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Improving Inference of Transcriptional Regulatory Networks Based on Network Evolutionary Models

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Algorithms in Bioinformatics (WABI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5724))

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Abstract

Computational inference of transcriptional regulatory networks remains a challenging problem, in part due to the lack of strong network models. In this paper we present evolutionary approaches to improve the inference of regulatory networks for a family of organisms by developing an evolutionary model for these networks and taking advantage of established phylogenetic relationships among these organisms. In previous work, we used a simple evolutionary model for regulatory networks and provided extensive simulation results showing that phylogenetic information, combined with such a model, could be used to gain significant improvements on the performance of current inference algorithms.

In this paper, we extend the evolutionary model so as to take into account gene duplications and losses, which are viewed as major drivers in the evolution of regulatory networks. We show how to adapt our evolutionary approach to this new model and provide detailed simulation results, which show significant improvement on the reference network inference algorithms. We also provide results on biological data (cis-regulatory modules for 12 species of Drosophila), confirming our simulation results.

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Author information

Authors and Affiliations

  1. Laboratory for Computational Biology and Bioinformatics, EPFL (Ecole Polytechnique Fédérale de Lausanne), Lausanne, Switzerland, and Swiss Institute of Bioinformatics, Switzerland

    Xiuwei Zhang & Bernard M. E. Moret

Authors
  1. Xiuwei Zhang
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  2. Bernard M. E. Moret
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Editor information

Editors and Affiliations

  1. Center for Bioinformatics and Computational Biology, and Department of Computer Science, University of Maryland, MD, College Park, USA

    Steven L. Salzberg

  2. Department of Computer Sciences, The University of Texas at Austin, TX, USA

    Tandy Warnow

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© 2009 Springer-Verlag Berlin Heidelberg

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Zhang, X., Moret, B.M.E. (2009). Improving Inference of Transcriptional Regulatory Networks Based on Network Evolutionary Models. In: Salzberg, S.L., Warnow, T. (eds) Algorithms in Bioinformatics. WABI 2009. Lecture Notes in Computer Science(), vol 5724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04241-6_34

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  • DOI: https://doi.org/10.1007/978-3-642-04241-6_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04240-9

  • Online ISBN: 978-3-642-04241-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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