Improving microbial genome annotations in an integrated database context
Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that all...
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creator | Chen, I-Min A Markowitz, Victor M Chu, Ken Anderson, Iain Mavromatis, Konstantinos Kyrpides, Nikos C Ivanova, Natalia N |
description | Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/. |
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Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0054859</identifier><identifier>PMID: 23424620</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acids ; Analysis ; Annotations ; Automation ; Bioinformatics ; Biology ; Comparative analysis ; Completeness ; Computer Science ; Consistency ; Databases, Genetic ; Genes ; Genomes ; Genomics ; Laboratories ; Metabolism ; Metadata ; Microbiology ; Microorganisms ; Molecular Sequence Annotation - methods ; Phenotype ; Physiology ; Proteins ; Respiration ; Semantics</subject><ispartof>PloS one, 2013-02, Vol.8 (2), p.e54859-e54859</ispartof><rights>COPYRIGHT 2013 Public Library of Science</rights><rights>2013 Chen et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2013 Chen et al 2013 Chen et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c785t-161aa79fd373e6c18336e0f666594aafdf012e828378b47f625f005f4799b76f3</citedby><cites>FETCH-LOGICAL-c785t-161aa79fd373e6c18336e0f666594aafdf012e828378b47f625f005f4799b76f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3570495/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3570495/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23424620$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/biblio/1154055$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Chen, I-Min A</creatorcontrib><creatorcontrib>Markowitz, Victor M</creatorcontrib><creatorcontrib>Chu, Ken</creatorcontrib><creatorcontrib>Anderson, Iain</creatorcontrib><creatorcontrib>Mavromatis, Konstantinos</creatorcontrib><creatorcontrib>Kyrpides, Nikos C</creatorcontrib><creatorcontrib>Ivanova, Natalia N</creatorcontrib><creatorcontrib>Joint Genome Institute (JGI)</creatorcontrib><title>Improving microbial genome annotations in an integrated database context</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. 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Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>23424620</pmid><doi>10.1371/journal.pone.0054859</doi><tpages>e54859</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Acids Analysis Annotations Automation Bioinformatics Biology Comparative analysis Completeness Computer Science Consistency Databases, Genetic Genes Genomes Genomics Laboratories Metabolism Metadata Microbiology Microorganisms Molecular Sequence Annotation - methods Phenotype Physiology Proteins Respiration Semantics |
title | Improving microbial genome annotations in an integrated database context |
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