Understanding the Science of Disease Through Human Genome Research with Manolis Kellis

In this episode

MIT CSAIL Professor Manolis Kellis discusses how the symbiotic relationship between computer science and biology helps us to better understand the complex programming language that is our DNA. Through DNA, we can find the molecular basis of the pathophysiology of a disease and take a more holistic approach to disease treatment, and one day may even predict disease. He explains the impact of human genome and epigenome research on the pharmaceutical industry in developing medicine that is both precise and personalized, dramatically transforming the therapeutic landscape.

About the speakers

Principal Investigator, MIT CSAIL
Professor, MIT CSAIL

Manolis Kellis obtained his PhD from MIT where he received the Sprowls award for the best doctorate thesis in computer science and the first Paris Kanellakis graduate fellowship. Kellis is also an Associate Professor of Computer Science at MIT, a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and of the Broad Institute of MIT and Harvard, where he directs the MIT Computational Biology Group. He has received a number of awards including: the US Presidential Early Career Award in Science and Engineering (PECASE), the NSF CAREER award, the Alfred P. Sloan Fellowship, and the Karl Van Tassel chair in EECS. Prior to computational biology, Kellis worked on artificial intelligence, sketch and image recognition, robotics, and computational geometry at MIT and at the Xerox Palo Alto Research Center.

Industry Impact
Manolis Kellis research interests are in the area of computational biology, genomics, epigenomics, gene regulation, and genome evolution.

  • In the area of genome interpretation, we seek to develop comparative genomics methods to identify genes and regulatory elements systematically in the human genome.
  • In the area of gene regulation, we seek to understand the regulatory motifs involved in cell types specification during development, understand their combinatorial relationships, and how these establish expression domains in the developing embryo.
  • In the area of epigenomics, we seek to understand the chromatin signatures associated with distinct activity states, the changing chromatin states across different cell types and during differentiation, and the sequencing signals responsible for the establishment and maintenance of chromatin marks.
  • In the area of evolutionary genomics, understanding the dynamics of gene phylogenies across complete genes, the emergence of new gene functions by duplication and mutation, and the algorithmic principles behind phylogenomic.