Manolis Kellis, Ph.D. (Massachusetts Institute of Technology/Broad Institute, Computer Science) has worked in the field of regulatory genomics and epigenomics for the last 10 years. He pioneered the first methods for the de novo discovery of regulatory motifs using genome-wide comparative genomics and applied them systematically in the human, fly and yeast genomes to discover dictionaries of known and novel regulatory motifs across the genome. He also developed new methods for identifying conserved instances of regulatory motifs across the human genome, resulting in a global map of conserved regulatory motifs and regulatory elements, published as part of the 29 mammals consortium. He also pioneered new methods for studying combinations of chromatin modifications to reveal biologically meaningful chromatin states and applied these in the context of the NIH ENCODE, modENCODE and Epigenomics Roadmap projects to discover diverse classes of enhancers, promoters, and insulators, and thousands of new long non-coding RNAs based on their chromatin and evolutionary signatures. He also developed methods for linking enhancers to their upstream regulators and downstream target genes based on their correlated activity patterns, resulting in dense regulatory networks in humans. His group has used these regulatory genomics and epigenomics tools to interpret the role of genetic variation in the context of molecular variation and human disease. His group was the first to show that disease-associated loci from GWAS are enriched in enhancer chromatin states for relevant human cell types, providing an unbiased method for predicting the likely regulatory roles of disease-associated variants across the whole genome. In the context of the ENCODE project, he also studied allele-specific activity in chromatin marks and showed that it correlated with the strength of predicted causal motif matches between the paternal and maternal genomes, providing a mechanistic basis for the observed differences.