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EcoliNet: a database of cofunctional gene network for Escherichia coli
During the past several decades, Escherichia coli has been a treasure chest for molecular biology. The molecular mechanisms of many fundamental cellular processes have been discovered through research on this bacterium. Although much basic research now focuses on more complex model organisms, E. col...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4314589/ https://www.ncbi.nlm.nih.gov/pubmed/25650278 http://dx.doi.org/10.1093/database/bav001 |
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author | Kim, Hanhae Shim, Jung Eun Shin, Junha Lee, Insuk |
author_facet | Kim, Hanhae Shim, Jung Eun Shin, Junha Lee, Insuk |
author_sort | Kim, Hanhae |
collection | PubMed |
description | During the past several decades, Escherichia coli has been a treasure chest for molecular biology. The molecular mechanisms of many fundamental cellular processes have been discovered through research on this bacterium. Although much basic research now focuses on more complex model organisms, E. coli still remains important in metabolic engineering and synthetic biology. Despite its long history as a subject of molecular investigation, more than one-third of the E. coli genome has no pathway annotation supported by either experimental evidence or manual curation. Recently, a network-assisted genetics approach to the efficient identification of novel gene functions has increased in popularity. To accelerate the speed of pathway annotation for the remaining uncharacterized part of the E. coli genome, we have constructed a database of cofunctional gene network with near-complete genome coverage of the organism, dubbed EcoliNet. We find that EcoliNet is highly predictive for diverse bacterial phenotypes, including antibiotic response, indicating that it will be useful in prioritizing novel candidate genes for a wide spectrum of bacterial phenotypes. We have implemented a web server where biologists can easily run network algorithms over EcoliNet to predict novel genes involved in a pathway or novel functions for a gene. All integrated cofunctional associations can be downloaded, enabling orthology-based reconstruction of gene networks for other bacterial species as well. Database URL: http://www.inetbio.org/ecolinet |
format | Online Article Text |
id | pubmed-4314589 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-43145892015-02-24 EcoliNet: a database of cofunctional gene network for Escherichia coli Kim, Hanhae Shim, Jung Eun Shin, Junha Lee, Insuk Database (Oxford) Original Article During the past several decades, Escherichia coli has been a treasure chest for molecular biology. The molecular mechanisms of many fundamental cellular processes have been discovered through research on this bacterium. Although much basic research now focuses on more complex model organisms, E. coli still remains important in metabolic engineering and synthetic biology. Despite its long history as a subject of molecular investigation, more than one-third of the E. coli genome has no pathway annotation supported by either experimental evidence or manual curation. Recently, a network-assisted genetics approach to the efficient identification of novel gene functions has increased in popularity. To accelerate the speed of pathway annotation for the remaining uncharacterized part of the E. coli genome, we have constructed a database of cofunctional gene network with near-complete genome coverage of the organism, dubbed EcoliNet. We find that EcoliNet is highly predictive for diverse bacterial phenotypes, including antibiotic response, indicating that it will be useful in prioritizing novel candidate genes for a wide spectrum of bacterial phenotypes. We have implemented a web server where biologists can easily run network algorithms over EcoliNet to predict novel genes involved in a pathway or novel functions for a gene. All integrated cofunctional associations can be downloaded, enabling orthology-based reconstruction of gene networks for other bacterial species as well. Database URL: http://www.inetbio.org/ecolinet Oxford University Press 2015-02-02 /pmc/articles/PMC4314589/ /pubmed/25650278 http://dx.doi.org/10.1093/database/bav001 Text en © The Author(s) 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Kim, Hanhae Shim, Jung Eun Shin, Junha Lee, Insuk EcoliNet: a database of cofunctional gene network for Escherichia coli |
title | EcoliNet: a database of cofunctional gene network for Escherichia coli |
title_full | EcoliNet: a database of cofunctional gene network for Escherichia coli |
title_fullStr | EcoliNet: a database of cofunctional gene network for Escherichia coli |
title_full_unstemmed | EcoliNet: a database of cofunctional gene network for Escherichia coli |
title_short | EcoliNet: a database of cofunctional gene network for Escherichia coli |
title_sort | ecolinet: a database of cofunctional gene network for escherichia coli |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4314589/ https://www.ncbi.nlm.nih.gov/pubmed/25650278 http://dx.doi.org/10.1093/database/bav001 |
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