøm, Peter; Schärfe, Henrik

    2004-01-01

    Any non-trivial top-level ontology should take temporal notions into account. The details of how this should be done, however, are frequently debated. In this paper it is argued that "the four grades of tense-logical involvement" suggested by A.N. Prior form a useful framework for discussing how...... various temporal notions are related in a top-level ontology. Furthermore, a number of modern ontologies are analysed with respect to their incorporation of temporal notions. It is argued that all of them correspond to Prior's first and second grade, and that none of them reflect the views which Prior......'s third and fourth grade represent. Finally, the paper deals with Prior's ideas on a tensed ontology and it is argued that a logic based on the third grade and will be useful in the further development of tensed ontology....

  10. Geo-Ontologies Are Scale Dependent

    Science.gov (United States)

    Frank, A. U.

    2009-04-01

    Philosophers aim at a single ontology that describes "how the world is"; for information systems we aim only at ontologies that describe a conceptualization of reality (Guarino 1995; Gruber 2005). A conceptualization of the world implies a spatial and temporal scale: what are the phenomena, the objects and the speed of their change? Few articles (Reitsma et al. 2003) seem to address that an ontology is scale specific (but many articles indicate that ontologies are scale-free in another sense namely that they are scale free in the link densities between concepts). The scale in the conceptualization can be linked to the observation process. The extent of the support of the physical observation instrument and the sampling theorem indicate what level of detail we find in a dataset. These rules apply for remote sensing or sensor networks alike. An ontology of observations must include scale or level of detail, and concepts derived from observations should carry this relation forward. A simple example: in high resolution remote sensing image agricultural plots and roads between them are shown, at lower resolution, only the plots and not the roads are visible. This gives two ontologies, one with plots and roads, the other with plots only. Note that a neighborhood relation in the two different ontologies also yield different results. References Gruber, T. (2005). "TagOntology - a way to agree on the semantics of tagging data." Retrieved October 29, 2005., from http://tomgruber.org/writing/tagontology-tagcapm-talk.pdf. Guarino, N. (1995). "Formal Ontology, Conceptual Analysis and Knowledge Representation." International Journal of Human and Computer Studies. Special Issue on Formal Ontology, Conceptual Analysis and Knowledge Representation, edited by N. Guarino and R. Poli 43(5/6). Reitsma, F. and T. Bittner (2003). Process, Hierarchy, and Scale. Spatial Information Theory. Cognitive and Computational Foundations of Geographic Information ScienceInternational Conference

  11. TermGenie - a web-application for pattern-based ontology class generation.

    Science.gov (United States)

    Dietze, Heiko; Berardini, Tanya Z; Foulger, Rebecca E; Hill, David P; Lomax, Jane; Osumi-Sutherland, David; Roncaglia, Paola; Mungall, Christopher J

    2014-01-01

    Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes. TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes. TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

  12. OMIT: dynamic, semi-automated ontology development for the microRNA domain.

    Directory of Open Access Journals (Sweden)

    Jingshan Huang

    Full Text Available As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT, the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology.

  13. OMIT: dynamic, semi-automated ontology development for the microRNA domain.

    Science.gov (United States)

    Huang, Jingshan; Dang, Jiangbo; Borchert, Glen M; Eilbeck, Karen; Zhang, He; Xiong, Min; Jiang, Weijian; Wu, Hao; Blake, Judith A; Natale, Darren A; Tan, Ming

    2014-01-01

    As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs) have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT), the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i) We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii) We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology.

  14. OMIT: Dynamic, Semi-Automated Ontology Development for the microRNA Domain

    Science.gov (United States)

    Huang, Jingshan; Dang, Jiangbo; Borchert, Glen M.; Eilbeck, Karen; Zhang, He; Xiong, Min; Jiang, Weijian; Wu, Hao; Blake, Judith A.; Natale, Darren A.; Tan, Ming

    2014-01-01

    As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs) have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT), the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i) We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii) We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology. PMID:25025130

  15. Ontology-based, Tissue MicroArray oriented, image centered tissue bank

    Directory of Open Access Journals (Sweden)

    Viti Federica

    2008-04-01

    Full Text Available Abstract Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes.

  16. The Software Ontology (SWO): a resource for reproducibility in biomedical data analysis, curation and digital preservation.

    Science.gov (United States)

    Malone, James; Brown, Andy; Lister, Allyson L; Ison, Jon; Hull, Duncan; Parkinson, Helen; Stevens, Robert

    2014-01-01

    Biomedical ontologists to date have concentrated on ontological descriptions of biomedical entities such as gene products and their attributes, phenotypes and so on. Recently, effort has diversified to descriptions of the laboratory investigations by which these entities were produced. However, much biological insight is gained from the analysis of the data produced from these investigations, and there is a lack of adequate descriptions of the wide range of software that are central to bioinformatics. We need to describe how data are analyzed for discovery, audit trails, provenance and reproducibility. The Software Ontology (SWO) is a description of software used to store, manage and analyze data. Input to the SWO has come from beyond the life sciences, but its main focus is the life sciences. We used agile techniques to gather input for the SWO and keep engagement with our users. The result is an ontology that meets the needs of a broad range of users by describing software, its information processing tasks, data inputs and outputs, data formats versions and so on. Recently, the SWO has incorporated EDAM, a vocabulary for describing data and related concepts in bioinformatics. The SWO is currently being used to describe software used in multiple biomedical applications. The SWO is another element of the biomedical ontology landscape that is necessary for the description of biomedical entities and how they were discovered. An ontology of software used to analyze data produced by investigations in the life sciences can be made in such a way that it covers the important features requested and prioritized by its users. The SWO thus fits into the landscape of biomedical ontologies and is produced using techniques designed to keep it in line with user's needs. The Software Ontology is available under an Apache 2.0 license at http://theswo.sourceforge.net/; the Software Ontology blog can be read at http://softwareontology.wordpress.com.

  17. Natural products from microbes associated with insects

    DEFF Research Database (Denmark)

    Beemelmanns, Christine; Guo, Huijuan; Rischer, Maja

    2016-01-01

    Here we review discoveries of secondary metabolites from microbes associated with insects. We mainly focus on natural products, where the ecological role has been at least partially elucidated, and/or the pharmaceutical properties evaluated, and on compounds with unique structural features. We...

  18. MVP: a microbe-phage interaction database.

    Science.gov (United States)

    Gao, Na L; Zhang, Chengwei; Zhang, Zhanbing; Hu, Songnian; Lercher, Martin J; Zhao, Xing-Ming; Bork, Peer; Liu, Zhi; Chen, Wei-Hua

    2018-01-04

    Phages invade microbes, accomplish host lysis and are of vital importance in shaping the community structure of environmental microbiota. More importantly, most phages have very specific hosts; they are thus ideal tools to manipulate environmental microbiota at species-resolution. The main purpose of MVP (Microbe Versus Phage) is to provide a comprehensive catalog of phage-microbe interactions and assist users to select phage(s) that can target (and potentially to manipulate) specific microbes of interest. We first collected 50 782 viral sequences from various sources and clustered them into 33 097 unique viral clusters based on sequence similarity. We then identified 26 572 interactions between 18 608 viral clusters and 9245 prokaryotes (i.e. bacteria and archaea); we established these interactions based on 30 321 evidence entries that we collected from published datasets, public databases and re-analysis of genomic and metagenomic sequences. Based on these interactions, we calculated the host range for each of the phage clusters and accordingly grouped them into subgroups such as 'species-', 'genus-' and 'family-' specific phage clusters. MVP is equipped with a modern, responsive and intuitive interface, and is freely available at: http://mvp.medgenius.info. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  19. The mucosal firewalls against commensal intestinal microbes.

    Science.gov (United States)

    Macpherson, Andrew J; Slack, Emma; Geuking, Markus B; McCoy, Kathy D

    2009-07-01

    Mammals coexist with an extremely dense microbiota in the lower intestine. Despite the constant challenge of small numbers of microbes penetrating the intestinal surface epithelium, it is very unusual for these organisms to cause disease. In this review article, we present the different mucosal firewalls that contain and allow mutualism with the intestinal microbiota.

  20. The MMI Device Ontology: Enabling Sensor Integration

    Science.gov (United States)

    Rueda, C.; Galbraith, N.; Morris, R. A.; Bermudez, L. E.; Graybeal, J.; Arko, R. A.; Mmi Device Ontology Working Group

    2010-12-01

    The Marine Metadata Interoperability (MMI) project has developed an ontology for devices to describe sensors and sensor networks. This ontology is implemented in the W3C Web Ontology Language (OWL) and provides an extensible conceptual model and controlled vocabularies for describing heterogeneous instrument types, with different data characteristics, and their attributes. It can help users populate metadata records for sensors; associate devices with their platforms, deployments, measurement capabilities and restrictions; aid in discovery of sensor data, both historic and real-time; and improve the interoperability of observational oceanographic data sets. We developed the MMI Device Ontology following a community-based approach. By building on and integrating other models and ontologies from related disciplines, we sought to facilitate semantic interoperability while avoiding duplication. Key concepts and insights from various communities, including the Open Geospatial Consortium (eg., SensorML and Observations and Measurements specifications), Semantic Web for Earth and Environmental Terminology (SWEET), and W3C Semantic Sensor Network Incubator Group, have significantly enriched the development of the ontology. Individuals ranging from instrument designers, science data producers and consumers to ontology specialists and other technologists contributed to the work. Applications of the MMI Device Ontology are underway for several community use cases. These include vessel-mounted multibeam mapping sonars for the Rolling Deck to Repository (R2R) program and description of diverse instruments on deepwater Ocean Reference Stations for the OceanSITES program. These trials involve creation of records completely describing instruments, either by individual instances or by manufacturer and model. Individual terms in the MMI Device Ontology can be referenced with their corresponding Uniform Resource Identifiers (URIs) in sensor-related metadata specifications (e

  1. Ontologies and tag-statistics

    Science.gov (United States)

    Tibély, Gergely; Pollner, Péter; Vicsek, Tamás; Palla, Gergely

    2012-05-01

    Due to the increasing popularity of collaborative tagging systems, the research on tagged networks, hypergraphs, ontologies, folksonomies and other related concepts is becoming an important interdisciplinary area with great potential and relevance for practical applications. In most collaborative tagging systems the tagging by the users is completely ‘flat’, while in some cases they are allowed to define a shallow hierarchy for their own tags. However, usually no overall hierarchical organization of the tags is given, and one of the interesting challenges of this area is to provide an algorithm generating the ontology of the tags from the available data. In contrast, there are also other types of tagged networks available for research, where the tags are already organized into a directed acyclic graph (DAG), encapsulating the ‘is a sub-category of’ type of hierarchy between each other. In this paper, we study how this DAG affects the statistical distribution of tags on the nodes marked by the tags in various real networks. The motivation for this research was the fact that understanding the tagging based on a known hierarchy can help in revealing the hidden hierarchy of tags in collaborative tagging systems. We analyse the relation between the tag-frequency and the position of the tag in the DAG in two large sub-networks of the English Wikipedia and a protein-protein interaction network. We also study the tag co-occurrence statistics by introducing a two-dimensional (2D) tag-distance distribution preserving both the difference in the levels and the absolute distance in the DAG for the co-occurring pairs of tags. Our most interesting finding is that the local relevance of tags in the DAG (i.e. their rank or significance as characterized by, e.g., the length of the branches starting from them) is much more important than their global distance from the root. Furthermore, we also introduce a simple tagging model based on random walks on the DAG, capable of

  2. Ontologies and tag-statistics

    International Nuclear Information System (INIS)

    Tibély, Gergely; Vicsek, Tamás; Pollner, Péter; Palla, Gergely

    2012-01-01

    Due to the increasing popularity of collaborative tagging systems, the research on tagged networks, hypergraphs, ontologies, folksonomies and other related concepts is becoming an important interdisciplinary area with great potential and relevance for practical applications. In most collaborative tagging systems the tagging by the users is completely ‘flat’, while in some cases they are allowed to define a shallow hierarchy for their own tags. However, usually no overall hierarchical organization of the tags is given, and one of the interesting challenges of this area is to provide an algorithm generating the ontology of the tags from the available data. In contrast, there are also other types of tagged networks available for research, where the tags are already organized into a directed acyclic graph (DAG), encapsulating the ‘is a sub-category of’ type of hierarchy between each other. In this paper, we study how this DAG affects the statistical distribution of tags on the nodes marked by the tags in various real networks. The motivation for this research was the fact that understanding the tagging based on a known hierarchy can help in revealing the hidden hierarchy of tags in collaborative tagging systems. We analyse the relation between the tag-frequency and the position of the tag in the DAG in two large sub-networks of the English Wikipedia and a protein-protein interaction network. We also study the tag co-occurrence statistics by introducing a two-dimensional (2D) tag-distance distribution preserving both the difference in the levels and the absolute distance in the DAG for the co-occurring pairs of tags. Our most interesting finding is that the local relevance of tags in the DAG (i.e. their rank or significance as characterized by, e.g., the length of the branches starting from them) is much more important than their global distance from the root. Furthermore, we also introduce a simple tagging model based on random walks on the DAG, capable of

  3. Anthropological Component of Descartes’ Ontology

    Directory of Open Access Journals (Sweden)

    Anatolii M. Malivskyi

    2014-06-01

    Full Text Available The purpose of the article is to outline and comprehend the Descartes’ theory about anthropological component of ontology as the most important part of his philosophy. The accomplishment of this purpose covers the successive solution of the following tasks: 1 review of the research literature concerning the problem of human’s presence and the individual nature of truth; 2 emphasize the ambivalence of the basic intention of his legacy; 3 justify the thesis about constitutivity of human’s presence and comprehend passions as the form of disclosure of ontology’s anthropological component. Methodology. The use of the euristic potential of phenomenology, postpositivism and postmodernism makes it possible to emphasize the multiple-layer and multiple-meaning classical philosophy works, to comprehend the limitation and scarcity of the naïve-enlightening vision of human nature and to look for a new reception of European classics that provides the overcoming of established nihilism and pessimism concerning the interpretation of human nature. Scientific novelty. It is the first time that anthropological component of Descartes’ ontology became an object of particular attention. It previously lacked attention because of following main reasons: 1 traditional underestimating of the fact of Descartes’ legacy incompleteness as an unrealized anthropological project and 2 lack of proper attention to the individual nature of truth. The premise for its constructive overcoming is the attention to ambivalence of the basic intention and the significance of ethics in the philosopher’s legacy. His texts and research literature allow confirming the constitutive nature of human’s presence and passions as the key form of disclosure of the ontology anthropological component. Conclusions. The established tradition of interpretation the Descartes’ philosophizing nature as the filiation process of impersonal knowledge loses its cogency these days. The

