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Bioinformatics Advance Access published online on February 27, 2009

Bioinformatics, doi:10.1093/bioinformatics/btp115
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© The Author (2009). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

GeNGe: Systematic Generation of Gene Regulatory Networks

Hendrik Hache *, Christoph Wierling , Hans Lehrach and Ralf Herwig

Vertebrate Genomics - Bioinformatics Group, Max Planck Institute for Molecular Genetics, Ihnestraβe 63-73, 14194 Berlin, Germany

*To whom correspondence should be addressed. Mr. Hendrik Hache, E-mail: hache{at}molgen.mpg.de


   Abstract

Summary: The analysis of gene regulatory networks (GRNs) is a central goal of bioinformatics highly accelerated by the advent of new experimental techniques, such as RNA interference. A battery of reverse engineering methods has been developed in recent years to reconstruct the underlying GRNs from these and other experimental data. However, the performance of the individual methods is poorly understood and validation of algorithmic performances is still missing to a large extent.

To enable such systematic validation, we have developed the web application GeNGe (GEne Network GEnerator), a controlled framework for the automatic generation of GRNs. The theoretical model for a GRN is a nonlinear differential equation system. Networks can be user-defined or constructed in a modular way with the option to introduce global and local network perturbations. Resulting data can be used, e.g., as benchmark data for evaluating GRN reconstruction methods or for predicting effects of perturbations as theoretical counterparts of biological experiments.

Availability: Available online at http://genge.molgen.mpg.de

Supplementary information: Supplementary data is available.

Contact: hache{at}molgen.mpg.de

Associate Editor: Dr. Jonathan Wren


Received on November 4, 2008; revised on February 10, 2009; accepted on February 23, 2009

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