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The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function

GeneMANIA (http://www.genemania.org) is a flexible, user-friendly web interface for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query list, GeneMANIA extends the list with functionally similar genes that it identifies using av...

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Autores principales: Warde-Farley, David, Donaldson, Sylva L., Comes, Ovi, Zuberi, Khalid, Badrawi, Rashad, Chao, Pauline, Franz, Max, Grouios, Chris, Kazi, Farzana, Lopes, Christian Tannus, Maitland, Anson, Mostafavi, Sara, Montojo, Jason, Shao, Quentin, Wright, George, Bader, Gary D., Morris, Quaid
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896186/
https://www.ncbi.nlm.nih.gov/pubmed/20576703
http://dx.doi.org/10.1093/nar/gkq537
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author Warde-Farley, David
Donaldson, Sylva L.
Comes, Ovi
Zuberi, Khalid
Badrawi, Rashad
Chao, Pauline
Franz, Max
Grouios, Chris
Kazi, Farzana
Lopes, Christian Tannus
Maitland, Anson
Mostafavi, Sara
Montojo, Jason
Shao, Quentin
Wright, George
Bader, Gary D.
Morris, Quaid
author_facet Warde-Farley, David
Donaldson, Sylva L.
Comes, Ovi
Zuberi, Khalid
Badrawi, Rashad
Chao, Pauline
Franz, Max
Grouios, Chris
Kazi, Farzana
Lopes, Christian Tannus
Maitland, Anson
Mostafavi, Sara
Montojo, Jason
Shao, Quentin
Wright, George
Bader, Gary D.
Morris, Quaid
author_sort Warde-Farley, David
collection PubMed
description GeneMANIA (http://www.genemania.org) is a flexible, user-friendly web interface for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query list, GeneMANIA extends the list with functionally similar genes that it identifies using available genomics and proteomics data. GeneMANIA also reports weights that indicate the predictive value of each selected data set for the query. Six organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Homo sapiens and Saccharomyces cerevisiae) and hundreds of data sets have been collected from GEO, BioGRID, Pathway Commons and I2D, as well as organism-specific functional genomics data sets. Users can select arbitrary subsets of the data sets associated with an organism to perform their analyses and can upload their own data sets to analyze. The GeneMANIA algorithm performs as well or better than other gene function prediction methods on yeast and mouse benchmarks. The high accuracy of the GeneMANIA prediction algorithm, an intuitive user interface and large database make GeneMANIA a useful tool for any biologist.
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spelling pubmed-28961862010-07-02 The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function Warde-Farley, David Donaldson, Sylva L. Comes, Ovi Zuberi, Khalid Badrawi, Rashad Chao, Pauline Franz, Max Grouios, Chris Kazi, Farzana Lopes, Christian Tannus Maitland, Anson Mostafavi, Sara Montojo, Jason Shao, Quentin Wright, George Bader, Gary D. Morris, Quaid Nucleic Acids Res Articles GeneMANIA (http://www.genemania.org) is a flexible, user-friendly web interface for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query list, GeneMANIA extends the list with functionally similar genes that it identifies using available genomics and proteomics data. GeneMANIA also reports weights that indicate the predictive value of each selected data set for the query. Six organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Homo sapiens and Saccharomyces cerevisiae) and hundreds of data sets have been collected from GEO, BioGRID, Pathway Commons and I2D, as well as organism-specific functional genomics data sets. Users can select arbitrary subsets of the data sets associated with an organism to perform their analyses and can upload their own data sets to analyze. The GeneMANIA algorithm performs as well or better than other gene function prediction methods on yeast and mouse benchmarks. The high accuracy of the GeneMANIA prediction algorithm, an intuitive user interface and large database make GeneMANIA a useful tool for any biologist. Oxford University Press 2010-07-01 2010-06-21 /pmc/articles/PMC2896186/ /pubmed/20576703 http://dx.doi.org/10.1093/nar/gkq537 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Warde-Farley, David
Donaldson, Sylva L.
Comes, Ovi
Zuberi, Khalid
Badrawi, Rashad
Chao, Pauline
Franz, Max
Grouios, Chris
Kazi, Farzana
Lopes, Christian Tannus
Maitland, Anson
Mostafavi, Sara
Montojo, Jason
Shao, Quentin
Wright, George
Bader, Gary D.
Morris, Quaid
The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function
title The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function
title_full The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function
title_fullStr The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function
title_full_unstemmed The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function
title_short The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function
title_sort genemania prediction server: biological network integration for gene prioritization and predicting gene function
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896186/
https://www.ncbi.nlm.nih.gov/pubmed/20576703
http://dx.doi.org/10.1093/nar/gkq537
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