  4. ANTHROPOLOGICAL COMPONENT OF DESCARTES’ ONTOLOGY

    Directory of Open Access Journals (Sweden)

    Anatolii M. Malivskyi

    2014-06-01

    Full Text Available The purpose of the article is to outline and comprehend the Descartes’ theory about anthropological component of ontology as the most important part of his philosophy. The accomplishment of this purpose covers the successive solution of the following tasks: 1 review of the research literature concerning the problem of human’s presence and the individual nature of truth; 2 emphasize the ambivalence of the basic intention of his legacy; 3 justify the thesis about constitutivity of human’s presence and comprehend passions as the form of disclosure of ontology’s anthropological component. Methodology. The use of the euristic potential of phenomenology, postpositivism and postmodernism makes it possible to emphasize the multiple-layer and multiple-meaning classical philosophy works, to comprehend the limitation and scarcity of the naïve-enlightening vision of human nature and to look for a new reception of European classics that provides the overcoming of established nihilism and pessimism concerning the interpretation of human nature. Scientific novelty. It is the first time that anthropological component of Descartes’ ontology became an object of particular attention. It previously lacked attention because of following main reasons: 1 traditional underestimating of the fact of Descartes’ legacy incompleteness as an unrealized anthropological project and 2 lack of proper attention to the individual nature of truth. The premise for its constructive overcoming is the attention to ambivalence of the basic intention and the significance of ethics in the philosopher’s legacy. His texts and research literature allow confirming the constitutive nature of human’s presence and passions as the key form of disclosure of the ontology anthropological component. Conclusions. The established tradition of interpretation the Descartes’ philosophizing nature as the filiation process of impersonal knowledge loses its cogency these days. The

  5. SPONGY (SPam ONtoloGY: Email Classification Using Two-Level Dynamic Ontology

    Directory of Open Access Journals (Sweden)

    Seongwook Youn

    2014-01-01

    Full Text Available Email is one of common communication methods between people on the Internet. However, the increase of email misuse/abuse has resulted in an increasing volume of spam emails over recent years. An experimental system has been designed and implemented with the hypothesis that this method would outperform existing techniques, and the experimental results showed that indeed the proposed ontology-based approach improves spam filtering accuracy significantly. In this paper, two levels of ontology spam filters were implemented: a first level global ontology filter and a second level user-customized ontology filter. The use of the global ontology filter showed about 91% of spam filtered, which is comparable with other methods. The user-customized ontology filter was created based on the specific user’s background as well as the filtering mechanism used in the global ontology filter creation. The main contributions of the paper are (1 to introduce an ontology-based multilevel filtering technique that uses both a global ontology and an individual filter for each user to increase spam filtering accuracy and (2 to create a spam filter in the form of ontology, which is user-customized, scalable, and modularized, so that it can be embedded to many other systems for better performance.

  6. SPONGY (SPam ONtoloGY): email classification using two-level dynamic ontology.

    Science.gov (United States)

    Youn, Seongwook

    2014-01-01

    Email is one of common communication methods between people on the Internet. However, the increase of email misuse/abuse has resulted in an increasing volume of spam emails over recent years. An experimental system has been designed and implemented with the hypothesis that this method would outperform existing techniques, and the experimental results showed that indeed the proposed ontology-based approach improves spam filtering accuracy significantly. In this paper, two levels of ontology spam filters were implemented: a first level global ontology filter and a second level user-customized ontology filter. The use of the global ontology filter showed about 91% of spam filtered, which is comparable with other methods. The user-customized ontology filter was created based on the specific user's background as well as the filtering mechanism used in the global ontology filter creation. The main contributions of the paper are (1) to introduce an ontology-based multilevel filtering technique that uses both a global ontology and an individual filter for each user to increase spam filtering accuracy and (2) to create a spam filter in the form of ontology, which is user-customized, scalable, and modularized, so that it can be embedded to many other systems for better performance.

  7. SPONGY (SPam ONtoloGY): Email Classification Using Two-Level Dynamic Ontology

    Science.gov (United States)

    2014-01-01

    Email is one of common communication methods between people on the Internet. However, the increase of email misuse/abuse has resulted in an increasing volume of spam emails over recent years. An experimental system has been designed and implemented with the hypothesis that this method would outperform existing techniques, and the experimental results showed that indeed the proposed ontology-based approach improves spam filtering accuracy significantly. In this paper, two levels of ontology spam filters were implemented: a first level global ontology filter and a second level user-customized ontology filter. The use of the global ontology filter showed about 91% of spam filtered, which is comparable with other methods. The user-customized ontology filter was created based on the specific user's background as well as the filtering mechanism used in the global ontology filter creation. The main contributions of the paper are (1) to introduce an ontology-based multilevel filtering technique that uses both a global ontology and an individual filter for each user to increase spam filtering accuracy and (2) to create a spam filter in the form of ontology, which is user-customized, scalable, and modularized, so that it can be embedded to many other systems for better performance. PMID:25254240

  8. Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing.

    Science.gov (United States)

    Liang, Chen; Sun, Jingchun; Tao, Cui

    2015-01-01

    There remain significant difficulties selecting probable candidate drugs from existing databases. We describe an ontology-oriented approach to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. We also report a case study in which we attempted to explore candidate drugs effective for bipolar disorder and epilepsy. We constructed an ontology incorporating knowledge between the two diseases and performed semantic reasoning tasks with the ontology. The results suggested 48 candidate drugs that hold promise for further breakthrough. The evaluation demonstrated the validity our approach. Our approach prioritizes the candidate drugs that have potential associations among genes, phenotypes and symptoms, and thus facilitates the data integration and drug repurposing in psychiatric disorders.

  9. The MGED Ontology: a resource for semantics-based description of microarray experiments.

    Science.gov (United States)

    Whetzel, Patricia L; Parkinson, Helen; Causton, Helen C; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Game, Laurence; Heiskanen, Mervi; Morrison, Norman; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Taylor, Chris; White, Joseph; Stoeckert, Christian J

    2006-04-01

    The generation of large amounts of microarray data and the need to share these data bring challenges for both data management and annotation and highlights the need for standards. MIAME specifies the minimum information needed to describe a microarray experiment and the Microarray Gene Expression Object Model (MAGE-OM) and resulting MAGE-ML provide a mechanism to standardize data representation for data exchange, however a common terminology for data annotation is needed to support these standards. Here we describe the MGED Ontology (MO) developed by the Ontology Working Group of the Microarray Gene Expression Data (MGED) Society. The MO provides terms for annotating all aspects of a microarray experiment from the design of the experiment and array layout, through to the preparation of the biological sample and the protocols used to hybridize the RNA and analyze the data. The MO was developed to provide terms for annotating experiments in line with the MIAME guidelines, i.e. to provide the semantics to describe a microarray experiment according to the concepts specified in MIAME. The MO does not attempt to incorporate terms from existing ontologies, e.g. those that deal with anatomical parts or developmental stages terms, but provides a framework to reference terms in other ontologies and therefore facilitates the use of ontologies in microarray data annotation. The MGED Ontology version.1.2.0 is available as a file in both DAML and OWL formats at http://mged.sourceforge.net/ontologies/index.php. Release notes and annotation examples are provided. The MO is also provided via the NCICB's Enterprise Vocabulary System (http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do). Stoeckrt@pcbi.upenn.edu Supplementary data are available at Bioinformatics online.

  10. Ontology-based representation and analysis of host-Brucella interactions.

    Science.gov (United States)

    Lin, Yu; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Biomedical ontologies are representations of classes of entities in the biomedical domain and how these classes are related in computer- and human-interpretable formats. Ontologies support data standardization and exchange and provide a basis for computer-assisted automated reasoning. IDOBRU is an ontology in the domain of Brucella and brucellosis. Brucella is a Gram-negative intracellular bacterium that causes brucellosis, the most common zoonotic disease in the world. In this study, IDOBRU is used as a platform to model and analyze how the hosts, especially host macrophages, interact with virulent Brucella strains or live attenuated Brucella vaccine strains. Such a study allows us to better integrate and understand intricate Brucella pathogenesis and host immunity mechanisms. Different levels of host-Brucella interactions based on different host cell types and Brucella strains were first defined ontologically. Three important processes of virulent Brucella interacting with host macrophages were represented: Brucella entry into macrophage, intracellular trafficking, and intracellular replication. Two Brucella pathogenesis mechanisms were ontologically represented: Brucella Type IV secretion system that supports intracellular trafficking and replication, and Brucella erythritol metabolism that participates in Brucella intracellular survival and pathogenesis. The host cell death pathway is critical to the outcome of host-Brucella interactions. For better survival and replication, virulent Brucella prevents macrophage cell death. However, live attenuated B. abortus vaccine strain RB51 induces caspase-2-mediated proinflammatory cell death. Brucella-associated cell death processes are represented in IDOBRU. The gene and protein information of 432 manually annotated Brucella virulence factors were represented using the Ontology of Genes and Genomes (OGG) and Protein Ontology (PRO), respectively. Seven inference rules were defined to capture the knowledge of host

  11. Nuclear Nonproliferation Ontology Assessment Team Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Strasburg, Jana D.; Hohimer, Ryan E.

    2012-01-01

    Final Report for the NA22 Simulations, Algorithm and Modeling (SAM) Ontology Assessment Team's efforts from FY09-FY11. The Ontology Assessment Team began in May 2009 and concluded in September 2011. During this two-year time frame, the Ontology Assessment team had two objectives: (1) Assessing the utility of knowledge representation and semantic technologies for addressing nuclear nonproliferation challenges; and (2) Developing ontological support tools that would provide a framework for integrating across the Simulation, Algorithm and Modeling (SAM) program. The SAM Program was going through a large assessment and strategic planning effort during this time and as a result, the relative importance of these two objectives changed, altering the focus of the Ontology Assessment Team. In the end, the team conducted an assessment of the state of art, created an annotated bibliography, and developed a series of ontological support tools, demonstrations and presentations. A total of more than 35 individuals from 12 different research institutions participated in the Ontology Assessment Team. These included subject matter experts in several nuclear nonproliferation-related domains as well as experts in semantic technologies. Despite the diverse backgrounds and perspectives, the Ontology Assessment team functioned very well together and aspects could serve as a model for future inter-laboratory collaborations and working groups. While the team encountered several challenges and learned many lessons along the way, the Ontology Assessment effort was ultimately a success that led to several multi-lab research projects and opened up a new area of scientific exploration within the Office of Nuclear Nonproliferation and Verification.

  12. Induction of Systemic Resistance against Insect Herbivores in Plants by Beneficial Soil Microbes

    Directory of Open Access Journals (Sweden)

    Md. Harun-Or Rashid

    2017-10-01

    Full Text Available Soil microorganisms with growth-promoting activities in plants, including rhizobacteria and rhizofungi, can improve plant health in a variety of different ways. These beneficial microbes may confer broad-spectrum resistance to insect herbivores. Here, we provide evidence that beneficial microbes modulate plant defenses against insect herbivores. Beneficial soil microorganisms can regulate hormone signaling including the jasmonic acid, ethylene and salicylic acid pathways, thereby leading to gene expression, biosynthesis of secondary metabolites, plant defensive proteins and different enzymes and volatile compounds, that may induce defenses against leaf-chewing as well as phloem-feeding insects. In this review, we discuss how beneficial microbes trigger induced systemic resistance against insects by promoting plant growth and highlight changes in plant molecular mechanisms and biochemical profiles.

  13. Assessing the practice of biomedical ontology evaluation: Gaps and opportunities.

    Science.gov (United States)

    Amith, Muhammad; He, Zhe; Bian, Jiang; Lossio-Ventura, Juan Antonio; Tao, Cui

    2018-04-01

    With the proliferation of heterogeneous health care data in the last three decades, biomedical ontologies and controlled biomedical terminologies play a more and more important role in knowledge representation and management, data integration, natural language processing, as well as decision support for health information systems and biomedical research. Biomedical ontologies and controlled terminologies are intended to assure interoperability. Nevertheless, the quality of biomedical ontologies has hindered their applicability and subsequent adoption in real-world applications. Ontology evaluation is an integral part of ontology development and maintenance. In the biomedicine domain, ontology evaluation is often conducted by third parties as a quality assurance (or auditing) effort that focuses on identifying modeling errors and inconsistencies. In this work, we first organized four categorical schemes of ontology evaluation methods in the existing literature to create an integrated taxonomy. Further, to understand the ontology evaluation practice in the biomedicine domain, we reviewed a sample of 200 ontologies from the National Center for Biomedical Ontology (NCBO) BioPortal-the largest repository for biomedical ontologies-and observed that only 15 of these ontologies have documented evaluation in their corresponding inception papers. We then surveyed the recent quality assurance approaches for biomedical ontologies and their use. We also mapped these quality assurance approaches to the ontology evaluation criteria. It is our anticipation that ontology evaluation and quality assurance approaches will be more widely adopted in the development life cycle of biomedical ontologies. Copyright © 2018 Elsevier Inc. All rights reserved.

  14. Ontology Versioning and Change Detection on the Web

    NARCIS (Netherlands)

    Klein, Michel; Fensel, Dieter; Kiryakov, Atanas; Ognyanov, Damyan

    2002-01-01

    To effectively use ontologies on the Web, it is essential that changes in ontologies are managed well. This paper analyzes the topic of ontology versioning in the context of the Web by looking at the characteristics of the version relation between ontologies and at the identification of online

  15. A Knowledge Engineering Approach to Develop Domain Ontology

    Science.gov (United States)

    Yun, Hongyan; Xu, Jianliang; Xiong, Jing; Wei, Moji

    2011-01-01

    Ontologies are one of the most popular and widespread means of knowledge representation and reuse. A few research groups have proposed a series of methodologies for developing their own standard ontologies. However, because this ontological construction concerns special fields, there is no standard method to build domain ontology. In this paper,…

  16. St. Thomas and the hilemorfic ontology

    Directory of Open Access Journals (Sweden)

    Lawrence Dewan, O.P.

