title: HIDEN: Hierarchical decomposition of regulatory networks.
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.
authors.affiliation: Computer and Information Sciences and Engineering, University of Florida, Gainesville, FL 32611, USA. ggulsoy@cise.ufl.edu
authors.forename: Günhan
authors.initials: G
authors.lastname: Gülsoy
authors.forename: Nirmalya
authors.initials: N
authors.lastname: Bandhyopadhyay
authors.forename: Tamer
authors.initials: T
authors.lastname: Kahveci
mesh_terms: D019295:Computational Biology / Q000379:methods*; D004926:Escherichia coli / Q000235:genetics; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D012441:Saccharomyces cerevisiae / Q000235:genetics; D012984:Software; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D014157:Transcription Factors