title: Inferring transcription factor collaborations in gene regulatory networks.
abstract: BACKGROUND
  Living cells are realized by complex gene expression programs that are moderated by regulatory proteins called transcription factors (TFs). The TFs control the differential expression of target genes in the context of transcriptional regulatory networks (TRNs), either individually or in groups. Deciphering the mechanisms of how the TFs control the expression of target genes is a challenging task, especially when multiple TFs collaboratively participate in the transcriptional regulation.
  
  
  RESULTS
  We model the underlying regulatory interactions in terms of the directions (activation or repression) and their logical roles (necessary and/or sufficient) with a modified association rule mining approach, called mTRIM. The experiment on Yeast discovered 670 regulatory interactions, in which multiple TFs express their functions on common target genes collaboratively. The evaluation on yeast genetic interactions, TF knockouts and a synthetic dataset shows that our algorithm is significantly better than the existing ones.
  
  
  CONCLUSIONS
  mTRIM is a novel method to infer TF collaborations in transcriptional regulation networks. mTRIM is available at http://www.msu.edu/~jinchen/mTRIM.
authors.forename: Sherine
authors.initials: S
authors.lastname: Awad
authors.forename: Jin
authors.initials: J
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D055786:Gene Knockout Techniques; D053263:Gene Regulatory Networks; D008954:Models, Biological; D014157:Transcription Factors / Q000172:deficiency / Q000235:genetics / Q000378:metabolism*; D015003:Yeasts / Q000235:genetics
chemical_list: D014157:Transcription Factors