    2009-06-01

    Full Text Available This article presents the relevancy of Aristotle’s hylemorphic ontology.Aristotle himself highlighted the importance and astonishing complexityof the problem of prime matter’s ontological status and he presenting thesolution in his doctrine of hylemorphism. As Saint Thomas Aquinasnoted, it is a crucial issue for philosophy because all four, hilemorfism,logic, physics and metaphysics, stand or fall depending on a correctunderstanding of the ontology of prime matter and of the kind of causalrelationship which exist between prime matter and substantial form ingenerable and corruptible substance.

  17. Hierarchical Analysis of the Omega Ontology

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, Cliff A.; Paulson, Patrick R.

    2009-12-01

    Initial delivery for mathematical analysis of the Omega Ontology. We provide an analysis of the hierarchical structure of a version of the Omega Ontology currently in use within the US Government. After providing an initial statistical analysis of the distribution of all link types in the ontology, we then provide a detailed order theoretical analysis of each of the four main hierarchical links present. This order theoretical analysis includes the distribution of components and their properties, their parent/child and multiple inheritance structure, and the distribution of their vertical ranks.

  18. Genetic engineering microbes for bioremediation/ biorecovery of uranium

    International Nuclear Information System (INIS)

    Apte, S.K.; Rao, A.S.; Appukuttan, D.; Nilgiriwala, K.S.; Acharya, C.

    2005-01-01

    Bioremediation (both bioremoval and biorecovery) of metals is considered a feasible, economic and eco-friendly alternative to chemical methods of metal extraction, particularly when the metal concentration is very low. Scanty distribution along with poor ore quality makes biomining of uranium an attractive preposition. Biosorption, bioprecipitation or bioaccumulation of uranium, aided by recombinant DNA technology, offer a promising technology for recovery of uranium from acidic or alkaline nuclear waste, tailings or from sea-water. Genetic engineering of bacteria, with a gene encoding an acid phosphatase, has yielded strains that can bioprecipitate uranium from very low concentrations at acidic-neutral pH, in a relatively short time. Organisms overproducing alkaline phosphatase have been selected for uranium precipitation from alkaline waste. Such abilities have now been transferred to the radioresistant microbe Deinococcus radiodurans to facilitate in situ bioremediation of nuclear waste, with some success. Sulfate-reducing bacteria are being characterized for bioremediation of uranium in tailings with the dual objective of uranium precipitation and reduction of sulfate to sulphide. Certain marine cyanobacteria have shown promise for uranium biosorption to extracellular polysaccharides, and intracellular accumulation involving metal sequestering metallothionin proteins. Future work is aimed at understanding the genetic basis of these abilities and to engineer them into suitable organisms subsequently. As photosynthetic, nitrogen-fixing microbes, which are considerably resistant to ionizing radiations, cyanobacteria hold considerable potential for bioremediation of nuclear waste. (author)

  19. Induction of abiotic stress tolerance in plants by endophytic microbes.

    Science.gov (United States)

    Lata, R; Chowdhury, S; Gond, S K; White, J F

    2018-04-01

    Endophytes are micro-organisms including bacteria and fungi that survive within healthy plant tissues and promote plant growth under stress. This review focuses on the potential of endophytic microbes that induce abiotic stress tolerance in plants. How endophytes promote plant growth under stressful conditions, like drought and heat, high salinity and poor nutrient availability will be discussed. The molecular mechanisms for increasing stress tolerance in plants by endophytes include induction of plant stress genes as well as biomolecules like reactive oxygen species scavengers. This review may help in the development of biotechnological applications of endophytic microbes in plant growth promotion and crop improvement under abiotic stress conditions. Increasing human populations demand more crop yield for food security while crop production is adversely affected by abiotic stresses like drought, salinity and high temperature. Development of stress tolerance in plants is a strategy to cope with the negative effects of adverse environmental conditions. Endophytes are well recognized for plant growth promotion and production of natural compounds. The property of endophytes to induce stress tolerance in plants can be applied to increase crop yields. With this review, we intend to promote application of endophytes in biotechnology and genetic engineering for the development of stress-tolerant plants. © 2018 The Society for Applied Microbiology.

  20. Formalization of taxon-based constraints to detect inconsistencies in annotation and ontology development

    Directory of Open Access Journals (Sweden)

    Mungall Christopher J

    2010-10-01

    Full Text Available Abstract Background The Gene Ontology project supports categorization of gene products according to their location of action, the molecular functions that they carry out, and the processes that they are involved in. Although the ontologies are intentionally developed to be taxon neutral, and to cover all species, there are inherent taxon specificities in some branches. For example, the process 'lactation' is specific to mammals and the location 'mitochondrion' is specific to eukaryotes. The lack of an explicit formalization of these constraints can lead to errors and inconsistencies in automated and manual annotation. Results We have formalized the taxonomic constraints implicit in some GO classes, and specified these at various levels in the ontology. We have also developed an inference system that can be used to check for violations of these constraints in annotations. Using the constraints in conjunction with the inference system, we have detected and removed errors in annotations and improved the structure of the ontology. Conclusions Detection of inconsistencies in taxon-specificity enables gradual improvement of the ontologies, the annotations, and the formalized constraints. This is progressively improving the quality of our data. The full system is available for download, and new constraints or proposed changes to constraints can be submitted online at https://sourceforge.net/tracker/?atid=605890&group_id=36855.

  1. A Hydrological Sensor Web Ontology Based on the SSN Ontology: A Case Study for a Flood

    Directory of Open Access Journals (Sweden)

    Chao Wang

    2017-12-01

    Full Text Available Accompanying the continuous development of sensor network technology, sensors worldwide are constantly producing observation data. However, the sensors and their data from different observation platforms are sometimes difficult to use collaboratively in response to natural disasters such as floods for the lack of semantics. In this paper, a hydrological sensor web ontology based on SSN ontology is proposed to describe the heterogeneous hydrological sensor web resources by importing the time and space ontology, instantiating the hydrological classes, and establishing reasoning rules. This work has been validated by semantic querying and knowledge acquiring experiments. The results demonstrate the feasibility and effectiveness of the proposed ontology and its potential to grow into a more comprehensive ontology for hydrological monitoring collaboratively. In addition, this method of ontology modeling is generally applicable to other applications and domains.

  2. An empirical analysis of ontology reuse in BioPortal.

    Science.gov (United States)

    Ochs, Christopher; Perl, Yehoshua; Geller, James; Arabandi, Sivaram; Tudorache, Tania; Musen, Mark A

    2017-07-01

    Biomedical ontologies often reuse content (i.e., classes and properties) from other ontologies. Content reuse enables a consistent representation of a domain and reusing content can save an ontology author significant time and effort. Prior studies have investigated the existence of reused terms among the ontologies in the NCBO BioPortal, but as of yet there has not been a study investigating how the ontologies in BioPortal utilize reused content in the modeling of their own content. In this study we investigate how 355 ontologies hosted in the NCBO BioPortal reuse content from other ontologies for the purposes of creating new ontology content. We identified 197 ontologies that reuse content. Among these ontologies, 108 utilize reused classes in the modeling of their own classes and 116 utilize reused properties in class restrictions. Current utilization of reuse and quality issues related to reuse are discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. The ontology-based answers (OBA) service: a connector for embedded usage of ontologies in applications.

    Science.gov (United States)

    Dönitz, Jürgen; Wingender, Edgar

    2012-01-01

    The semantic web depends on the use of ontologies to let electronic systems interpret contextual information. Optimally, the handling and access of ontologies should be completely transparent to the user. As a means to this end, we have developed a service that attempts to bridge the gap between experts in a certain knowledge domain, ontologists, and application developers. The ontology-based answers (OBA) service introduced here can be embedded into custom applications to grant access to the classes of ontologies and their relations as most important structural features as well as to information encoded in the relations between ontology classes. Thus computational biologists can benefit from ontologies without detailed knowledge about the respective ontology. The content of ontologies is mapped to a graph of connected objects which is compatible to the object-oriented programming style in Java. Semantic functions implement knowledge about the complex semantics of an ontology beyond the class hierarchy and "partOf" relations. By using these OBA functions an application can, for example, provide a semantic search function, or (in the examples outlined) map an anatomical structure to the organs it belongs to. The semantic functions relieve the application developer from the necessity of acquiring in-depth knowledge about the semantics and curation guidelines of the used ontologies by implementing the required knowledge. The architecture of the OBA service encapsulates the logic to process ontologies in order to achieve a separation from the application logic. A public server with the current plugins is available and can be used with the provided connector in a custom application in scenarios analogous to the presented use cases. The server and the client are freely available if a project requires the use of custom plugins or non-public ontologies. The OBA service and further documentation is available at http://www.bioinf.med.uni-goettingen.de/projects/oba.

  4. OntoMaven: Maven-based Ontology Development and Management of Distributed Ontology Repositories

    OpenAIRE

    Paschke, Adrian

    2013-01-01

    In collaborative agile ontology development projects support for modular reuse of ontologies from large existing remote repositories, ontology project life cycle management, and transitive dependency management are important needs. The Apache Maven approach has proven its success in distributed collaborative Software Engineering by its widespread adoption. The contribution of this paper is a new design artifact called OntoMaven. OntoMaven adopts the Maven-based development methodology and ada...

  5. PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources.

    Science.gov (United States)

    Kahanda, Indika; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa

    2015-01-01

    The human phenotype ontology (HPO) was recently developed as a standardized vocabulary for describing the phenotype abnormalities associated with human diseases. At present, only a small fraction of human protein coding genes have HPO annotations. But, researchers believe that a large portion of currently unannotated genes are related to disease phenotypes. Therefore, it is important to predict gene-HPO term associations using accurate computational methods. In this work we demonstrate the performance advantage of the structured SVM approach which was shown to be highly effective for Gene Ontology term prediction in comparison to several baseline methods. Furthermore, we highlight a collection of informative data sources suitable for the problem of predicting gene-HPO associations, including large scale literature mining data.

  6. Honey Bee Health: The Potential Role of Microbes

    Science.gov (United States)

    Microbes, are a diverse group of unicellular organisms that include bacteria, fungi, archaea, protists, and sometimes viruses. Bees carry a diverse assemblage of microbes (mostly bacteria and fungi). Very few are pathogenic; most microbes are likely commensal or even beneficial to the colony. Mic...

  7. Ontology-based multi-agent systems

    Energy Technology Data Exchange (ETDEWEB)

    Hadzic, Maja; Wongthongtham, Pornpit; Dillon, Tharam; Chang, Elizabeth [Digital Ecosystems and Business Intelligence Institute, Perth, WA (Australia)

    2009-07-01

    The Semantic web has given a great deal of impetus to the development of ontologies and multi-agent systems. Several books have appeared which discuss the development of ontologies or of multi-agent systems separately on their own. The growing interaction between agents and ontologies has highlighted the need for integrated development of these. This book is unique in being the first to provide an integrated treatment of the modeling, design and implementation of such combined ontology/multi-agent systems. It provides clear exposition of this integrated modeling and design methodology. It further illustrates this with two detailed case studies in (a) the biomedical area and (b) the software engineering area. The book is, therefore, of interest to researchers, graduate students and practitioners in the semantic web and web science area. (orig.)

  8. Learning Ontology from Object-Relational Database

    Directory of Open Access Journals (Sweden)

    Kaulins Andrejs

    2015-12-01

    Full Text Available This article describes a method of transformation of object-relational model into ontology. The offered method uses learning rules for such complex data types as object tables and collections – arrays of a variable size, as well as nested tables. Object types and their transformation into ontologies are insufficiently considered in scientific literature. This fact served as motivation for the authors to investigate this issue and to write the article on this matter. In the beginning, we acquaint the reader with complex data types and object-oriented databases. Then we describe an algorithm of transformation of complex data types into ontologies. At the end of the article, some examples of ontologies described in the OWL language are given.

  9. Randomised controlled trials in educational research: Ontological ...

    African Journals Online (AJOL)

    based practice in medical and clinical settings because they are associated with a particular ontological and epistemological perspective that is situated within a positivist world view. It assumes that environments and variables can be controlled ...

  10. Interoperability between phenotype and anatomy ontologies.

    Science.gov (United States)

    Hoehndorf, Robert; Oellrich, Anika; Rebholz-Schuhmann, Dietrich

    2010-12-15

    Phenotypic information is important for the analysis of the molecular mechanisms underlying disease. A formal ontological representation of phenotypic information can help to identify, interpret and infer phenotypic traits based on experimental findings. The methods that are currently used to represent data and information about phenotypes fail to make the semantics of the phenotypic trait explicit and do not interoperate with ontologies of anatomy and other domains. Therefore, valuable resources for the analysis of phenotype studies remain unconnected and inaccessible to automated analysis and reasoning. We provide a framework to formalize phenotypic descriptions and make their semantics explicit. Based on this formalization, we provide the means to integrate phenotypic descriptions with ontologies of other domains, in particular anatomy and physiology. We demonstrate how our framework leads to the capability to represent disease phenotypes, perform powerful queries that were not possible before and infer additional knowledge. http://bioonto.de/pmwiki.php/Main/PheneOntology.

  11. Using an ontology for network attack planning

    CSIR Research Space (South Africa)

    Van Heerden, R

    2016-09-01

    Full Text Available The modern complexity of network attacks and their counter-measures (cyber operations) requires detailed planning. This paper presents a Network Attack Planning ontology which is aimed at providing support for planning such network operations within...

  12. Ontology Enabled Generation of Embedded Web Services

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius; Zhang, Weishan; Soares, Goncalo Teofilo Afonso Pinheiro

    2008-01-01

    Web services are increasingly adopted as a service provision mechanism in pervasive computing environments. Implementing web services on networked, embedded devices raises a number of challenges, for example efficiency of web services, handling of variability and dependencies of hardware...... and software platforms, and of devices state and context changes. To address these challenges, we developed a Web service compiler, Limbo, in which Web Ontology Language (OWL) ontologies are used to make the Limbo compiler aware of its compilation context, such as targeted hardware and software. At the same...... time, knowledge on device details, platform dependencies, and resource/power consumption is built into the supporting ontologies, which are used to configure Limbo for generating resource efficient web service code. A state machine ontology is used to generate stub code to facilitate handling of state...

