Manolis Kellis, Ph.D.

Professor of Computer Science, Massachusetts Institute of Technology
Member, Broad Institute of MIT and Harvard

Manolis Kellis is a professor of computer science at MIT, a member of the Broad Institute of MIT and Harvard, a member of the Computer Science and Artificial Intelligence Lab at MIT, and head of the MIT Computational Biology Group ( His research spans an unusually broad spectrum of areas, including disease genetics, epigenomics, gene circuitry, noncoding ribonucleic acids (RNAs), comparative genomics and phylogenetics. He has authored more than 150 journal publications that have been cited more than 40,000 times. He has helped direct several large-scale genomics projects, including the Roadmap Epigenomics project, the Encyclopedia of DNA Elements (ENCODE) project, the Genotype Tissue-Expression (GTEx) project, and comparative genomics projects in mammals, flies and yeast. He received the Presidential Early Career Award for Scientists and Engineers (PECASE), the NSF CAREER award, the Alfred P. Sloan Foundation Sloan Research Fellowship, the MIT Technology Review TR35 recognition, the Athens Information Technology (AIT) Niki Award, the Spira Teaching award, and the George M. Sprowls Award for the best Ph.D. thesis in computer science at MIT.

Dr. Kellis lived in Greece and France before moving to the United States, and he studied and conducted research at MIT, the Xerox Palo Alto Research Center, and the Cold Spring Harbor Lab. For more information, please visit

Funded Research

Project Description Researchers Funding
CIRCUITS: Production Center for Reference and Variation Gene-Regulatory Maps

Alzheimer’s disease is a devastating neurodegenerative disorder, afflicting 1 in 3 dying seniors and costing $236 billion annually in the United States alone. Its prevalence is increasing rapidly in an aging population, and currently there is no cure. Recent genetic studies provide new hope for therapeutic avenues, but translating genetic results into therapeutics has been remarkably difficult, due primarily to the fact that most genetic mutations do not alter protein function directly, but instead affect the expression of nearby genes in subtle ways.

CIRCUITS: Functional Analysis of Alzheimer’s Disease Risk Genes Using Human-Induced Pluripotent Stem Cells

The vast majority of people with Alzheimer’s disease (AD) suffer from the sporadic, or late-onset form, which causes remain completely unknown. From studies involving thousands of people, researchers have identified a number of genetic variants that may increase one’s risk for sporadic AD. However, little is understood regarding why these small changes impact one’s risk to develop AD. In this work, we will use the cutting-edge genome editing technique CRISPR/Cas9 to introduce AD-associated genetic variants identified through genome-wide analysis into reprogrammed human stem cells.