We work in a highly interdisciplinary environment at the interface of computer science and biology. Members of the group come from a primarily computational background and share a strong passion for understanding biological systems. We are engaged in several collaborative research partnerships with biological and experimental collaborators, at the Broad Institute, the ENCODE, modENCODE and Epigenomics Roadmap Consortia, the Harvard Medical School, and other universities.

MIT Computational Biology Group

Our work focuses on the computational foundations of genomics, developing algorithmic, statistical, and machine learning methods to interpret the functional elements encoded in the human genome, reconstruct the regulatory circuits they define, and understand their evolutionary mechanisms.

Our research focuses on the following major questions, central to our understanding of biological systems:

Genome Interpretation: We have developed comparative genomics methods which can directly discover diverse functional genomic elements based on their characteristic patterns of evolutionary change across related species. These "evolutionary signatures" are dictated by precise functional constraints unique to each class of functional elements, thus enabling their genome-wide discovery. We have used such signatures in the human, fly, and yeast genomes to recognize protein-coding genes and exons, RNA genes and structures, microRNAs and their targets, and diverse classes of regulatory elements. This has resulted in many surprising findings and new insights, including extensive stop-codon read-through in adult brain proteins, novel types of RNA structures involved in post-transcriptional and translational regulation, miRNA targeting in protein-coding regions, functionality of both arms of a miRNA hairpin, and both sense and anti-sense miRNAs, and the discovery of a new class of long intergenic non-coding RNAs.
More on: Genome Interpretation - Protein-coding Genes - Non-coding RNAs
Gene regulation: We have also developed computational methods to study the cellular circuitry of genomes, which directs gene expression levels in response to environmental and developmental stimuli. Our work has resulted in global maps of regulatory elements in yeast and animal genomes, and their role in specifying pre- and post-transcriptional gene regulatory networks. Combining comparative genomics with experimental datasets, we have studied condition-specific and tissue-specific activation networks, and revealed new insights on activation and silencing of developmental genes, and post-transcriptional targeting by miRNA genes.
Read more on: Chromatin - Regulatory Motifs - Biological Networks
Epigenomics: With the recent availability of genome-wide maps of histone modifications, we have developed new methods for the systematic discovery of recurrent combinations of chromatin marks, or "chromatin signatures," which we found to be associated with very specific types of functional elements, including diverse classes of enhancers, promoters, and insulators. We have used these signatures to discover new elements, including novel non-coding RNA genes, and to systematically study the dynamics of chromatin state across tissues and during development, and to discover the sequence elements and grammars governing those changes. We are currently also exploring the role of small non-coding RNAs in the establishment, maintenance, and targeting of chromatin state.
More on: Epigenetics - Regulatory RNAs
Genome evolution: We have also developed methods to study systematic differences between the species compared, and uncovered important evolutionary mechanisms for the emergence of new functions. Our work provided definitive proof of an ancestral whole-genome duplication in yeast, which led to a complete doubling of the gene count, and was rapidly followed by massive gene loss, asymmetric divergence, and new gene functions. To further understand the evolutionary processes leading to new functions, we developed a phylogenomic framework for studying gene family evolution in the context of complete genomes, revealing two largely independent evolutionary forces, dictating gene- and species-specific mutation rates. De-coupling these two rates also allowed us to develop the first machine-learning approach to phylogeny, resulting in drastically higher accuracies than any existing phylogenetic method.
More on: Evolution - Phylogenomics.

We are located on the 5th floor (D5) of MIT Stata Center, a truly unique building that stretches the imagination, and home of the Computer Science and Artificial Intelligence Lab (CSAIL). We are just across Main Street from the Broad Institute, which boasts a unique collaborative environment for genomics, and we have weekly meetings in both institutions.

Positions Available

Selected Publications

Defining functional DNA elements in the human genome (pdf)
Evolutionary dynamics and tissue specificity of human long noncoding RNAs in six mammals (pdf)
Genome-wide probing of RNA structure reveals active unfolding of mRNA structures in vivo (pdf)
Systematic discovery and characterization of regulatory motifs in ENCODE TF binding experiments (pdf)
Most parsimonious reconciliation in the presence of gene duplication, loss, and deep coalescence using labeled coalescent trees (pdf)
Extensive Variation in Chromatin States Across Humans (pdf)
Reconciliation revisited: handling multiple optima when reconciling with duplication, transfer, and loss (pdf)
Network deconvolution as a general method to distinguish direct dependencies in networks (pdf)
Systematic dissection of regulatory motifs in 2,000 predicted human enhancers using a massively parallel reporter assay (pdf)
Interpreting noncoding genetic variation in complex traits and human disease (pdf)
Evidence of Abundant Purifying Selection in Humans for Recently Acquired Regulatory Functions (pdf)
An integrated Encyclopedia of DNA elements in the human genome (pdf)
A high-resolution map of human evolutionary constraint using 29 mammals (pdf)
Mapping and analysis of chromatin state dynamics in nine human cell types (pdf)
A Cis-Regulatory Map of the Drosophila Genome (pdf)
Comprehensive analysis of the Drosophila melanogaster chromatin landscape differentiates among chromosomes, genes, and regulatory elements (pdf)
Identification of functional elements and regulatory circuits in Drosophila by large-scale data integration (pdf)
Discovery and characterization of chromatin states for systematic annotation of the human genome (pdf)
Evolution of pathogenicity and sexual reproduction in eight Candida genomes (pdf)
Histone modifications at human enhancers reflect global cell-type-specific gene expression (pdf)
Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammal (pdf)
Discovery of functional elements in 12 Drosophila genomes using evolutionary signature (pdf)
Systematic discovery of regulatory motifs in human promoters and 3' UTRs by comparison of several mammal (pdf)
Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisia (pdf)
Sequencing and comparison of yeast species to identify genes and regulatory motif (pdf)

Group leader: Manolis Kellis
Associate Professor of Computer Science
Karl Van Tassel Career Development Chair

Presidential Early Career Award in Science and Engineering (PECASE), 2008
Alfred P. Sloan Foundation Award, 2008
National Science Foundation Career Award, 2007
Karl Van Tassel Career Development Chair, 2007
Technology Review TR35 Top Young Innovators, 2006
Distinguished Alumnus 1964 Career Development Chair, 2005

Contact: MIT Stata Center, 32D-524
32 Vassar St, Cambridge, MA 02139
617-253-2419, x3-3434, x3-6079, x3-6284
k.e.l.l.i.s.l.a.b (without the dots) at mit dot edu
Assistant: Teresa Cataldo 32G-475 617-452-5005
cataldo@csail.mit.edu Fax: 617-253-6652

Massachusetts Institute of Technology

Broad Institute of MIT and Harvard

Computer Science and Artificial Intelligence Lab

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