  13. Metadata and Ontologies in Learning Resources Design

    Science.gov (United States)

    Vidal C., Christian; Segura Navarrete, Alejandra; Menéndez D., Víctor; Zapata Gonzalez, Alfredo; Prieto M., Manuel

    Resource design and development requires knowledge about educational goals, instructional context and information about learner's characteristics among other. An important information source about this knowledge are metadata. However, metadata by themselves do not foresee all necessary information related to resource design. Here we argue the need to use different data and knowledge models to improve understanding the complex processes related to e-learning resources and their management. This paper presents the use of semantic web technologies, as ontologies, supporting the search and selection of resources used in design. Classification is done, based on instructional criteria derived from a knowledge acquisition process, using information provided by IEEE-LOM metadata standard. The knowledge obtained is represented in an ontology using OWL and SWRL. In this work we give evidence of the implementation of a Learning Object Classifier based on ontology. We demonstrate that the use of ontologies can support the design activities in e-learning.

  14. A Bayesian Network Approach to Ontology Mapping

    National Research Council Canada - National Science Library

    Pan, Rong; Ding, Zhongli; Yu, Yang; Peng, Yun

    2005-01-01

    This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web...

  15. Language and embodied consciousness: A Peircean ontological ...

    African Journals Online (AJOL)

    An ontology of language: its source and place in First Language ... knowledge they supposedly gain in school with their immediate environment and their lived .... looking stick in space looks bent at the point it enters the medium of water.

  16. The Study of the Microbes Degraded Polystyrene

    Directory of Open Access Journals (Sweden)

    Zhi-Long Tang

    2017-01-01

    Full Text Available Under the observation that Tenebrio molitor and Zophobas morio could eat polystyrene (PS, we setup the platform to screen the gut microbes of these two worms. To take advantage of that Tenebrio molitor and Zophobas morio can eat and digest polystyrene as its diet, we analyzed these special microbes with PS plate and PS turbidity system with time courses. There were two strains TM1 and ZM1 which isolated from Tenebrio molitor and Zophobas morio, and were identified by 16S rDNA sequencing. The results showed that TM1 and ZM1 were cocci-like and short rod shape Gram-negative bacteria under microscope. The PS plate and turbidity assay showed that TM1 and ZM1 could utilize polystyrene as their carbon sources. The further study of PS degraded enzyme and cloning warrants our attention that this platform will be an excellent tools to explore and solve this problem.

  17. Engineering tailored nanoparticles with microbes: quo vadis?

    Science.gov (United States)

    Prasad, Ram; Pandey, Rishikesh; Barman, Ishan

    2016-01-01

    In the quest for less toxic and cleaner methods of nanomaterials production, recent developments in the biosynthesis of nanoparticles have underscored the important role of microorganisms. Their intrinsic ability to withstand variable extremes of temperature, pressure, and pH coupled with the minimal downstream processing requirements provide an attractive route for diverse applications. Yet, controlling the dispersity and facile tuning of the morphology of the nanoparticles of desired chemical compositions remains an ongoing challenge. In this Focus Review, we critically review the advances in nanoparticle synthesis using microbes, ranging from bacteria and fungi to viruses, and discuss new insights into the cellular mechanisms of such formation that may, in the near future, allow complete control over particle morphology and functionalization. In addition to serving as paradigms for cost-effective, biocompatible, and eco-friendly synthesis, microbes hold the promise for a unique template for synthesis of tailored nanoparticles targeted at therapeutic and diagnostic platform technologies. © 2015 Wiley Periodicals, Inc.

  18. Electrifying microbes for the production of chemicals

    Directory of Open Access Journals (Sweden)

    Pier-Luc eTremblay

    2015-03-01

    Full Text Available Powering microbes with electrical energy to produce valuable chemicals such as biofuels has recently gained traction as a biosustainable strategy to reduce our dependence on oil. Microbial electrosynthesis (MES is one of the bioelectrochemical approaches developed in the last decade that could have critical impact on the current methods of chemical synthesis. MES is a process in which electroautotrophic microbes use electrical current as electron source to reduce CO2 to multicarbon organics. Electricity necessary for MES can be harvested from renewable resources such as solar energy, wind turbine or wastewater treatment processes. The net outcome is that renewable energy is stored in the covalent bonds of organic compounds synthesized from greenhouse gas. This review will discuss the future of MES and the challenges that lie ahead for its development into a mature technology.

  19. Electrifying microbes for the production of chemicals

    DEFF Research Database (Denmark)

    Tremblay, Pier-Luc; Zhang, Tian

    2015-01-01

    have critical impact on the current methods of chemical synthesis. MES is a process in which electroautotrophic microbes use electrical current as electron source to reduce CO2 to multicarbon organics. Electricity necessary for MES can be harvested from renewable resources such as solar energy, wind......Powering microbes with electrical energy to produce valuable chemicals such as biofuels has recently gained traction as a biosustainable strategy to reduce our dependence on oil. Microbial electrosynthesis (MES) is one of the bioelectrochemical approaches developed in the last decade that could...... turbine, or wastewater treatment processes. The net outcome is that renewable energy is stored in the covalent bonds of organic compounds synthesized from greenhouse gas. This review will discuss the future of MES and the challenges that lie ahead for its development into a mature technology....

  20. An Astrobiology Microbes Exhibit and Education Module

    Science.gov (United States)

    Lindstrom, Marilyn M.; Allen, Jaclyn S.; Stocco, Karen; Tobola, Kay; Olendzenski, Lorraine

    2001-01-01

    Telling the story of NASA-sponsored scientific research to the public in exhibits is best done by partnerships of scientists and museum professionals. Likewise, preparing classroom activities and training teachers to use them should be done by teams of teachers and scientists. Here we describe how we used such partnerships to develop a new astrobiology augmentation to the Microbes! traveling exhibit and a companion education module. "Additional information is contained in the original extended abstract."

  1. Making methodology a matter of process ontology

    DEFF Research Database (Denmark)

    Revsbæk, Line

    2016-01-01

    This paper presents a practice of doing qualitative interview analysis from the insights of the process ontology in G. H. Mead’s Philosophy of the Present (1932). The paper presents two cases of analyzing in the present while listening to recorded interview material eliciting researcher’s case...... study and otherwise related experiences creating case narratives inclusive of researcher’s reflexive voice. The paper presents an auto-ethnographic approach to data analysis based on process theory ontology....

  2. On the ontological emergence from quantum regime

    Energy Technology Data Exchange (ETDEWEB)

    Luty, Damian [Adam Mickiewicz University, Poznan (Poland)

    2014-07-01

    There are several views on the relation between quantum physics and theory of relativity (especially General Relativity, GR). A popular perspective is this: GR with its macroscopic gravitational effects will turn out to be a limit of a more fundamental theory which should consider discrete physics and not deal with continuity (like theory of relativity). Thus, GR will emerge from a more basic theory, which should be quantum-like. One could call this an epistemic emergence view towards fundamental theories. The question is, given that scientific realism is valid: should emergence be a fundamental notion in our ontological view about the evolving, physical Universe? Is there an ontological emergence fully compatible with the notion of fundamentality? I argue that if we want to defend ontological emergence (from quantum to macroscopic regime) as something fundamental, we will arrive at the position of metaphysics of dispositions (and I argue, why this is undesirable), or conclude, that we cannot square fully fundamental ontology with the notion of emergence, and that we have to accept an ontological pluralism relativised to a certain scale. I defend the latter proposition, showing, that epistemic emergence doesn't entail (logically) ontological emergence.

  3. An ontology for major histocompatibility restriction.

    Science.gov (United States)

    Vita, Randi; Overton, James A; Seymour, Emily; Sidney, John; Kaufman, Jim; Tallmadge, Rebecca L; Ellis, Shirley; Hammond, John; Butcher, Geoff W; Sette, Alessandro; Peters, Bjoern

    2016-01-01

    MHC molecules are a highly diverse family of proteins that play a key role in cellular immune recognition. Over time, different techniques and terminologies have been developed to identify the specific type(s) of MHC molecule involved in a specific immune recognition context. No consistent nomenclature exists across different vertebrate species. To correctly represent MHC related data in The Immune Epitope Database (IEDB), we built upon a previously established MHC ontology and created an ontology to represent MHC molecules as they relate to immunological experiments. This ontology models MHC protein chains from 16 species, deals with different approaches used to identify MHC, such as direct sequencing verses serotyping, relates engineered MHC molecules to naturally occurring ones, connects genetic loci, alleles, protein chains and multi-chain proteins, and establishes evidence codes for MHC restriction. Where available, this work is based on existing ontologies from the OBO foundry. Overall, representing MHC molecules provides a challenging and practically important test case for ontology building, and could serve as an example of how to integrate other ontology building efforts into web resources.

  4. The Development of Ontology from Multiple Databases

    Science.gov (United States)

    Kasim, Shahreen; Aswa Omar, Nurul; Fudzee, Mohd Farhan Md; Azhar Ramli, Azizul; Aizi Salamat, Mohamad; Mahdin, Hairulnizam

    2017-08-01

    The area of halal industry is the fastest growing global business across the world. The halal food industry is thus crucial for Muslims all over the world as it serves to ensure them that the food items they consume daily are syariah compliant. Currently, ontology has been widely used in computer sciences area such as web on the heterogeneous information processing, semantic web, and information retrieval. However, ontology has still not been used widely in the halal industry. Today, Muslim community still have problem to verify halal status for products in the market especially foods consisting of E number. This research tried to solve problem in validating the halal status from various halal sources. There are various chemical ontology from multilple databases found to help this ontology development. The E numbers in this chemical ontology are codes for chemicals that can be used as food additives. With this E numbers ontology, Muslim community could identify and verify the halal status effectively for halal products in the market.

  5. Engineered microbes and methods for microbial oil production

    Energy Technology Data Exchange (ETDEWEB)

    Stephanopoulos, Gregory; Tai, Mitchell; Chakraborty, Sagar

    2018-01-09

    Some aspects of this invention provide engineered microbes for oil production. Methods for microbe engineering and for use of engineered microbes are also provided herein. In some embodiments, microbes are provided that are engineered to modulate a combination of rate-controlling steps of lipid synthesis, for example, a combination of a step generating metabolites, acetyl-CoA, ATP or NADPH for lipid synthesis (a push step), and a step sequestering a product or an intermediate of a lipid synthesis pathway that mediates feedback inhibition of lipid synthesis (a pull step). Such push-and-pull engineered microbes exhibit greatly enhanced conversion yields and TAG synthesis and storage properties.

  6. Engineered microbes and methods for microbial oil production

    Science.gov (United States)

    Stephanopoulos, Gregory; Tai, Mitchell; Chakraborty, Sagar

    2015-02-10

    Some aspects of this invention provide engineered microbes for oil production. Methods for microbe engineering and for use of engineered microbes are also provided herein. In some embodiments, microbes are provided that are engineered to modulate a combination of rate-controlling steps of lipid synthesis, for example, a combination of a step generating metabolites, acetyl-CoA, ATP or NADPH for lipid synthesis (a push step), and a step sequestering a product or an intermediate of a lipid synthesis pathway that mediates feedback inhibition of lipid synthesis (a pull step). Such push-and-pull engineered microbes exhibit greatly enhanced conversion yields and TAG synthesis and storage properties.

  7. COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance.

    Science.gov (United States)

    Cui, Licong

    Biomedical ontologies play a vital role in healthcare information management, data integration, and decision support. Ontology quality assurance (OQA) is an indispensable part of the ontology engineering cycle. Most existing OQA methods are based on the knowledge provided within the targeted ontology. This paper proposes a novel cross-ontology analysis method, Cross-Ontology Hierarchical Relation Examination (COHeRE), to detect inconsistencies and possible errors in hierarchical relations across multiple ontologies. COHeRE leverages the Unified Medical Language System (UMLS) knowledge source and the MapReduce cloud computing technique for systematic, large-scale ontology quality assurance work. COHeRE consists of three main steps with the UMLS concepts and relations as the input. First, the relations claimed in source vocabularies are filtered and aggregated for each pair of concepts. Second, inconsistent relations are detected if a concept pair is related by different types of relations in different source vocabularies. Finally, the uncovered inconsistent relations are voted according to their number of occurrences across different source vocabularies. The voting result together with the inconsistent relations serve as the output of COHeRE for possible ontological change. The highest votes provide initial suggestion on how such inconsistencies might be fixed. In UMLS, 138,987 concept pairs were found to have inconsistent relationships across multiple source vocabularies. 40 inconsistent concept pairs involving hierarchical relationships were randomly selected and manually reviewed by a human expert. 95.8% of the inconsistent relations involved in these concept pairs indeed exist in their source vocabularies rather than being introduced by mistake in the UMLS integration process. 73.7% of the concept pairs with suggested relationship were agreed by the human expert. The effectiveness of COHeRE indicates that UMLS provides a promising environment to enhance

  8. Using Ontologies in Cybersecurity Field

    Directory of Open Access Journals (Sweden)

    Tiberiu Marian GEORGESCU

    2017-01-01

    Full Text Available This paper is an exploratory research which aims to improve the cybersecurity field by means of semantic web technologies. The authors present a framework which uses Semantic Web technologies to automatically extract and analyse text in natural language available online. The system provides results that are further analysed by cybersecurity experts to detect black hat hackers’ activities. The authors examine several characteristics of how hacking communities communicate and collaborate online and how much information can be obtained by analysing different types of internet text communication channels. Having online sources as input data, the model proposed extracts and analyses natural language that relates with cybersecurity field, with the aid of ontologies. The main objective is to generate information about possible black hat hacking actions, which later can be analysed punctually by experts. This paper describes the data flow of the framework and it proposes technological solutions so that the model can be applied. In their future work, the authors plan to implement the framework described as a system software application.

