Back to Faculty/Researchers

Prof. Manolis Kellis (Kamvysselis)

Professor of Computer Science
Institute Member, Broad Institute
Head, MIT Computational Biology Group (CSAIL)

Primary DLC

Department of Electrical Engineering and Computer Science

MIT Room: 32D-524
(617) 253-2419
https://compbio-mit-edu.ezproxy.canberra.edu.au/

Assistant

Geraldine McGowan
(617) 253-3497
gmcgmit@gmail.com

Areas of Interest and Expertise

Pharmaceutical Discovery
Genome Sequencing
Analysis Pipeline
Gene Regulation
Micro-RNA
Computational Biology, Machine Learning and Algorithms in Genomics
Genome Interpretation, Comparative Genomics, Evolutionary Signatures
Gene Regulation: Regulatory Motifs, Biological Networks, Dimensionality Reduction, Epigenomics
Evolution: Phylogenomics, Population Genomics, Human Variation
Disease: Genome-Wide Association Studies (GWAS), Single-Nucleotide Polymorphisms (SNPs), Personal Genomes, Molecular Underpinnings of Common Disease
Big Data

Research Summary

Professor Kellis' research interests are in the area of computational biology, genomics, epigenomics, gene regulation, and genome evolution. Specifically:

(1) in the area of genome interpretation, we seek to develop comparative genomics methods to identify genes and regulatory elements systematically in the human genome

(2) in the area of gene regulation, we seek to understand the regulatory motifs involved in cell type specification during development, understand their combinatorial relationships, and how these establish expression domains in the developing embryo.

(3) 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.

(4) 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 phylogenomics.

Recent Work

  • Video

    10.12.23-AI-Driven-Kellis

    October 12, 2023Conference Video Duration: 31:42
    Using Biochemical Data Sets, Optimized with Genomic Data, to Train Machine Learning Models for Therapeutic Development 

    10.12.23-AI-Driven-Panel

    October 12, 2023Conference Video Duration: 22:39
    Panel Discussion 

    4.4.23-Health-Kellis

    April 4, 2023Conference Video Duration: 32:10
    From Genomics to Therapeutics: Single-Cell Dissection and Manipulation of Disease Circuitry 

    3.25.21-Health-Roundtable

    March 25, 2021Conference Video Duration: 89:1
    Manolis Kellis
    Professor, MIT Computer Science and Artificial Intelligence Lab
    Institute Member, Broad Institute of MIT and Harvard
    Ernest Fraenkel
    Professor, Biological Engineering
    Associate Member, Broad InstituteJuan Caicedo
    Schmidt Fellow, Broad Institute
    Caroline Uhler
    Associate Professor, Electrical Engineering and Computer Science and Institute for Data, Systems and Society
    Dipen Sangurdekar
    Head of Oncology Translational Genomics team, Takeda

    3.23.21-Health-Manolis-Kellis

    March 23, 2021Conference Video Duration: 17:11
    Manolis Kellis
    Professor, MIT Computer Science and Artificial Intelligence Lab
    Institute Member, Broad Institute of MIT and Harvard

Related Faculty

Prof. Elfar Adalsteinsson

Eaton-Peabody Professor of Electrical Engineering and Computer Science

Prof. Randall Davis

Professor of Computer Science and Engineering

Dr. Deanna Montgomery

Manager, Electrical Engineering and Computer Science Communication Lab