ProPhyC: a probabilistic phylogenetic model for refining regulatory networks

The experimental determination of transcriptional regulatory networks in the laboratory remains difficult and time-consuming, while computational methods to infer these networks provide only modest accuracy. The latter can be attributed in part to the limitations of a single-organism approach. Computational biology has long used comparative and, more generally, evolutionary approaches to extend the reach and accuracy of its analyses. We therefore use an evolutionary approach to the inference of regulatory networks, which enables us to study evolutionary models for these networks as well as to improve the accuracy of inferred networks.


Published in:
Proceedings of the 7th International Symposium on Bioinformatics Research and Applications ISBRA'11, 344-357
Presented at:
7th International Symposium on Bioinformatics Research and Applications ISBRA'11, China, May 2011
Year:
2011
Publisher:
Springer Verlag
Keywords:
Laboratories:




 Record created 2011-04-17, last modified 2018-03-17


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