  9. Transcriptomic profiling of microbe-microbe interactions reveals the specific response of the biocontrol strain P. fluorescens In5 to the phytopathogen Rhizoctonia solani

    DEFF Research Database (Denmark)

    Hennessy, Rosanna Catherine; Glaring, Mikkel Andreas; Olsson, Stefan

    2017-01-01

    reads per sample. RESULTS: No significant changes in global gene expression were recorded during dual-culture of P. fluorescens In5 with any of the two pathogens but rather each pathogen appeared to induce expression of a specific set of genes. A particularly strong transcriptional response to R. solani...... and in particular the fungus R. solani. This highlights the importance of studying microbe-microbe interactions to gain a better understanding of how different systems function in vitro and ultimately in natural systems where biocontrol agents can be used for the sustainable management of plant diseases....

  10. ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies

    DEFF Research Database (Denmark)

    Nilsson, Jørgen Fischer; Szymczak, Bartlomiej Antoni; Jensen, P.A.

    2009-01-01

    We describe principles for extracting information from texts using a so-called generative ontology in combination with syntactic analysis. Generative ontologies are introduced as semantic domains for natural language phrases. Generative ontologies extend ordinary finite ontologies with rules...... for producing recursively shaped terms representing the ontological content (ontological semantics) of NL noun phrases and other phrases. We focus here on achieving a robust, often only partial, ontology-driven parsing of and ascription of semantics to a sentence in the text corpus. The aim of the ontological...... analysis is primarily to identify paraphrases, thereby achieving a search functionality beyond mere keyword search with synsets. We further envisage use of the generative ontology as a phrase-based rather than word-based browser into text corpora....

  11. Ontology Mapping Neural Network: An Approach to Learning and Inferring Correspondences among Ontologies

    Science.gov (United States)

    Peng, Yefei

    2010-01-01

    An ontology mapping neural network (OMNN) is proposed in order to learn and infer correspondences among ontologies. It extends the Identical Elements Neural Network (IENN)'s ability to represent and map complex relationships. The learning dynamics of simultaneous (interlaced) training of similar tasks interact at the shared connections of the…

  12. OIntEd: online ontology instance editor enabling a new approach to ontology development

    NARCIS (Netherlands)

    Wibisono, A.; Koning, R.; Grosso, P.; Belloum, A.; Bubak, M.; de Laat, C.

    2013-01-01

    Ontology development involves people with different background knowledge and expertise. It is an elaborate process, where sophisticated tools for experienced knowledge engineers are available. However, domain experts need simple tools that they can use to focus on ontology instantiation. In this

  13. Using an ontology pattern stack to engineer a core ontology of Accounting Information Systems

    NARCIS (Netherlands)

    Blums, Ivar; Weigand, Hans

    Although the field of Accounting Information Systems (AIS) has a long tradition, there is still a lack of a widely adopted conceptualization. In this paper, The UFO ontology patterns are regarded for application by analogy and extension in the engineering of a core ontology for AIS. The new IASB

  14. Documenting the emergence of bio-ontologies: or, why researching bioinformatics requires HPSSB.

    Science.gov (United States)

    Leonelli, Sabina

    2010-01-01

    This paper reflects on the analytic challenges emerging from the study of bioinformatic tools recently created to store and disseminate biological data, such as databases, repositories, and bio-ontologies. I focus my discussion on the Gene Ontology, a term that defines three entities at once: a classification system facilitating the distribution and use of genomic data as evidence towards new insights; an expert community specialised in the curation of those data; and a scientific institution promoting the use of this tool among experimental biologists. These three dimensions of the Gene Ontology can be clearly distinguished analytically, but are tightly intertwined in practice. I suggest that this is true of all bioinformatic tools: they need to be understood simultaneously as epistemic, social, and institutional entities, since they shape the knowledge extracted from data and at the same time regulate the organisation, development, and communication of research. This viewpoint has one important implication for the methodologies used to study these tools; that is, the need to integrate historical, philosophical, and sociological approaches. I illustrate this claim through examples of misunderstandings that may result from a narrowly disciplinary study of the Gene Ontology, as I experienced them in my own research.

  15. The Cognitive Paradigm Ontology: Design and Application

    Science.gov (United States)

    Laird, Angela R.

    2013-01-01

    We present the basic structure of the Cognitive Paradigm Ontology (CogPO) for human behavioral experiments. While the experimental psychology and cognitive neuroscience literature may refer to certain behavioral tasks by name (e.g., the Stroop paradigm or the Sternberg paradigm) or by function (a working memory task, a visual attention task), these paradigms can vary tremendously in the stimuli that are presented to the subject, the response expected from the subject, and the instructions given to the subject. Drawing from the taxonomy developed and used by the BrainMap project (www.brainmap.org) for almost two decades to describe key components of published functional imaging results, we have developed an ontology capable of representing certain characteristics of the cognitive paradigms used in the fMRI and PET literature. The Cognitive Paradigm Ontology is being developed to be compliant with the Basic Formal Ontology (BFO), and to harmonize where possible with larger ontologies such as RadLex, NeuroLex, or the Ontology of Biomedical Investigations (OBI). The key components of CogPO include the representation of experimental conditions focused on the stimuli presented, the instructions given, and the responses requested. The use of alternate and even competitive terminologies can often impede scientific discoveries. Categorization of paradigms according to stimulus, response, and instruction has been shown to allow advanced data retrieval techniques by searching for similarities and contrasts across multiple paradigm levels. The goal of CogPO is to develop, evaluate, and distribute a domain ontology of cognitive paradigms for application and use in the functional neuroimaging community. PMID:21643732

  16. GFVO: the Genomic Feature and Variation Ontology

    KAUST Repository

    Baran, Joachim

    2015-05-05

    Falling costs in genomic laboratory experiments have led to a steady increase of genomic feature and variation data. Multiple genomic data formats exist for sharing these data, and whilst they are similar, they are addressing slightly different data viewpoints and are consequently not fully compatible with each other. The fragmentation of data format specifications makes it hard to integrate and interpret data for further analysis with information from multiple data providers. As a solution, a new ontology is presented here for annotating and representing genomic feature and variation dataset contents. The Genomic Feature and Variation Ontology (GFVO) specifically addresses genomic data as it is regularly shared using the GFF3 (incl. FASTA), GTF, GVF and VCF file formats. GFVO simplifies data integration and enables linking of genomic annotations across datasets through common semantics of genomic types and relations. Availability and implementation. The latest stable release of the ontology is available via its base URI; previous and development versions are available at the ontology’s GitHub repository: https://github.com/BioInterchange/Ontologies; versions of the ontology are indexed through BioPortal (without external class-/property-equivalences due to BioPortal release 4.10 limitations); examples and reference documentation is provided on a separate web-page: http://www.biointerchange.org/ontologies.html. GFVO version 1.0.2 is licensed under the CC0 1.0 Universal license (https://creativecommons.org/publicdomain/zero/1.0) and therefore de facto within the public domain; the ontology can be appropriated without attribution for commercial and non-commercial use.

  17. Process attributes in bio-ontologies

    Directory of Open Access Journals (Sweden)

    Andrade André Q

    2012-08-01

    Full Text Available Abstract Background Biomedical processes can provide essential information about the (mal- functioning of an organism and are thus frequently represented in biomedical terminologies and ontologies, including the GO Biological Process branch. These processes often need to be described and categorised in terms of their attributes, such as rates or regularities. The adequate representation of such process attributes has been a contentious issue in bio-ontologies recently; and domain ontologies have correspondingly developed ad hoc workarounds that compromise interoperability and logical consistency. Results We present a design pattern for the representation of process attributes that is compatible with upper ontology frameworks such as BFO and BioTop. Our solution rests on two key tenets: firstly, that many of the sorts of process attributes which are biomedically interesting can be characterised by the ways that repeated parts of such processes constitute, in combination, an overall process; secondly, that entities for which a full logical definition can be assigned do not need to be treated as primitive within a formal ontology framework. We apply this approach to the challenge of modelling and automatically classifying examples of normal and abnormal rates and patterns of heart beating processes, and discuss the expressivity required in the underlying ontology representation language. We provide full definitions for process attributes at increasing levels of domain complexity. Conclusions We show that a logical definition of process attributes is feasible, though limited by the expressivity of DL languages so that the creation of primitives is still necessary. This finding may endorse current formal upper-ontology frameworks as a way of ensuring consistency, interoperability and clarity.

  18. Application of Ontologies for Big Earth Data

    Science.gov (United States)

    Huang, T.; Chang, G.; Armstrong, E. M.; Boening, C.

    2014-12-01

    Connected data is smarter data! Earth Science research infrastructure must do more than just being able to support temporal, geospatial discovery of satellite data. As the Earth Science data archives continue to expand across NASA data centers, the research communities are demanding smarter data services. A successful research infrastructure must be able to present researchers the complete picture, that is, datasets with linked citations, related interdisciplinary data, imageries, current events, social media discussions, and scientific data tools that are relevant to the particular dataset. The popular Semantic Web for Earth and Environmental Terminology (SWEET) ontologies is a collection of ontologies and concepts designed to improve discovery and application of Earth Science data. The SWEET ontologies collection was initially developed to capture the relationships between keywords in the NASA Global Change Master Directory (GCMD). Over the years this popular ontologies collection has expanded to cover over 200 ontologies and 6000 concepts to enable scalable classification of Earth system science concepts and Space science. This presentation discusses the semantic web technologies as the enabling technology for data-intensive science. We will discuss the application of the SWEET ontologies as a critical component in knowledge-driven research infrastructure for some of the recent projects, which include the DARPA Ontological System for Context Artifact and Resources (OSCAR), 2013 NASA ACCESS Virtual Quality Screening Service (VQSS), and the 2013 NASA Sea Level Change Portal (SLCP) projects. The presentation will also discuss the benefits in using semantic web technologies in developing research infrastructure for Big Earth Science Data in an attempt to "accommodate all domains and provide the necessary glue for information to be cross-linked, correlated, and discovered in a semantically rich manner." [1] [1] Savas Parastatidis: A platform for all that we know

  19. Linking plant nutritional status to plant-microbe interactions.

    Science.gov (United States)

    Carvalhais, Lilia C; Dennis, Paul G; Fan, Ben; Fedoseyenko, Dmitri; Kierul, Kinga; Becker, Anke; von Wiren, Nicolaus; Borriss, Rainer

    2013-01-01

    Plants have developed a wide-range of adaptations to overcome nutrient limitation, including changes to the quantity and composition of carbon-containing compounds released by roots. Root-associated bacteria are largely influenced by these compounds which can be perceived as signals or substrates. Here, we evaluate the effect of root exudates collected from maize plants grown under nitrogen (N), phosphate (P), iron (Fe) and potassium (K) deficiencies on the transcriptome of the plant growth promoting rhizobacterium (PGPR) Bacillus amyloliquefaciens FZB42. The largest shifts in gene expression patterns were observed in cells exposed to exudates from N-, followed by P-deficient plants. Exudates from N-deprived maize triggered a general stress response in FZB42 in the exponential growth phase, which was evidenced by the suppression of numerous genes involved in protein synthesis. Exudates from P-deficient plants induced bacterial genes involved in chemotaxis and motility whilst exudates released by Fe and K deficient plants did not cause dramatic changes in the bacterial transcriptome during exponential growth phase. Global transcriptional changes in bacteria elicited by nutrient deficient maize exudates were significantly correlated with concentrations of the amino acids aspartate, valine and glutamate in root exudates suggesting that transcriptional profiling of FZB42 associated with metabolomics of N, P, Fe and K-deficient maize root exudates is a powerful approach to better understand plant-microbe interactions under conditions of nutritional stress.

  20. Ion Channel ElectroPhysiology Ontology (ICEPO) - a case study of text mining assisted ontology development.

    Science.gov (United States)

    Elayavilli, Ravikumar Komandur; Liu, Hongfang

    2016-01-01

    Computational modeling of biological cascades is of great interest to quantitative biologists. Biomedical text has been a rich source for quantitative information. Gathering quantitative parameters and values from biomedical text is one significant challenge in the early steps of computational modeling as it involves huge manual effort. While automatically extracting such quantitative information from bio-medical text may offer some relief, lack of ontological representation for a subdomain serves as impedance in normalizing textual extractions to a standard representation. This may render textual extractions less meaningful to the domain experts. In this work, we propose a rule-based approach to automatically extract relations involving quantitative data from biomedical text describing ion channel electrophysiology. We further translated the quantitative assertions extracted through text mining to a formal representation that may help in constructing ontology for ion channel events using a rule based approach. We have developed Ion Channel ElectroPhysiology Ontology (ICEPO) by integrating the information represented in closely related ontologies such as, Cell Physiology Ontology (CPO), and Cardiac Electro Physiology Ontology (CPEO) and the knowledge provided by domain experts. The rule-based system achieved an overall F-measure of 68.93% in extracting the quantitative data assertions system on an independently annotated blind data set. We further made an initial attempt in formalizing the quantitative data assertions extracted from the biomedical text into a formal representation that offers potential to facilitate the integration of text mining into ontological workflow, a novel aspect of this study. This work is a case study where we created a platform that provides formal interaction between ontology development and text mining. We have achieved partial success in extracting quantitative assertions from the biomedical text and formalizing them in ontological

  1. Leave-two-out stability of ontology learning algorithm

    International Nuclear Information System (INIS)

    Wu, Jianzhang; Yu, Xiao; Zhu, Linli; Gao, Wei

    2016-01-01

    Ontology is a semantic analysis and calculation model, which has been applied to many subjects. Ontology similarity calculation and ontology mapping are employed as machine learning approaches. The purpose of this paper is to study the leave-two-out stability of ontology learning algorithm. Several leave-two-out stabilities are defined in ontology learning setting and the relationship among these stabilities are presented. Furthermore, the results manifested reveal that leave-two-out stability is a sufficient and necessary condition for ontology learning algorithm.

  2. Product line based ontology development for semantic web service

    DEFF Research Database (Denmark)

    Zhang, Weishan; Kunz, Thomas

    2006-01-01

    Ontology is recognized as a key technology for the success of the Semantic Web. Building reusable and evolve-able ontologies in order to cope with ontology evolution and requirement changes is increasingly important. But the existing methodologies and tools fail to support effective ontology reuse...... will lead to the initial implementation of the meta-onotologies using design by reuse and with the objective of design for reuse. After that step new ontologies could be generated by reusing these meta-ontologies. We demonstrate our approach with a Semantic Web Service application to show how to build...

