GeneCodis: interpreting gene lists through enrichment analysis and integration of diverse biological information

By Rubén Nogales-Cadenas, Pedro Carmona-Saez, Miguel Vázquez, Cesar Vicente, Xiaoyuan Yang, Francisco Tirado, J. M. Carazo, Alberto Domingo Pascual-Montano. Nucleic Acids Res., 2009

466 citations recorded by the source corpus.

GeneCodis is a web server application for functional analysis of gene lists that integrates different sources of information and finds modular patterns of interrelated annotations. This integrative approach has proved to be useful for the interpretation of high-throughput experiments and therefore a new version of the system has been developed to expand its functionality and scope. GeneCodis now expands the functional information with regulatory patterns and user-defined annotations, offering the possibility of integrating all sources of information in the same analysis. Traditional singular enrichment is now permitted and more organisms and gene identifiers have been added to the database. The application has been re-engineered to improve performance, accessibility and scalability. In addition, GeneCodis can now be accessed through a public SOAP web services interface, enabling users to perform analysis from their own scripts and workflows. The application is freely available at http://genecodis.dacya.ucm.es

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2f8d8d719ae361f5a08170cc4e52850c4c496dfc

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Citations in the corpus

GeneCodis3: a non-redundant and modular enrichment analysis tool for functional genomics (2012, methodology): “In 2007, we introduced GeneCodis (12,13), a tool for singular and modular enrichment analysis that integrates information of diverse nature (e.g. functional, regulatory or structural) by looking for frequent patterns in the space of annotations and computing their statistical relevance.”
Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics (2013, background): “Gene ontology analysis (25) revealed that themost heterogeneous genes fromeach patient were involved in the same biological processes (Fig.”
KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases (2011, background): “A growing number of tools have been developed for pathway and disease identiﬁcation, including, but not limited to, MAPPFinder (13), EASE (14), DAVID (15,16), ArrayXPath (17), WebGestalt (18), FuncCluster (19), PageMan (20), GENECODIS (21,22), GeneTrail (23), g:Proﬁler (24), FunNet (25) and PaLS (26”