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FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks

The characterization of the interacting behaviors of complex biological systems is a primary objective in protein–protein network analysis and computational biology. In this paper we present FunMod, an innovative Cytoscape version 2.8 plugin that is able to mine undirected protein–protein networks a...

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Detalles Bibliográficos
Autores principales: Natale, Massimo, Benso, Alfredo, Di Carlo, Stefano, Ficarra, Elisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4411368/
https://www.ncbi.nlm.nih.gov/pubmed/25153667
http://dx.doi.org/10.1016/j.gpb.2014.05.002
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author Natale, Massimo
Benso, Alfredo
Di Carlo, Stefano
Ficarra, Elisa
author_facet Natale, Massimo
Benso, Alfredo
Di Carlo, Stefano
Ficarra, Elisa
author_sort Natale, Massimo
collection PubMed
description The characterization of the interacting behaviors of complex biological systems is a primary objective in protein–protein network analysis and computational biology. In this paper we present FunMod, an innovative Cytoscape version 2.8 plugin that is able to mine undirected protein–protein networks and to infer sub-networks of interacting proteins intimately correlated with relevant biological pathways. This plugin may enable the discovery of new pathways involved in diseases. In order to describe the role of each protein within the relevant biological pathways, FunMod computes and scores three topological features of the identified sub-networks. By integrating the results from biological pathway clustering and topological network analysis, FunMod proved to be useful for the data interpretation and the generation of new hypotheses in two case studies.
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spelling pubmed-44113682015-05-06 FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks Natale, Massimo Benso, Alfredo Di Carlo, Stefano Ficarra, Elisa Genomics Proteomics Bioinformatics Method The characterization of the interacting behaviors of complex biological systems is a primary objective in protein–protein network analysis and computational biology. In this paper we present FunMod, an innovative Cytoscape version 2.8 plugin that is able to mine undirected protein–protein networks and to infer sub-networks of interacting proteins intimately correlated with relevant biological pathways. This plugin may enable the discovery of new pathways involved in diseases. In order to describe the role of each protein within the relevant biological pathways, FunMod computes and scores three topological features of the identified sub-networks. By integrating the results from biological pathway clustering and topological network analysis, FunMod proved to be useful for the data interpretation and the generation of new hypotheses in two case studies. Elsevier 2014-08 2014-08-19 /pmc/articles/PMC4411368/ /pubmed/25153667 http://dx.doi.org/10.1016/j.gpb.2014.05.002 Text en © 2014 The Authors http://creativecommons.org/licenses/by-nc-sa/3.0/ This is an open access article under the CC BY-NC-SA license (http://creativecommons.org/licenses/by-nc-sa/3.0/).
spellingShingle Method
Natale, Massimo
Benso, Alfredo
Di Carlo, Stefano
Ficarra, Elisa
FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks
title FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks
title_full FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks
title_fullStr FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks
title_full_unstemmed FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks
title_short FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks
title_sort funmod: a cytoscape plugin for identifying functional modules in undirected protein–protein networks
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4411368/
https://www.ncbi.nlm.nih.gov/pubmed/25153667
http://dx.doi.org/10.1016/j.gpb.2014.05.002
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