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Our group at MIT aims to further our understanding of the human genome by computational integration of large-scale functional and comparative genomics datasets. (1) We use comparative genomics of multiple related species to recognize evolutionary signatures of protein-coding genes, RNA structures, microRNAs, regulatory motifs, and individual regulatory elements. (2) We use combinations of epigenetic modifications to define chromatin states associated with distinct functions, including promoter, enhancer, transcribed, and repressed regions, each with distinct functional properties. (3) We use dynamics of functional elements across many cell types to link regulatory regions to their target genes, predict activators and repressors, and cell type specific regulatory action. (4) We combine these evolutionary, chromatin, and activity signatures to dramatically expand the annotation of the non-coding genome, elucidate the regulatory circuitry of the human and fly genomes, and to revisit previously uncharacterized disease-associated variants, providing mechanistic insights into their likely molecular roles
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