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Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks

Genomics provided us with an unprecedented quantity of data on the genes that are activated or repressed in a wide range of phenotypes. We have increasingly come to recognize that defining the networks and pathways underlying these phenotypes requires both the integration of multiple data types and...

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Autores principales: Haibe-Kains, Benjamin, Olsen, Catharina, Djebbari, Amira, Bontempi, Gianluca, Correll, Mick, Bouton, Christopher, Quackenbush, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245161/
https://www.ncbi.nlm.nih.gov/pubmed/22096235
http://dx.doi.org/10.1093/nar/gkr1050
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author Haibe-Kains, Benjamin
Olsen, Catharina
Djebbari, Amira
Bontempi, Gianluca
Correll, Mick
Bouton, Christopher
Quackenbush, John
author_facet Haibe-Kains, Benjamin
Olsen, Catharina
Djebbari, Amira
Bontempi, Gianluca
Correll, Mick
Bouton, Christopher
Quackenbush, John
author_sort Haibe-Kains, Benjamin
collection PubMed
description Genomics provided us with an unprecedented quantity of data on the genes that are activated or repressed in a wide range of phenotypes. We have increasingly come to recognize that defining the networks and pathways underlying these phenotypes requires both the integration of multiple data types and the development of advanced computational methods to infer relationships between the genes and to estimate the predictive power of the networks through which they interact. To address these issues we have developed Predictive Networks (PN), a flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these ‘known’ interactions together with gene expression data to infer robust gene networks. The PN web application is accessible from http://predictivenetworks.org. The PN code base is freely available at https://sourceforge.net/projects/predictivenets/.
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spelling pubmed-32451612012-01-10 Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks Haibe-Kains, Benjamin Olsen, Catharina Djebbari, Amira Bontempi, Gianluca Correll, Mick Bouton, Christopher Quackenbush, John Nucleic Acids Res Articles Genomics provided us with an unprecedented quantity of data on the genes that are activated or repressed in a wide range of phenotypes. We have increasingly come to recognize that defining the networks and pathways underlying these phenotypes requires both the integration of multiple data types and the development of advanced computational methods to infer relationships between the genes and to estimate the predictive power of the networks through which they interact. To address these issues we have developed Predictive Networks (PN), a flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these ‘known’ interactions together with gene expression data to infer robust gene networks. The PN web application is accessible from http://predictivenetworks.org. The PN code base is freely available at https://sourceforge.net/projects/predictivenets/. Oxford University Press 2012-01 2011-11-16 /pmc/articles/PMC3245161/ /pubmed/22096235 http://dx.doi.org/10.1093/nar/gkr1050 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Haibe-Kains, Benjamin
Olsen, Catharina
Djebbari, Amira
Bontempi, Gianluca
Correll, Mick
Bouton, Christopher
Quackenbush, John
Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks
title Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks
title_full Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks
title_fullStr Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks
title_full_unstemmed Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks
title_short Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks
title_sort predictive networks: a flexible, open source, web application for integration and analysis of human gene networks
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245161/
https://www.ncbi.nlm.nih.gov/pubmed/22096235
http://dx.doi.org/10.1093/nar/gkr1050
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