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Transcriptional mechanisms of phenotypic variation from multi-omics data

Saurabh Sinha, (University of Illinois, Urbana-Champaign)
Tuesday October 29, 12-1pm
McIntyre Medical Building, room 1034

Abstract: Reconstruction of gene regulatory networks (GRNs), specifically those connecting transcription factors (TFs) to their target genes, has been a central goal of computational regulatory genomics for decades. Such networks help us identify major TFs and TF-gene relationships that underlie expression changes in the system being studied. Frequently, GRN reconstruction methods exploit correlations in expression data and in many cases they also utilize genome-wide TF-DNA binding and epigenomic profiles. Our recent research on this problem addresses two important challenges: (a) how to integrate multiple types of data pertaining to TF-gene relationships, during GRN reconstruction, and (b) how to ‘enrich’ the reconstructed GRN with genes that underlie phenotypic variation among the samples. 

I will present the main underlying methodology, based on probabilistic graphical models, and its application to two biological problems: (i) identifying TFs underlying drug response variation among individuals, while integrating genotype, TF-DNA binding, DNA methylation, gene expression and cytotoxicity data, and (ii) identifying TFs underlying colorectal cancer progression from dynamic histone modification data as well as gene expression and TF-DNA binding data.