Abstract
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. 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. mTRIM is a novel method to infer TF collaborations in transcriptional regulation networks. mTRIM is available at http://www.msu.edu/~jinchen/mTRIM.
| Original language | English |
|---|---|
| Pages (from-to) | S1 |
| Journal | BMC Systems Biology |
| Volume | 8 Suppl 1 |
| DOIs | |
| State | Published - 2014 |
Bibliographical note
Funding Information:This project has been funded by the Egyptian Government GM 845.
Funding Information:
The publication costs for this article were funded by the corresponding author’s institution. This article has been published as part of BMC Systems Biology Volume 8 Supplement 1, 2014: Selected articles from the Twelfth Asia Pacific Bioinformatics Conference (APBC 2014): Systems Biology. The full contents of the supplement are available online at http://www.biomedcentral.com/ bmcsystbiol/supplements/8/S1.
ASJC Scopus subject areas
- Structural Biology
- Modeling and Simulation
- Molecular Biology
- Computer Science Applications
- Applied Mathematics