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Nucleic Acids Research 2004 32(Web Server Issue):W485-W491; doi:10.1093/nar/gkh421
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© 2004, the authors
Nucleic Acids Research, Vol. 32, Web Server issue © Oxford University Press 2004; all rights reserved

New challenges in gene expression data analysis and the extended GEPAS

Javier Herrero, Juan M. Vaquerizas, Fátima Al-Shahrour, Lucía Conde, Álvaro Mateos, Javier Santoyo Ramón Díaz-Uriarte and Joaquín Dopazo*

Bioinformatics Unit, Biotechnology Programme, Centro Nacional de Investigaciones Oncológicas (CNIO), Melchor Fernández Almagro, 3, E-28029 Madrid, Spain

* To whom correspondence should be addressed. Tel: +34 912 246 919; Fax: +34 912 246 972; Email: jdopazo{at}cnio.es

Received February 13, 2004; Revised and Accepted April 7, 2004

Since the first papers published in the late nineties, including, for the first time, a comprehensive analysis of microarray data, the number of questions that have been addressed through this technique have both increased and diversified. Initially, interest focussed on genes coexpressing across sets of experimental conditions, implying, essentially, the use of clustering techniques. Recently, however, interest has focussed more on finding genes differentially expressed among distinct classes of experiments, or correlated to diverse clinical outcomes, as well as in building predictors. In addition to this, the availability of accurate genomic data and the recent implementation of CGH arrays has made mapping expression and genomic data on the chromosomes possible. There is also a clear demand for methods that allow the automatic transfer of biological information to the results of microarray experiments. Different initiatives, such as the Gene Ontology (GO) consortium, pathways databases, protein functional motifs, etc., provide curated annotations for genes. Whereas many resources on the web focus mainly on clustering methods, GEPAS has evolved to cope with the aforementioned new challenges that have recently arisen in the field of microarray data analysis. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://gepas.bioinfo.cnio.es.

The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated.


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