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Bioinformatics Advance Access originally published online on September 13, 2007
Bioinformatics 2007 23(22):3098-3099; doi:10.1093/bioinformatics/btm445
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© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Functional profiling of microarray experiments using text-mining derived bioentities

Pablo Minguez 1, Fátima Al-Shahrour 1, David Montaner 1,2 and Joaquín Dopazo 1,2,*

1Department of Bioinformatics and 2Functional Genomics Node, (INB), Centro de Investigación Príncipe Felipe (CIPF), Valencia, E46013, Spain

*To whom correspondence should be addressed.


  Abstract

Motivation: The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.

Availability: Marmite and MarmiteScan can be found in the Babelomics suite: http://www.babelomics.org

Contact: jdopazo{at}cipf.es

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: John Quackenbush

Received on January 17, 2007; revised on July 11, 2007; accepted on August 21, 2007

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