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Open Access Research article

HIDEN: Hierarchical decomposition of regulatory networks

Günhan Gülsoy*, Nirmalya Bandhyopadhyay and Tamer Kahveci

Author Affiliations

Computer and Information Sciences and Engineering, University of Florida, Gainesville, FL 32611, USA

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BMC Bioinformatics 2012, 13:250  doi:10.1186/1471-2105-13-250

Published: 28 September 2012

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.