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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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Detalles Bibliográficos
Autores principales: Chen, I-Min A., Markowitz, Victor M., Chu, Ken, Anderson, Iain, Mavromatis, Konstantinos, Kyrpides, Nikos C., Ivanova, Natalia N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3570495/
https://www.ncbi.nlm.nih.gov/pubmed/23424620
http://dx.doi.org/10.1371/journal.pone.0054859
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author Chen, I-Min A.
Markowitz, Victor M.
Chu, Ken
Anderson, Iain
Mavromatis, Konstantinos
Kyrpides, Nikos C.
Ivanova, Natalia N.
author_facet Chen, I-Min A.
Markowitz, Victor M.
Chu, Ken
Anderson, Iain
Mavromatis, Konstantinos
Kyrpides, Nikos C.
Ivanova, Natalia N.
author_sort Chen, I-Min A.
collection PubMed
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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spelling pubmed-35704952013-02-19 Improving Microbial Genome Annotations in an Integrated Database Context Chen, I-Min A. Markowitz, Victor M. Chu, Ken Anderson, Iain Mavromatis, Konstantinos Kyrpides, Nikos C. Ivanova, Natalia N. PLoS One Research Article 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/. Public Library of Science 2013-02-12 /pmc/articles/PMC3570495/ /pubmed/23424620 http://dx.doi.org/10.1371/journal.pone.0054859 Text en © 2013 Chen et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Chen, I-Min A.
Markowitz, Victor M.
Chu, Ken
Anderson, Iain
Mavromatis, Konstantinos
Kyrpides, Nikos C.
Ivanova, Natalia N.
Improving Microbial Genome Annotations in an Integrated Database Context
title 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_short Improving Microbial Genome Annotations in an Integrated Database Context
title_sort improving microbial genome annotations in an integrated database context
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3570495/
https://www.ncbi.nlm.nih.gov/pubmed/23424620
http://dx.doi.org/10.1371/journal.pone.0054859
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