  3. A methodology for creating ontologies for engineering design

    DEFF Research Database (Denmark)

    Ahmed, Saeema; Kim, S.; Wallace, K.M.

    2007-01-01

    This paper describes a six-stage methodology for developing ontologies for engineering design, together with the research methods and evaluation of each stage. The methodology focuses upon understanding a user's domain models through empirical research. A case study of an ontology for searching......, indexing, and retrieving engineering knowledge is described. The root concepts of the ontology were elicited from engineering designers. Relationships between concepts are extracted as the ontology is populated. The contribution of this research is a methodology to allow researchers. and industry to create...... ontologies for their particular purpose and a thesaurus for the terms within the ontology....

  4. Roles and Importance of Microbes in the Radioactive Waste Disposal

    International Nuclear Information System (INIS)

    Baik, Min Hoon; Lee, Seung Yeop; Roh, Yeol

    2009-01-01

    Recently the importance and interest for the microbes has been increased because several important results for the effects of microbes on the radioactive waste disposal have been published continuously. In this study, research status and major results on the various roles and effects of microbes in the radioactive waste disposal have been investigated. We investigated and summarized the roles and major results of microbes in a multi-barrier system consisting of an engineered barrier and a natural barrier which is considered in radioactive waste disposal systems. For the engineered barrier, we discussed about the effects of microbes on the corrosion of a waste container and investigated the survival possibility and roles of microbes in a compacted bentonite buffer. For the natural barrier, the roles of microbes present in groundwaters and rocks were discussed and summarized with major results from natural analogue studies. Furthermore, we investigated and summarized the roles and various interactions processes of microbes and their effects on the radionuclide migration and retardation including recent research status. Therefore, it is expected that the effects and roles of microbes on the radioactive waste disposal can be rigorously evaluated if further researches are carried out for a long-term behavior of the disposal system in the deep geological environments and for the effects of microbes on the radionuclide migration through geological media.

  5. The microbe capture experiment in space: Fluorescence microscopic detection of microbes captured by aerogel

    Science.gov (United States)

    Sugino, Tomohiro; Yokobori, Shin-Ichi; Yang, Yinjie; Kawaguchi, Yuko; Okudaira, Kyoko; Tabata, Makoto; Kawai, Hideyuki; Hasegawa, Sunao; Yamagishi, Akihiko

    Microbes have been collected at the altitude up to about 70 km in the sampling experiment done by several groups[1]. We have also collected high altitude microbes, by using an airplane and balloons[2][3][4][5]. We collected new deinococcal strain (Deinococcus aetherius and Deinococ-cus aerius) and several strains of spore-forming bacilli from stratosphere[2][4][5]. However, microbe sampling in space has never been reported. On the other hand, "Panspermia" hy-pothesis, where terrestrial life is originated from outside of Earth, has been proposed[6][7][8][9]. Recent report suggesting existence of the possible microbe fossils in the meteorite of Mars origin opened the serious debate on the possibility of migration of life embedded in meteorites (and cosmic dusts)[10][11]. If we were able to find terrestrial microbes in space, it would suggest that the terrestrial life can travel between astronomical bodies. We proposed a mission "Tanpopo: Astrobiology Exposure and Micrometeoroid Capture Experiments" to examine possible inter-planetary migration of microbes, organic compounds and meteoroids on Japan Experimental Module of the International Space Station (ISS)[12]. Two of six sub themes in this mission are directly related to interplanetary migration of microbes. One is the direct capturing experi-ment of microbes (probably within the particles such as clay) in space by the exposed ultra-low density aerogel. Another is the exposure experiment to examine survivability of the microbes in harsh space environment. They will tell us the possibility of interplanetary migration of microbes (life) from Earth to outside of Earth (or vise versa). In this report, we will report whether aerogel that have been used for the collection of space debris and cosmic dusts can be used for microbe sampling in space. We will discuss how captured particles by aerogel can be detected with DNA-specific fluorescent dye, and how to distinguish microbes from other mate-rials (i.e. aerogel and

  6. Integrating systems biology models and biomedical ontologies.

    Science.gov (United States)

    Hoehndorf, Robert; Dumontier, Michel; Gennari, John H; Wimalaratne, Sarala; de Bono, Bernard; Cook, Daniel L; Gkoutos, Georgios V

    2011-08-11

    Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

  7. Validating EHR clinical models using ontology patterns.

    Science.gov (United States)

    Martínez-Costa, Catalina; Schulz, Stefan

    2017-12-01

    Clinical models are artefacts that specify how information is structured in electronic health records (EHRs). However, the makeup of clinical models is not guided by any formal constraint beyond a semantically vague information model. We address this gap by advocating ontology design patterns as a mechanism that makes the semantics of clinical models explicit. This paper demonstrates how ontology design patterns can validate existing clinical models using SHACL. Based on the Clinical Information Modelling Initiative (CIMI), we show how ontology patterns detect both modeling and terminology binding errors in CIMI models. SHACL, a W3C constraint language for the validation of RDF graphs, builds on the concept of "Shape", a description of data in terms of expected cardinalities, datatypes and other restrictions. SHACL, as opposed to OWL, subscribes to the Closed World Assumption (CWA) and is therefore more suitable for the validation of clinical models. We have demonstrated the feasibility of the approach by manually describing the correspondences between six CIMI clinical models represented in RDF and two SHACL ontology design patterns. Using a Java-based SHACL implementation, we found at least eleven modeling and binding errors within these CIMI models. This demonstrates the usefulness of ontology design patterns not only as a modeling tool but also as a tool for validation. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Where the Wild Microbes Are: Education and Outreach on Sub-Seafloor Microbes

    Science.gov (United States)

    Cooper, S. K.; Kurtz, K.; Orcutt, B.; Strong, L.; Collins, J.; Feagan, A.

    2014-12-01

    Sub-seafloor microbiology has the power to spark the imaginations of children, students and the general public with its mysterious nature, cutting-edge research, and connections to the search for extraterrestrial life. These factors have been utilized to create a number of educational and outreach products to bring subsurface microbes to non-scientist audiences in creative and innovative ways. The Adopt a Microbe curriculum for middle school students provides hands-on activities and investigations for students to learn about microbes and the on-going research about them, and provides opportunities to connect with active expeditions. A new series of videos engages non-scientists with stories about research expeditions and the scientists themselves. A poster and associated activities explore the nature of science using a microbiologist and her research as examples. A new e-book for young children will engage them with age-appropriate text and illustrations. These projects are multidisciplinary, involve science and engineering practices, are available to all audiences and provide examples of high level and meaningful partnerships between scientists and educators and the kinds of products that can result. Subseafloor microbiology projects such as these, aimed at K-12 students and the general public, have the potential to entice the interest of the next generation of microbe scientists and increase general awareness of this important science.

  9. Functional metagenomics to decipher food-microbe-host crosstalk.

    Science.gov (United States)

    Larraufie, Pierre; de Wouters, Tomas; Potocki-Veronese, Gabrielle; Blottière, Hervé M; Doré, Joël

    2015-02-01

    The recent developments of metagenomics permit an extremely high-resolution molecular scan of the intestinal microbiota giving new insights and opening perspectives for clinical applications. Beyond the unprecedented vision of the intestinal microbiota given by large-scale quantitative metagenomics studies, such as the EU MetaHIT project, functional metagenomics tools allow the exploration of fine interactions between food constituents, microbiota and host, leading to the identification of signals and intimate mechanisms of crosstalk, especially between bacteria and human cells. Cloning of large genome fragments, either from complex intestinal communities or from selected bacteria, allows the screening of these biological resources for bioactivity towards complex plant polymers or functional food such as prebiotics. This permitted identification of novel carbohydrate-active enzyme families involved in dietary fibre and host glycan breakdown, and highlighted unsuspected bacterial players at the top of the intestinal microbial food chain. Similarly, exposure of fractions from genomic and metagenomic clones onto human cells engineered with reporter systems to track modulation of immune response, cell proliferation or cell metabolism has allowed the identification of bioactive clones modulating key cell signalling pathways or the induction of specific genes. This opens the possibility to decipher mechanisms by which commensal bacteria or candidate probiotics can modulate the activity of cells in the intestinal epithelium or even in distal organs such as the liver, adipose tissue or the brain. Hence, in spite of our inability to culture many of the dominant microbes of the human intestine, functional metagenomics open a new window for the exploration of food-microbe-host crosstalk.

  10. Toward a formal ontology for narrative

    Directory of Open Access Journals (Sweden)

    Ciotti, Fabio

    2016-03-01

    Full Text Available In this paper the rationale and the first draft of a formal ontology for modeling narrative texts are presented. Building on the semiotic and structuralist narratology, and on the work carried out in the late 1980s by Giuseppe Gigliozzi in Italy, the focus of my research are the concepts of character and of narrative world/space. This formal model is expressed in the OWL 2 ontology language. The main reason to adopt a formal modeling approach is that I consider the purely probabilistic-quantitative methods (now widespread in digital literary studies inadequate. An ontology, on one hand provides a tool for the analysis of strictly literary texts. On the other hand (though beyond the scope of the present work, its formalization can also represent a significant contribution towards grounding the application of storytelling methods outside of scholarly contexts.

  11. A Formal Theory for Modular ERDF Ontologies

    Science.gov (United States)

    Analyti, Anastasia; Antoniou, Grigoris; Damásio, Carlos Viegas

    The success of the Semantic Web is impossible without any form of modularity, encapsulation, and access control. In an earlier paper, we extended RDF graphs with weak and strong negation, as well as derivation rules. The ERDF #n-stable model semantics of the extended RDF framework (ERDF) is defined, extending RDF(S) semantics. In this paper, we propose a framework for modular ERDF ontologies, called modular ERDF framework, which enables collaborative reasoning over a set of ERDF ontologies, while support for hidden knowledge is also provided. In particular, the modular ERDF stable model semantics of modular ERDF ontologies is defined, extending the ERDF #n-stable model semantics. Our proposed framework supports local semantics and different points of view, local closed-world and open-world assumptions, and scoped negation-as-failure. Several complexity results are provided.

  12. The Russian Quest for Ontological Security

    DEFF Research Database (Denmark)

    Pedersen, Jonas Gejl

    This paper argues that Russia’s decision to militarily intervene in the Kosovo crisis (1999) arose out of ontological, alongside material, insecurity. Whereas states’ material security essentially deals with national survival, ontological security concerns safety of the ‘national Self......’. By supplementing the existing theories of geopolitics and regime security with the conceptual lens of ontological security, my interpretivist case study demonstrates why Russia, despite great risk and material costs, decided to militarily intervene and traces how Russian senses of ‘national Self’ were...... fundamentally reconstructed during intervention. I find that the anxiety arising from a future scenario of an already weak post-Soviet ‘Russian Self’ gradually being engulfed by a confident ‘Western Self’ played a significant role in Russia’s decision to occupy Slatina airbase. My analysis paradoxically shows...

  13. Løgstrup’s Ontological Ethics

    DEFF Research Database (Denmark)

    Rabjerg, Bjørn

    2017-01-01

    aim is to provide a coherent exposition of Løgstrup’s ethics. However, the result is not a normative ethics upon which we may act, but rather a descriptive diagnosis of interdependence as the basic ontological condition of human social life, where the sovereign expressions of life may enable us to act.......The article explores K. E. Løgstrup’s ontological ethics, understood as an ethics rooted in interdependence. Interdependence, the fact that human beings always hold power over each other, has two very different aspects, which I will call negative and positive, each of them in turn leading...... to different aspects of ontological ethics. By negative and positive I mean the two opposing possibilities of all human interaction that we can either destroy the other person’s life (to a greater or smaller degree) or cause the other person’s life to flourish. We can either be a blessing in the other person’s...

  14. Designing Network-based Business Model Ontology

    DEFF Research Database (Denmark)

    Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz

    2015-01-01

    Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....

  15. Player-Specific Conflict Handling Ontology

    Directory of Open Access Journals (Sweden)

    Charline Hondrou

    2014-09-01

    Full Text Available This paper presents an ontology that leads the player of a serious game - regarding conflict handling - to the educative experience from which they will benefit the most. It provides a clearly defined tree of axioms that maps the player’s visually manifested affective cues and emotional stimuli from the serious game to conflict handling styles and proposes interventions. The importance of this ontology lies in the fact that it promotes natural interaction (non-invasive methods and at the same time makes the game as player-specific as it can be for its educational goal. It is an ontology that can be adapted to different educational theories and serve various educational purposes.

  16. Using ontology network structure in text mining.

    Science.gov (United States)

    Berndt, Donald J; McCart, James A; Luther, Stephen L

    2010-11-13

    Statistical text mining treats documents as bags of words, with a focus on term frequencies within documents and across document collections. Unlike natural language processing (NLP) techniques that rely on an engineered vocabulary or a full-featured ontology, statistical approaches do not make use of domain-specific knowledge. The freedom from biases can be an advantage, but at the cost of ignoring potentially valuable knowledge. The approach proposed here investigates a hybrid strategy based on computing graph measures of term importance over an entire ontology and injecting the measures into the statistical text mining process. As a starting point, we adapt existing search engine algorithms such as PageRank and HITS to determine term importance within an ontology graph. The graph-theoretic approach is evaluated using a smoking data set from the i2b2 National Center for Biomedical Computing, cast as a simple binary classification task for categorizing smoking-related documents, demonstrating consistent improvements in accuracy.

  17. The Porifera Ontology (PORO): enhancing sponge systematics with an anatomy ontology.

    Science.gov (United States)

    Thacker, Robert W; Díaz, Maria Cristina; Kerner, Adeline; Vignes-Lebbe, Régine; Segerdell, Erik; Haendel, Melissa A; Mungall, Christopher J

    2014-01-01

    Porifera (sponges) are ancient basal metazoans that lack organs. They provide insight into key evolutionary transitions, such as the emergence of multicellularity and the nervous system. In addition, their ability to synthesize unusual compounds offers potential biotechnical applications. However, much of the knowledge of these organisms has not previously been codified in a machine-readable way using modern web standards. The Porifera Ontology is intended as a standardized coding system for sponge anatomical features currently used in systematics. The ontology is available from http://purl.obolibrary.org/obo/poro.owl, or from the project homepage http://porifera-ontology.googlecode.com/. The version referred to in this manuscript is permanently available from http://purl.obolibrary.org/obo/poro/releases/2014-03-06/. By standardizing character representations, we hope to facilitate more rapid description and identification of sponge taxa, to allow integration with other evolutionary database systems, and to perform character mapping across the major clades of sponges to better understand the evolution of morphological features. Future applications of the ontology will focus on creating (1) ontology-based species descriptions; (2) taxonomic keys that use the nested terms of the ontology to more quickly facilitate species identifications; and (3) methods to map anatomical characters onto molecular phylogenies of sponges. In addition to modern taxa, the ontology is being extended to include features of fossil taxa.

