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Citation
Zhang, X., Moret, B.M. (2010). Refining transcriptional regulatory networks using network evolutionary models and gene histories.  Algorithms Mol. Biol. 5(1): 1.
FlyBase ID
FBrf0210040
Publication Type
Research paper
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 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. Different evolutionary histories for gene duplications and losses are studied, showing that our adapted approach is feasible under a broad range of conditions. We also provide results on biological data (cis-regulatory modules for 12 species of Drosophila), confirming our simulation results.
PubMed ID
PubMed Central ID
PMC2823753 (PMC) (EuropePMC)
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Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    Algorithms Mol. Biol.
    Title
    Algorithms for Molecular Biology: AMB
    Publication Year
    2006-
    ISBN/ISSN
    1748-7188
    Data From Reference
    Genes (6)