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Discovery And Validation Of Information Theory-Based Transcription Factor And Cofactor Binding Site Motifs., Ruipeng Lu, Eliseos J Mucaki, Peter K Rogan Mar 2017

Discovery And Validation Of Information Theory-Based Transcription Factor And Cofactor Binding Site Motifs., Ruipeng Lu, Eliseos J Mucaki, Peter K Rogan

Biochemistry Publications

Data from ChIP-seq experiments can derive the genome-wide binding specificities of transcription factors (TFs) and other regulatory proteins. We analyzed 765 ENCODE ChIP-seq peak datasets of 207 human TFs with a novel motif discovery pipeline based on recursive, thresholded entropy minimization. This approach, while obviating the need to compensate for skewed nucleotide composition, distinguishes true binding motifs from noise, quantifies the strengths of individual binding sites based on computed affinity and detects adjacent cofactor binding sites that coordinate with the targets of primary, immunoprecipitated TFs. We obtained contiguous and bipartite information theory-based position weight matrices (iPWMs) for 93 sequence-specific TFs, …