  18. Matching disease and phenotype ontologies in the ontology alignment evaluation initiative.

    Science.gov (United States)

    Harrow, Ian; Jiménez-Ruiz, Ernesto; Splendiani, Andrea; Romacker, Martin; Woollard, Peter; Markel, Scott; Alam-Faruque, Yasmin; Koch, Martin; Malone, James; Waaler, Arild

    2017-12-02

    The disease and phenotype track was designed to evaluate the relative performance of ontology matching systems that generate mappings between source ontologies. Disease and phenotype ontologies are important for applications such as data mining, data integration and knowledge management to support translational science in drug discovery and understanding the genetics of disease. Eleven systems (out of 21 OAEI participating systems) were able to cope with at least one of the tasks in the Disease and Phenotype track. AML, FCA-Map, LogMap(Bio) and PhenoMF systems produced the top results for ontology matching in comparison to consensus alignments. The results against manually curated mappings proved to be more difficult most likely because these mapping sets comprised mostly subsumption relationships rather than equivalence. Manual assessment of unique equivalence mappings showed that AML, LogMap(Bio) and PhenoMF systems have the highest precision results. Four systems gave the highest performance for matching disease and phenotype ontologies. These systems coped well with the detection of equivalence matches, but struggled to detect semantic similarity. This deserves more attention in the future development of ontology matching systems. The findings of this evaluation show that such systems could help to automate equivalence matching in the workflow of curators, who maintain ontology mapping services in numerous domains such as disease and phenotype.

  19. Endogenous System Microbes as Treatment Process ...

    Science.gov (United States)

    Monitoring the efficacy of treatment strategies to remove pathogens in decentralized systems remains a challenge. Evaluating log reduction targets by measuring pathogen levels is hampered by their sporadic and low occurrence rates. Fecal indicator bacteria are used in centralized systems to indicate the presence of fecal pathogens, but are ineffective decentralized treatment process indicators as they generally occur at levels too low to assess log reduction targets. System challenge testing by spiking with high loads of fecal indicator organisms, like MS2 coliphage, has limitations, especially for large systems. Microbes that are endogenous to the decentralized system, occur in high abundances and mimic removal rates of bacterial, viral and/or parasitic protozoan pathogens during treatment could serve as alternative treatment process indicators to verify log reduction targets. To identify abundant microbes in wastewater, the bacterial and viral communities were examined using deep sequencing. Building infrastructure-associated bacteria, like Zoogloea, were observed as dominant members of the bacterial community in graywater. In blackwater, bacteriophage of the order Caudovirales constituted the majority of contiguous sequences from the viral community. This study identifies candidate treatment process indicators in decentralized systems that could be used to verify log removal during treatment. The association of the presence of treatment process indic

  20. MicrO: an ontology of phenotypic and metabolic characters, assays, and culture media found in prokaryotic taxonomic descriptions.

    Science.gov (United States)

    Blank, Carrine E; Cui, Hong; Moore, Lisa R; Walls, Ramona L

    2016-01-01

    MicrO is an ontology of microbiological terms, including prokaryotic qualities and processes, material entities (such as cell components), chemical entities (such as microbiological culture media and medium ingredients), and assays. The ontology was built to support the ongoing development of a natural language processing algorithm, MicroPIE (or, Microbial Phenomics Information Extractor). During the MicroPIE design process, we realized there was a need for a prokaryotic ontology which would capture the evolutionary diversity of phenotypes and metabolic processes across the tree of life, capture the diversity of synonyms and information contained in the taxonomic literature, and relate microbiological entities and processes to terms in a large number of other ontologies, most particularly the Gene Ontology (GO), the Phenotypic Quality Ontology (PATO), and the Chemical Entities of Biological Interest (ChEBI). We thus constructed MicrO to be rich in logical axioms and synonyms gathered from the taxonomic literature. MicrO currently has ~14550 classes (~2550 of which are new, the remainder being microbiologically-relevant classes imported from other ontologies), connected by ~24,130 logical axioms (5,446 of which are new), and is available at (http://purl.obolibrary.org/obo/MicrO.owl) and on the project website at https://github.com/carrineblank/MicrO. MicrO has been integrated into the OBO Foundry Library (http://www.obofoundry.org/ontology/micro.html), so that other ontologies can borrow and re-use classes. Term requests and user feedback can be made using MicrO's Issue Tracker in GitHub. We designed MicrO such that it can support the ongoing and future development of algorithms that can leverage the controlled vocabulary and logical inference power provided by the ontology. By connecting microbial classes with large numbers of chemical entities, material entities, biological processes, molecular functions, and qualities using a dense array of logical axioms, we

  1. A meta-ontological framework for multi-agent systems design

    OpenAIRE

    Sokolova, Marina; Fernández Caballero, Antonio

    2007-01-01

    The paper introduces an approach to using a meta-ontology framework for complex multi-agent systems design, and illustrates it in an application related to ecological-medical issues. The described shared ontology is pooled from private sub-ontologies, which represent a problem area ontology, an agent ontology, a task ontology, an ontology of interactions, and the multi-agent system architecture ontology.

  2. OAE: The Ontology of Adverse Events.

    Science.gov (United States)

    He, Yongqun; Sarntivijai, Sirarat; Lin, Yu; Xiang, Zuoshuang; Guo, Abra; Zhang, Shelley; Jagannathan, Desikan; Toldo, Luca; Tao, Cui; Smith, Barry

    2014-01-01

    A medical intervention is a medical procedure or application intended to relieve or prevent illness or injury. Examples of medical interventions include vaccination and drug administration. After a medical intervention, adverse events (AEs) may occur which lie outside the intended consequences of the intervention. The representation and analysis of AEs are critical to the improvement of public health. The Ontology of Adverse Events (OAE), previously named Adverse Event Ontology (AEO), is a community-driven ontology developed to standardize and integrate data relating to AEs arising subsequent to medical interventions, as well as to support computer-assisted reasoning. OAE has over 3,000 terms with unique identifiers, including terms imported from existing ontologies and more than 1,800 OAE-specific terms. In OAE, the term 'adverse event' denotes a pathological bodily process in a patient that occurs after a medical intervention. Causal adverse events are defined by OAE as those events that are causal consequences of a medical intervention. OAE represents various adverse events based on patient anatomic regions and clinical outcomes, including symptoms, signs, and abnormal processes. OAE has been used in the analysis of several different sorts of vaccine and drug adverse event data. For example, using the data extracted from the Vaccine Adverse Event Reporting System (VAERS), OAE was used to analyse vaccine adverse events associated with the administrations of different types of influenza vaccines. OAE has also been used to represent and classify the vaccine adverse events cited in package inserts of FDA-licensed human vaccines in the USA. OAE is a biomedical ontology that logically defines and classifies various adverse events occurring after medical interventions. OAE has successfully been applied in several adverse event studies. The OAE ontological framework provides a platform for systematic representation and analysis of adverse events and of the factors (e

  3. Ontology-based Metadata Portal for Unified Semantics

    Data.gov (United States)

    National Aeronautics and Space Administration — The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS) will extend the prototype Ontology-Driven Interactive Search Environment for Earth Sciences...

  4. One Song, Many Works: A Pluralist Ontology of Rock

    Directory of Open Access Journals (Sweden)

    Dan Burkett

    2016-01-01

    Full Text Available A number of attempts have been made to construct a plausible ontology of rock music. Each of these ontologies identifies a single type of ontological entity as the “work” in rock music. Yet, all the suggestions advanced to date fail to capture some important considerations about how we engage with music of this tradition. This prompted Lee Brown to advocate a healthy skepticism of higher-order musical ontologies. I argue here that we should instead embrace a pluralist ontology of rock, an ontology that recognizes more than one kind of entity as “the work” in rock music. I contend that this approach has a number of advantages over other ontologies of rock, including that of allowing us to make some comparisons across ontological kinds.

  5. Prospects and Possibilities for Ontology Evaluation: The View from NCOR

    National Research Council Canada - National Science Library

    Obrst, Leo; Hughes, Todd; Ray, Steve

    2006-01-01

    ...) on ontology evaluation. NCOR's inauguration was recently held (October 2005), and at that time goals were identified and committees formed to pursue those goals, including the Ontology Evaluation Committee...

  6. 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

  7. Semi-automated ontology generation and evolution

    Science.gov (United States)

    Stirtzinger, Anthony P.; Anken, Craig S.

    2009-05-01

    Extending the notion of data models or object models, ontology can provide rich semantic definition not only to the meta-data but also to the instance data of domain knowledge, making these semantic definitions available in machine readable form. However, the generation of an effective ontology is a difficult task involving considerable labor and skill. This paper discusses an Ontology Generation and Evolution Processor (OGEP) aimed at automating this process, only requesting user input when un-resolvable ambiguous situations occur. OGEP directly attacks the main barrier which prevents automated (or self learning) ontology generation: the ability to understand the meaning of artifacts and the relationships the artifacts have to the domain space. OGEP leverages existing lexical to ontological mappings in the form of WordNet, and Suggested Upper Merged Ontology (SUMO) integrated with a semantic pattern-based structure referred to as the Semantic Grounding Mechanism (SGM) and implemented as a Corpus Reasoner. The OGEP processing is initiated by a Corpus Parser performing a lexical analysis of the corpus, reading in a document (or corpus) and preparing it for processing by annotating words and phrases. After the Corpus Parser is done, the Corpus Reasoner uses the parts of speech output to determine the semantic meaning of a word or phrase. The Corpus Reasoner is the crux of the OGEP system, analyzing, extrapolating, and evolving data from free text into cohesive semantic relationships. The Semantic Grounding Mechanism provides a basis for identifying and mapping semantic relationships. By blending together the WordNet lexicon and SUMO ontological layout, the SGM is given breadth and depth in its ability to extrapolate semantic relationships between domain entities. The combination of all these components results in an innovative approach to user assisted semantic-based ontology generation. This paper will describe the OGEP technology in the context of the architectural

  8. Ontological Model of Business Process Management Systems

    Science.gov (United States)

    Manoilov, G.; Deliiska, B.

    2008-10-01

    The activities which constitute business process management (BPM) can be grouped into five categories: design, modeling, execution, monitoring and optimization. Dedicated software packets for business process management system (BPMS) are available on the market. But the efficiency of its exploitation depends on used ontological model in the development time and run time of the system. In the article an ontological model of BPMS in area of software industry is investigated. The model building is preceded by conceptualization of the domain and taxonomy of BPMS development. On the base of the taxonomy an simple online thesaurus is created.

  9. Methodology of decreasing software complexity using ontology

    Science.gov (United States)

    DÄ browska-Kubik, Katarzyna

    2015-09-01

    In this paper a model of web application`s source code, based on the OSD ontology (Ontology for Software Development), is proposed. This model is applied to implementation and maintenance phase of software development process through the DevOntoCreator tool [5]. The aim of this solution is decreasing software complexity of that source code, using many different maintenance techniques, like creation of documentation, elimination dead code, cloned code or bugs, which were known before [1][2]. Due to this approach saving on software maintenance costs of web applications will be possible.

  10. Ontology-Based Model Of Firm Competitiveness

    Science.gov (United States)

    Deliyska, Boryana; Stoenchev, Nikolay

    2010-10-01

    Competitiveness is important characteristics of each business organization (firm, company, corporation etc). It is of great significance for the organization existence and defines evaluation criteria of business success at microeconomical level. Each criterium comprises set of indicators with specific weight coefficients. In the work an ontology-based model of firm competitiveness is presented as a set of several mutually connected ontologies. It would be useful for knowledge structuring, standardization and sharing among experts and software engineers who develop application in the domain. Then the assessment of the competitiveness of various business organizations could be generated more effectively.

  11. Applications of the ACGT Master Ontology on Cancer

    OpenAIRE

    Brochhausen, Mathias; Weiler, Gabriele; Martín Martín, Luis; Cocos, Cristian; Stenzhorn, Holger; Graf, Norbert; Dörr, Martin; Tsiknakis, Manolis; Smith, Barry

    2008-01-01

    In this paper we present applications of the ACGT Master Ontology (MO) which is a new terminology resource for a transnational network providing data exchange in oncology, emphasizing the integration of both clinical and molecular data. The development of a new ontology was necessary due to problems with existing biomedical ontologies in oncology. The ACGT MO is a test case for the application of best practices in ontology development. This paper provides an overview of the application of the...

  12. Self-adaptation of Ontologies to Folksonomies in Semantic Web

    OpenAIRE

    Francisco Echarte; José Javier Astrain; Alberto Córdoba; Jesús Villadangos

    2008-01-01

    Ontologies and tagging systems are two different ways to organize the knowledge present in the current Web. In this paper we propose a simple method to model folksonomies, as tagging systems, with ontologies. We show the scalability of the method using real data sets. The modeling method is composed of a generic ontology that represents any folksonomy and an algorithm to transform the information contained in folksonomies to the generic ontology. The method allows representing folksonomies at...

  13. A collaborative recommendation framework for ontology evaluation and reuse

    OpenAIRE

    Cantador, Iván; Fernández Sánchez, Miriam; Castells, Pablo

    2006-01-01

    This is an electronic version of the paper presented at the International Workshop on Recommender Systems, held in Riva del Garda on 2006 Ontology evaluation can be defined as assessing the quality and the adequacy of an ontology for being used in a spe-cific context, for a specific goal. Although ontology reuse is being extensively addressed by the Semantic Web community, the lack of appropriate support tools and automatic techniques for the evaluation of certain ontology features are oft...

  14. Conflict Resolution in Partially Ordered OWL DL Ontologies

    NARCIS (Netherlands)

    Ji, Q.; Gao, Z.; Huang, Z.

