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Nucleic Acids Research 2006 34(1):e6; doi:10.1093/nar/gnj002
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Published online 10 January 2006

© The Author 2006. Published by Oxford University Press. All rights reserved
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Methods Online

A systematic approach to infer biological relevance and biases of gene network structures

Alexey V. Antonov1,*, Igor V. Tetko1 and Hans W. Mewes1,2

1GSF National Research Center for Environment and Health, Institute for Bioinformatics Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany 2Department of Genome-Oriented Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München 85350 Freising, Germany

*To whom correspondence should be addressed. Tel: +49 89 31872788; Fax: +49 89 31873585; Email: antonov{at}gsf.de

Received September 27, 2005. Revised November 15, 2005. Accepted December 5, 2005.

The development of high-throughput technologies has generated the need for bioinformatics approaches to assess the biological relevance of gene networks. Although several tools have been proposed for analysing the enrichment of functional categories in a set of genes, none of them is suitable for evaluating the biological relevance of the gene network. We propose a procedure and develop a web-based resource (BIOREL) to estimate the functional bias (biological relevance) of any given genetic network by integrating different sources of biological information. The weights of the edges in the network may be either binary or continuous. These essential features make our web tool unique among many similar services. BIOREL provides standardized estimations of the network biases extracted from independent data. By the analyses of real data we demonstrate that the potential application of BIOREL ranges from various benchmarking purposes to systematic analysis of the network biology.


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