Showing papers by "Midori A. Harris published in 2013"
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Mississippi State University1, Lawrence Berkeley National Laboratory2, Northwestern University3, Texas A&M University4, University of Cambridge5, Swiss Institute of Bioinformatics6, University College London7, University of Maryland, Baltimore8, European Bioinformatics Institute9, Medical College of Wisconsin10, New York University11, Stanford University12, Carnegie Institution for Science13, University of Southern California14, California Institute of Technology15, University of Oregon16
TL;DR: The Gene Ontology (GO) Consortium is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies and has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology.
Abstract: The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.
492 citations
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TL;DR: This guide represents the best practices for manual annotation as established by the GOC project over the past 12 years and it is hoped this guide will encourage research communities to annotate gene products of their interest to enhance the corpus of GO annotations available to all.
Abstract: The Gene Ontology Consortium (GOC) is a community-based bioinformatics project that classifies gene product function through the use of structured controlled vocabularies. A fundamental application of the Gene Ontology (GO) is in the creation of gene product annotations, evidence-based associations between GO definitions and experimental or sequence-based analysis. Currently, the GOC disseminates 126 million annotations covering >374 000 species including all the kingdoms of life. This number includes two classes of GO annotations: those created manually by experienced biocurators reviewing the literature or by examination of biological data (1.1 million annotations covering 2226 species) and those generated computationally via automated methods. As manual annotations are often used to propagate functional predictions between related proteins within and between genomes, it is critical to provide accurate consistent manual annotations. Toward this goal, we present here the conventions defined by the GOC for the creation of manual annotation. This guide represents the best practices for manual annotation as established by the GOC project over the past 12 years. We hope this guide will encourage research communities to annotate gene products of their interest to enhance the corpus of GO annotations available to all.
128 citations
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TL;DR: 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 is described.
Abstract: 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. 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. 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
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61 citations
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TL;DR: The fission yeast phenotype ontology (FYPO) is a modular ontology that uses several existing ontologies from the open biological and biomedical ontologies (OBO) collection as building blocks, including the phenotypic quality ontology PATO, the Gene Ontology and Chemical Entities of Biological Interest.
Abstract: Motivation: To provide consistent computable descriptions of phenotype data, PomBase is developing a formal ontology of phenotypes observed in fission yeast. Results: The fission yeast phenotype ontology (FYPO) is a modular ontology that uses several existing ontologies from the open biological and biomedical ontologies (OBO) collection as building blocks, including the phenotypic quality ontology PATO, the Gene Ontology and Chemical Entities of Biological Interest. Modular ontology development facilitates partially automated effective organization of detailed phenotype descriptions with complex relationships to each other and to underlying biological phenomena. As a result, FYPO supports sophisticated querying, computational analysis and comparison between different experiments and even between species. Availability: FYPO releases are available from the Subversion repository at the PomBase SourceForge project page (https://sourceforge. net/p/pombase/code/HEAD/tree/phenotype_ontology/). The current version of FYPO is also available on the OBO Foundry Web site
57 citations