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Functional Gene Networks: R/Bioc package to generate and analyse gene networks derived from functional enrichment and clustering.
Aibar, Sara; Fontanillo, Celia; Droste, Conrad; De Las Rivas, Javier.
Afiliação
  • Aibar S; Bioinformatics and Functional Genomics Research Group, Cancer Research Center (Consejo Superior de Investigaciones Científicas, Universidad de Salamanca and Instituto de Investigación Biomédica de Salamanca, CSIC/USAL/IBSAL), Salamanca, Spain.
  • Fontanillo C; Bioinformatics and Functional Genomics Research Group, Cancer Research Center (Consejo Superior de Investigaciones Científicas, Universidad de Salamanca and Instituto de Investigación Biomédica de Salamanca, CSIC/USAL/IBSAL), Salamanca, Spain.
  • Droste C; Bioinformatics and Functional Genomics Research Group, Cancer Research Center (Consejo Superior de Investigaciones Científicas, Universidad de Salamanca and Instituto de Investigación Biomédica de Salamanca, CSIC/USAL/IBSAL), Salamanca, Spain.
  • De Las Rivas J; Bioinformatics and Functional Genomics Research Group, Cancer Research Center (Consejo Superior de Investigaciones Científicas, Universidad de Salamanca and Instituto de Investigación Biomédica de Salamanca, CSIC/USAL/IBSAL), Salamanca, Spain.
Bioinformatics ; 31(10): 1686-8, 2015 May 15.
Article em En | MEDLINE | ID: mdl-25600944
ABSTRACT
Functional Gene Networks (FGNet) is an R/Bioconductor package that generates gene networks derived from the results of functional enrichment analysis (FEA) and annotation clustering. The sets of genes enriched with specific biological terms (obtained from a FEA platform) are transformed into a network by establishing links between genes based on common functional annotations and common clusters. The network provides a new view of FEA results revealing gene modules with similar functions and genes that are related to multiple functions. In addition to building the functional network, FGNet analyses the similarity between the groups of genes and provides a distance heatmap and a bipartite network of functionally overlapping genes. The application includes an interface to directly perform FEA queries using different external tools DAVID, GeneTerm Linker, TopGO or GAGE; and a graphical interface to facilitate the use.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Limite: Humans Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Limite: Humans Idioma: En Ano de publicação: 2015 Tipo de documento: Article