A new framework for identifying combinatorial regulation of transcription factors: a case study of the yeast cell cycle

Details A new framework for identifying combinatorial regulation of transcription factors: a case study of the yeast cell cycle A new framework for identifying combinatorial regulation of transcription factors: a case study of the yeast cell cycle

2010-10-06

arxiv.org/abs/1010.1100v1

Journal of Biomedical Informatics Volume 40, Issue 6, December 2007, Pages 707-725. Intelligent Data Analysis in Biomedicine

Biology

Quantitative Biology

Quantitative Methods

55 pages 7 figures

Scientific paper

10.1016/j.jbi.2007.02.003

By integrating heterogeneous functional genomic datasets, we have developed a new framework for detecting combinatorial control of gene expression, which includes estimating transcription factor activities using a singular value decomposition method and reducing high-dimensional input gene space by considering genomic properties of gene clusters. The prediction of cooperative gene regulation is accomplished by either Gaussian Graphical Models or Pairwise Mixed Graphical Models. The proposed framework was tested on yeast cell cycle datasets: (1) 54 known yeast cell cycle genes with 9 cell cycle regulators and (2) 676 putative yeast cell cycle genes with 9 cell cycle regulators. The new framework gave promising results on inferring TF-TF and TF-gene interactions. It also revealed several interesting mechanisms such as negatively correlated protein-protein interactions and low affinity protein-DNA interactions that may be important during the yeast cell cycle. The new framework may easily be extended to study other higher eukaryotes.

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