Refining transcriptional regulatory networks using network evolutionary models and gene histories

Background: 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.


Published in:
BMC Algorithms in Molecular Biology , 5, 1
Year:
2010
Keywords:
Laboratories:




 Record created 2010-03-12, last modified 2018-03-17


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