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BMC Bioinformatics. 2012 Sep 28;13:250. doi: 10.1186/1471-2105-13-250.

HIDEN: Hierarchical decomposition of regulatory networks.

Author information

1
Computer and Information Sciences and Engineering, University of Florida, Gainesville, FL 32611, USA. ggulsoy@cise.ufl.edu

Abstract

BACKGROUND:

Transcription factors regulate numerous cellular processes by controlling the rate of production of each gene. The regulatory relations are modeled using transcriptional regulatory networks. Recent studies have shown that such networks have an underlying hierarchical organization. We consider the problem of discovering the underlying hierarchy in transcriptional regulatory networks.

RESULTS:

We first transform this problem to a mixed integer programming problem. We then use existing tools to solve the resulting problem. For larger networks this strategy does not work due to rapid increase in running time and space usage. We use divide and conquer strategy for such networks. We use our method to analyze the transcriptional regulatory networks of E. coli, H. sapiens and S. cerevisiae.

CONCLUSIONS:

Our experiments demonstrate that: (i) Our method gives statistically better results than three existing state of the art methods; (ii) Our method is robust against errors in the data and (iii) Our method's performance is not affected by the different topologies in the data.

PMID:
23016513
PMCID:
PMC3556311
DOI:
10.1186/1471-2105-13-250
[Indexed for MEDLINE]
Free PMC Article
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