4/12 – Yang Dai, University of Illinois at Chicago

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Speaker: Yang Dai

Associate Professor, Alternative Director of Graduate Studies (Bioinformatics Program), Department of Bioengineering, University of Illinois at Chicago

Title: Learning regulatory mechanisms of DNA methylation using convolutional neural networks

Abstract: 

DNA methylation of CpG dinucleotides plays key roles in cellular differentiation and development, pathogenesis of diseases, cancer, and aging. Mounting evidence suggests the association of CpG methylation to gene expression. However, their mechanisms in regulating gene expression are complex. The correlation analysis of CpG methylation on promotors and gene coding regions cannot fully explain gene expression.  We present a computational framework based on convolutional neural networks (CNNs) to integrate information of methylations, DNA sequences from multiple genomic regions to discern the relationship with gene expression. Using data of 8 cell types from ENCODE, we show that the filters from the convolution layers of the trained CNN uncover the motifs of important methylation modulator genes, suggesting potential mechanisms of DNA methylation on gene regulation. We further introduce our recent work on extending CNNs to integrate additional histone modification data in the analysis.