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GeneCodis3: a non-redundant and modular enrichment analysis tool for functional genomics.


ABSTRACT: Since its first release in 2007, GeneCodis has become a valuable tool to functionally interpret results from experimental techniques in genomics. This web-based application integrates different sources of information to finding groups of genes with similar biological meaning. This process, known as enrichment analysis, is essential in the interpretation of high-throughput experiments. The frequent feedbacks and the natural evolution of genomics and bioinformatics have allowed the growth of the tool and the development of this third release. In this version, a special effort has been made to remove noisy and redundant output from the enrichment results with the inclusion of a recently reported algorithm that summarizes significantly enriched terms and generates functionally coherent modules of genes and terms. A new comparative analysis has been added to allow the differential analysis of gene sets. To expand the scope of the application, new sources of biological information have been included, such as genetic diseases, drugs-genes interactions and Pubmed information among others. Finally, the graphic section has been renewed with the inclusion of new interactive graphics and filtering options. The application is freely available at http://genecodis.cnb.csic.es.

SUBMITTER: Tabas-Madrid D 

PROVIDER: S-EPMC3394297 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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GeneCodis3: a non-redundant and modular enrichment analysis tool for functional genomics.

Tabas-Madrid Daniel D   Nogales-Cadenas Ruben R   Pascual-Montano Alberto A  

Nucleic acids research 20120509 Web Server issue


Since its first release in 2007, GeneCodis has become a valuable tool to functionally interpret results from experimental techniques in genomics. This web-based application integrates different sources of information to finding groups of genes with similar biological meaning. This process, known as enrichment analysis, is essential in the interpretation of high-throughput experiments. The frequent feedbacks and the natural evolution of genomics and bioinformatics have allowed the growth of the t  ...[more]

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