    2014-01-01

    Inconsistency handling in OWL DL ontologies is an important problem because an ontology can easily be inconsistent when it is generated or modified. Current approaches to dealing with inconsistent ontologies often assume that there exists a total order over axioms and use such an order to select

  15. Methodology for Automatic Ontology Generation Using Database Schema Information

    Directory of Open Access Journals (Sweden)

    JungHyen An

    2018-01-01

    Full Text Available An ontology is a model language that supports the functions to integrate conceptually distributed domain knowledge and infer relationships among the concepts. Ontologies are developed based on the target domain knowledge. As a result, methodologies to automatically generate an ontology from metadata that characterize the domain knowledge are becoming important. However, existing methodologies to automatically generate an ontology using metadata are required to generate the domain metadata in a predetermined template, and it is difficult to manage data that are increased on the ontology itself when the domain OWL (Ontology Web Language individuals are continuously increased. The database schema has a feature of domain knowledge and provides structural functions to efficiently process the knowledge-based data. In this paper, we propose a methodology to automatically generate ontologies and manage the OWL individual through an interaction of the database and the ontology. We describe the automatic ontology generation process with example schema and demonstrate the effectiveness of the automatically generated ontology by comparing it with existing ontologies using the ontology quality score.

  16. Construction of Engineering Ontologies for Knowledge Sharing and Reuse

    NARCIS (Netherlands)

    Borst, Willem Nico; Borst, W.N.

    1997-01-01

    This thesis describes an investigation into the practical use of ontologies for the development of information systems. Ontologies are formal descriptions of shared knowledge in a domain. An ontology can be used as a specification of an information system because it specifies the knowledge that is

  17. Six scenarios of exploiting an ontology based, mobilized learning environment

    NARCIS (Netherlands)

    Kismihók, G.; Szabó, I.; Vas, R.

    2012-01-01

    In this article, six different exploitation possibilities of an educational ontology based, mobilized learning management system are presented. The focal point of this system is the educational ontology model. The first version of this educational ontology model serves as a foundation for curriculum

  18. On Automatic Modeling and Use of Domain-specific Ontologies

    DEFF Research Database (Denmark)

    Andreasen, Troels; Knappe, Rasmus; Bulskov, Henrik

    2005-01-01

    In this paper, we firstly introduce an approach to the modeling of a domain-specific ontology for use in connection with a given document collection. Secondly, we present a methodology for deriving conceptual similarity from the domain-specific ontology. Adopted for ontology representation is a s...

  19. ContoExam: an ontology on context-aware examinations

    NARCIS (Netherlands)

    Brandt, P.; Basten, A.A.; Stuijk, S.

    2014-01-01

    Patient observations in health care, subjective surveys in social research or dyke sensor data in water management are all examples of measurements. Several ontologies already exist to express measurements, W3C's SSN ontology being a prominent example. However, these ontologies address quantities

  20. Towards Ontological Foundations for Agent Modeling Concepts using UFO

    NARCIS (Netherlands)

    Guizzardi, G.; Wagner, Gerd

    Foundational ontologies provide the basic concepts upon which any domain-specific ontology is built. This paper presents a new foundational ontology, UFO, and shows how it can be used as a foundation of agent concepts and for evaluating agent-oriented modeling methods. UFO is derived from a

  1. Menthor Editor: An Ontology-Driven Conceptual Modeling Platform

    NARCIS (Netherlands)

    Moreira, João Luiz; Sales, Tiago Prince; Guerson, John; Braga, Bernardo F.B; Brasileiro, Freddy; Sobral, Vinicius

    2016-01-01

    The lack of well-founded constructs in ontology tools can lead to the construction of non-intended models. In this demonstration we present the Menthor Editor, an ontology-driven conceptual modelling platform which incorporates the theories of the Unified Foundational Ontology (UFO). We illustrate

  2. The Relationship between User Expertise and Structural Ontology Characteristics

    Science.gov (United States)

    Waldstein, Ilya Michael

    2014-01-01

    Ontologies are commonly used to support application tasks such as natural language processing, knowledge management, learning, browsing, and search. Literature recommends considering specific context during ontology design, and highlights that a different context is responsible for problems in ontology reuse. However, there is still no clear…

  3. Developing Learning Materials Using an Ontology of Mathematical Logic

    Science.gov (United States)

    Boyatt, Russell; Joy, Mike

    2012-01-01

    Ontologies describe a body of knowledge and give formal structure to a domain by describing concepts and their relationships. The construction of an ontology provides an opportunity to develop a shared understanding and a consistent vocabulary to be used for a given activity. This paper describes the construction of an ontology for an area of…

  4. Unsupervised Ontology Generation from Unstructured Text. CRESST Report 827

    Science.gov (United States)

    Mousavi, Hamid; Kerr, Deirdre; Iseli, Markus R.

    2013-01-01

    Ontologies are a vital component of most knowledge acquisition systems, and recently there has been a huge demand for generating ontologies automatically since manual or supervised techniques are not scalable. In this paper, we introduce "OntoMiner", a rule-based, iterative method to extract and populate ontologies from unstructured or…

  5. Ontology-based intelligent fuzzy agent for diabetes application

    NARCIS (Netherlands)

    Acampora, G.; Lee, C.-S.; Wang, M.-H.; Hsu, C.-Y.; Loia, V.

    2009-01-01

    It is widely pointed out that classical ontologies are not sufficient to deal with imprecise and vague knowledge for some real world applications, but the fuzzy ontology can effectively solve data and knowledge with uncertainty. In this paper, an ontology-based intelligent fuzzy agent (OIFA),

  6. MultiFarm: A Benchmark for Multilingual Ontology Matching

    NARCIS (Netherlands)

    Meilicke, C.; García-Castro, R.; Freitas, F.; van Hage, W.R.; Montiel-Ponsoda, E.; Ribeiro de Azevedo, R.; Stuckenschmidt, H.; Svab-Zamazal, O.; Svatek, V.; Tamalin, A.; Wang, S.

    2012-01-01

    In this paper we present the MultiFarm dataset, which has been designed as a benchmark for multilingual ontology matching. The MultiFarm dataset is composed of a set of ontologies translated in different languages and the corresponding alignments between these ontologies. It is based on the OntoFarm

  7. Utilizing a structural meta-ontology for family-based quality assurance of the BioPortal ontologies.

    Science.gov (United States)

    Ochs, Christopher; He, Zhe; Zheng, Ling; Geller, James; Perl, Yehoshua; Hripcsak, George; Musen, Mark A

    2016-06-01

    An Abstraction Network is a compact summary of an ontology's structure and content. In previous research, we showed that Abstraction Networks support quality assurance (QA) of biomedical ontologies. The development of an Abstraction Network and its associated QA methodologies, however, is a labor-intensive process that previously was applicable only to one ontology at a time. To improve the efficiency of the Abstraction-Network-based QA methodology, we introduced a QA framework that uses uniform Abstraction Network derivation techniques and QA methodologies that are applicable to whole families of structurally similar ontologies. For the family-based framework to be successful, it is necessary to develop a method for classifying ontologies into structurally similar families. We now describe a structural meta-ontology that classifies ontologies according to certain structural features that are commonly used in the modeling of ontologies (e.g., object properties) and that are important for Abstraction Network derivation. Each class of the structural meta-ontology represents a family of ontologies with identical structural features, indicating which types of Abstraction Networks and QA methodologies are potentially applicable to all of the ontologies in the family. We derive a collection of 81 families, corresponding to classes of the structural meta-ontology, that enable a flexible, streamlined family-based QA methodology, offering multiple choices for classifying an ontology. The structure of 373 ontologies from the NCBO BioPortal is analyzed and each ontology is classified into multiple families modeled by the structural meta-ontology. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. Growth Rates of Microbes in the Oceans.

    Science.gov (United States)

    Kirchman, David L

    2016-01-01

    A microbe's growth rate helps to set its ecological success and its contribution to food web dynamics and biogeochemical processes. Growth rates at the community level are constrained by biomass and trophic interactions among bacteria, phytoplankton, and their grazers. Phytoplankton growth rates are approximately 1 d(-1), whereas most heterotrophic bacteria grow slowly, close to 0.1 d(-1); only a few taxa can grow ten times as fast. Data from 16S rRNA and other approaches are used to speculate about the growth rate and the life history strategy of SAR11, the most abundant clade of heterotrophic bacteria in the oceans. These strategies are also explored using genomic data. Although the methods and data are imperfect, the available data can be used to set limits on growth rates and thus on the timescale for changes in the composition and structure of microbial communities.

  9. Life Redefined: Microbes Built with Arsenic

    Energy Technology Data Exchange (ETDEWEB)

    Webb, Sam (SLAC and Felisa Wolfe-Simon, NASA and U.S. Geological Survey)

    2011-03-22

    Life can survive in many harsh environments, from extreme heat to the presence of deadly chemicals. However, life as we know it has always been based on the same six elements -- carbon, oxygen, nitrogen, hydrogen, sulfur and phosphorus. Now it appears that even this rule has an exception. In the saline and poisonous environment of Mono Lake, researchers have found a bacterium that can grow by incorporating arsenic into its structure in place of phosphorus. X-ray images taken at SLAC's synchrotron light source reveal that this microbe may even use arsenic as a building block for DNA. Please join us as we describe this discovery, which rewrites the textbook description of how living cells work.

  10. Indoor Air '93. Particles, microbes, radon

    International Nuclear Information System (INIS)

    Kalliokoski, P.; Jantunen, M.; Seppaenen, O.

    1993-01-01

    The conference was held in Helsinki, Finland, July 4-8, 1993. The proceedings of the conference were published in 6 volumes. The main topics of the volume 5 are: (1) particles, fibers and dust - their concentrations and sources in buildings, (2) Health effects of particles, (3) Need of asbestos replacement and encapsulation, (4) Seasonal and temporal variation of fungal and bacterial concentration, (5) The evaluation of microbial contamination of buildings, (6) New methods and comparison of different methods for microbial sampling and evaluation, (7) Microbes in building materials and HVAC-systems, (8) Prevention of microbial contamination in buildings, (9) Dealing with house dust mites, (10) Radon measurements and surveys in different countries, (11) The identification of homes with high radon levels, (12) The measurement methods and prediction of radon levels in buildings, and (13) Prevention of radon penetration from the soil

  11. Contributions to a Conceptual Ontology for Wittgenstein

    DEFF Research Database (Denmark)

    Addis, Mark; Brock, Steen; Pichler, Alois

    2015-01-01

    A conceptual ontology was used to semantically enrich the Wittgenstein Archives at the University of Bergen’s taxonomy for Wittgenstein Source to facilitate improved searching in the areas of the philosophies of mathematics and psychology. The classes and sub-classes of the multilingual taxonomy...

  12. Social Groups, Explanation and Ontological Holism | Sheehy ...

    African Journals Online (AJOL)

    The paper begins from the claim that ontological holism is given prima facie plausibility by the apparently ineliminable role of groups in some descriptions and explanations of the social domain. If the individualist accepts the link between indispensabilty and realism, then individualism must show that groups cannot play the ...

  13. Africanity: A Combative Ontology | Mafeje | CODESRIA Bulletin

    African Journals Online (AJOL)

    Africanity: A Combative Ontology. Archie Mafeje. AJOL African Journals Online. HOW TO USE AJOL... for Researchers · for Librarians · for Authors · FAQ's · More about AJOL · AJOL's Partners · Terms and Conditions of Use · Contact AJOL · News. OTHER RESOURCES... for Researchers · for Journals · for Authors · for Policy ...

  14. Ontological Order in Scientific Explanation | Park | Philosophical ...

    African Journals Online (AJOL)

    A conceptually sound explanation, I claim, respects the ontological order between properties. A dependent property is to be explained in terms of its underlying property, not the other way around. The applicability of this point goes well beyond the realm of the debate between scientific realists and antirealists.

  15. The location problem in social ontology

    NARCIS (Netherlands)

    Hindriks, Frank

    Mental, mathematical, and moral facts are difficult to accommodate within an overall worldview due to the peculiar kinds of properties inherent to them. In this paper I argue that a significant class of social entities also presents us with an ontological puzzle that has thus far not been addressed

  16. Ontologies for commitment-based smart contracts

    NARCIS (Netherlands)

    de Kruijff, Joost; Weigand, Hans; Panetto, H; Debruyne, C.; Gaaloul, W.; Papazoglou, M.; Paschke, A.; Ardagna, C.A.; Meersman, R.

    2017-01-01

    Smart contracts gain rapid exposure since the inception of blockchain technology. Yet there is no unified ontology for smart contracts. Being categorized as coded contracts or substitutes of conventional legal contracts, there is a need to reduce the conceptual ambiguity of smart contracts. We

  17. Patient Centric Ontology for Telehealth Domain

    DEFF Research Database (Denmark)

    Jørgensen, Daniel Bjerring; Hallenborg, Kasper; Demazeau, Yves

    2015-01-01

    This paper presents an ontology for the telehealth domain, a domain that concerns the use of telecommunication to support and deliver health related services e.g. patient monitoring and rehabilitative training. Our vision for the future of telehealth solutions is that they adapt their behavior to...

  18. Ontological support for web courseware authoring

    NARCIS (Netherlands)

    Aroyo, L.M.; Dicheva, D.; Cristea, A.I.; Cerri, S.A.; Gouardères, G.; Paraguaçu, F.

    2002-01-01

    In this paper we present an ontology- oriented authoring support system for Web-based courseware. This is an elaboration of our approach to knowledge classification and indexing in the previously developed system AIMS (Agent-based Information Management System) aimed at supporting students while

  19. Ontology matching evaluation : A statistical perspective

    NARCIS (Netherlands)

    Mohammadi, M.; Hofman, W.J.; Tan, Y.H.

    2016-01-01

    This paper proposes statistical approaches to test if the difference between two ontology matchers is real. Specifically, the performances of the matchers over multiple data sets are obtained and based on their performances, the conclusion can be drawn whether one method is better than one another

  20. Ontology matching evaluation : A statistical perspective

    NARCIS (Netherlands)

    Mohammadi, M.; Hofman, Wout; Tan, Y.

    2016-01-01

    This paper proposes statistical approaches to test if the difference between two ontology matchers is real. Specifically, the performances of the matchers over multiple data sets are obtained and based on their performances, the conclusion can be drawn whether one method is better than one