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MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates
Laboratory mouse, Mus musculus, is one of the most important animal tools in biomedical research. Functional characterization of the mouse genes, hence, has been a long-standing goal in mammalian and human genetics. Although large-scale knockout phenotyping is under progress by international collabo...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702832/ https://www.ncbi.nlm.nih.gov/pubmed/26527726 http://dx.doi.org/10.1093/nar/gkv1155 |
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author | Kim, Eiru Hwang, Sohyun Kim, Hyojin Shim, Hongseok Kang, Byunghee Yang, Sunmo Shim, Jae Ho Shin, Seung Yeon Marcotte, Edward M. Lee, Insuk |
author_facet | Kim, Eiru Hwang, Sohyun Kim, Hyojin Shim, Hongseok Kang, Byunghee Yang, Sunmo Shim, Jae Ho Shin, Seung Yeon Marcotte, Edward M. Lee, Insuk |
author_sort | Kim, Eiru |
collection | PubMed |
description | Laboratory mouse, Mus musculus, is one of the most important animal tools in biomedical research. Functional characterization of the mouse genes, hence, has been a long-standing goal in mammalian and human genetics. Although large-scale knockout phenotyping is under progress by international collaborative efforts, a large portion of mouse genome is still poorly characterized for cellular functions and associations with disease phenotypes. A genome-scale functional network of mouse genes, MouseNet, was previously developed in context of MouseFunc competition, which allowed only limited input data for network inferences. Here, we present an improved mouse co-functional network, MouseNet v2 (available at http://www.inetbio.org/mousenet), which covers 17 714 genes (>88% of coding genome) with 788 080 links, along with a companion web server for network-assisted functional hypothesis generation. The network database has been substantially improved by large expansion of genomics data. For example, MouseNet v2 database contains 183 co-expression networks inferred from 8154 public microarray samples. We demonstrated that MouseNet v2 is predictive for mammalian phenotypes as well as human diseases, which suggests its usefulness in discovery of novel disease genes and dissection of disease pathways. Furthermore, MouseNet v2 database provides functional networks for eight other vertebrate models used in various research fields. |
format | Online Article Text |
id | pubmed-4702832 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47028322016-01-07 MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates Kim, Eiru Hwang, Sohyun Kim, Hyojin Shim, Hongseok Kang, Byunghee Yang, Sunmo Shim, Jae Ho Shin, Seung Yeon Marcotte, Edward M. Lee, Insuk Nucleic Acids Res Database Issue Laboratory mouse, Mus musculus, is one of the most important animal tools in biomedical research. Functional characterization of the mouse genes, hence, has been a long-standing goal in mammalian and human genetics. Although large-scale knockout phenotyping is under progress by international collaborative efforts, a large portion of mouse genome is still poorly characterized for cellular functions and associations with disease phenotypes. A genome-scale functional network of mouse genes, MouseNet, was previously developed in context of MouseFunc competition, which allowed only limited input data for network inferences. Here, we present an improved mouse co-functional network, MouseNet v2 (available at http://www.inetbio.org/mousenet), which covers 17 714 genes (>88% of coding genome) with 788 080 links, along with a companion web server for network-assisted functional hypothesis generation. The network database has been substantially improved by large expansion of genomics data. For example, MouseNet v2 database contains 183 co-expression networks inferred from 8154 public microarray samples. We demonstrated that MouseNet v2 is predictive for mammalian phenotypes as well as human diseases, which suggests its usefulness in discovery of novel disease genes and dissection of disease pathways. Furthermore, MouseNet v2 database provides functional networks for eight other vertebrate models used in various research fields. Oxford University Press 2016-01-04 2015-11-02 /pmc/articles/PMC4702832/ /pubmed/26527726 http://dx.doi.org/10.1093/nar/gkv1155 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. 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 | Database Issue Kim, Eiru Hwang, Sohyun Kim, Hyojin Shim, Hongseok Kang, Byunghee Yang, Sunmo Shim, Jae Ho Shin, Seung Yeon Marcotte, Edward M. Lee, Insuk MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates |
title | MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates |
title_full | MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates |
title_fullStr | MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates |
title_full_unstemmed | MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates |
title_short | MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates |
title_sort | mousenet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702832/ https://www.ncbi.nlm.nih.gov/pubmed/26527726 http://dx.doi.org/10.1093/nar/gkv1155 |
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