Abstract
BackgroundLiving 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.ResultsWe 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.ConclusionsmTRIM is a novel method to infer TF collaborations in transcriptional regulation networks. mTRIM is available at http://www.msu.edu/~jinchen/mTRIM.
Highlights
Living cells are realized by complex gene expression programs that are moderated by regulatory proteins called transcription factors (TFs)
Experimental results evaluated with yeast genetic interactions, TF knockouts and a synthetic dataset shows that our algorithm is significantly better than the existing ones
Experimental results mTRIM was applied on two independently-constructed yeast transcriptional regulatory networks to identify regulatory interactions
Summary
Living cells are realized by complex gene expression programs that are moderated by regulatory proteins called transcription factors (TFs). In a multiple-TF regulatory interaction, a group of TFs collaborate to control the expression levels of the same target genes.
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