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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Autores principales: I-Min A Chen, Victor M Markowitz, Ken Chu, Iain Anderson, Konstantinos Mavromatis, Nikos C Kyrpides, Natalia N Ivanova
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Publicado: Public Library of Science (PLoS) 2013
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Acceso en línea:https://doaj.org/article/04f77dd709824ada9d00d4faf5a0d204
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spelling oai:doaj.org-article:04f77dd709824ada9d00d4faf5a0d2042021-11-18T07:57:59ZImproving microbial genome annotations in an integrated database context.1932-620310.1371/journal.pone.0054859https://doaj.org/article/04f77dd709824ada9d00d4faf5a0d2042013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23424620/?tool=EBIhttps://doaj.org/toc/1932-6203Effective 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/.I-Min A ChenVictor M MarkowitzKen ChuIain AndersonKonstantinos MavromatisNikos C KyrpidesNatalia N IvanovaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 2, p e54859 (2013)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
I-Min A Chen
Victor M Markowitz
Ken Chu
Iain Anderson
Konstantinos Mavromatis
Nikos C Kyrpides
Natalia N Ivanova
Improving microbial genome annotations in an integrated database context.
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/.
format article
author I-Min A Chen
Victor M Markowitz
Ken Chu
Iain Anderson
Konstantinos Mavromatis
Nikos C Kyrpides
Natalia N Ivanova
author_facet I-Min A Chen
Victor M Markowitz
Ken Chu
Iain Anderson
Konstantinos Mavromatis
Nikos C Kyrpides
Natalia N Ivanova
author_sort I-Min A Chen
title Improving microbial genome annotations in an integrated database context.
title_short Improving microbial genome annotations in an integrated database context.
title_full Improving microbial genome annotations in an integrated database context.
title_fullStr Improving microbial genome annotations in an integrated database context.
title_full_unstemmed Improving microbial genome annotations in an integrated database context.
title_sort improving microbial genome annotations in an integrated database context.
publisher Public Library of Science (PLoS)
publishDate 2013
url https://doaj.org/article/04f77dd709824ada9d00d4faf5a0d204
work_keys_str_mv AT iminachen improvingmicrobialgenomeannotationsinanintegrateddatabasecontext
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AT iainanderson improvingmicrobialgenomeannotationsinanintegrateddatabasecontext
AT konstantinosmavromatis improvingmicrobialgenomeannotationsinanintegrateddatabasecontext
AT nikosckyrpides improvingmicrobialgenomeannotationsinanintegrateddatabasecontext
AT natalianivanova improvingmicrobialgenomeannotationsinanintegrateddatabasecontext
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