I am a computer scientist who is fascinated by the challenge of making sense of vast quantities of genetic data. My research group focuses in particular on questions involving human evolution and transcriptional regulation.
Modern genomic technologies make it relatively easy to generate rich data sets describing genome sequences, RNA expression, chromatin states, and many other aspects of the storage, transmission, and expression of genetic information. For many problems in genetics today, the limiting step is no longer in data generation, but in integrating, interpreting, and understanding the available data. Addressing these challenges requires expertise both in the practical arts of data analysis and in the theoretical underpinnings of statistics, computer science, genetics, and evolutionary biology.
My group focuses on a diverse collection of research questions in this interdisciplinary area. Over the years, our research has touched on topics including the identification of recombinant strains of HIV, the discovery of new human genes, the characterization of conserved regulatory elements in mammalian genomes, and the estimation of the times in early human history when major population groups first diverged. A general theme in our work is the development of precise mathematical models for the complex processes by which genomes evolve over time, and the use of these models, together with techniques from computer science and statistics, both to peer into the past, and to address questions of practical importance for human health. Recently, we have increasingly concentrated on research at the interface of population genomics and phylogenetics, with a particular focus on humans and the great apes. We also have an active research program in computational modeling and analysis of transcriptional regulation in mammals and Drosophila, in close collaboration with Prof. John Lis at Cornell University.
John Simon Guggenheim Memorial Foundation Fellowship, 2012-2013.
Alfred P. Sloan Foundation Research Fellowship, 2009-2011.
David & Lucile Packard Foundation Fellowship for Science and Engineering, 2007.
Microsoft Research Faculty Fellowship Program, 2007.
National Science Foundation (NSF) CAREER Award, 2007.
How much are we learning? Natural selection is science’s best critic
December 17, 2018
Researchers determine that natural selection and our evolutionary history may be the best guides for future research.
A science writer’s quest to understand heredity
May 30, 2018
LabDish spoke with science writer Carl Zimmer about what he learned about heredity as he zig-zagged through CSHL while writing his new book.
Evolving sets of gene regulators explain some of our differences from other primates
January 29, 2018
What makes us different from our primate relatives? Gene regulation is one important evolutionary factor
A lesson in class
December 15, 2017
In this episode of Base Pairs, we discuss how genetic information is changing how we define important categories.
August 15, 2016
This episode on Base Pairs explores how genetic information to better understand human history.
Neanderthals mated with modern humans much earlier than previously thought, study finds
February 12, 2016
Using several different methods of DNA analysis, an international research team has found what they consider to be strong evidence of interbreeding.
Harnessing data from nature’s great evolutionary experiment
January 21, 2015
Scientists develop a computational method to estimate the importance of each letter in the human genome
New senior faculty join CSHL
November 10, 2014
Interviews with new faculty Adam Siepel and Douglas Fearon.
Re-learning how to read a genome
November 10, 2014
Study suggests a unified model for how DNA is read, offering insight into how genes evolve
CSHL receives $50 million to establish Simons Center for Quantitative Biology
July 7, 2014
CSHL announced a $50 million gift from Jim and Marilyn Simons to establish the Simons Center for Quantitative Biology.
Kuhlwilm, M. and Gronau, I. and Hubisz, M. J. and de Filippo, C. and Prado-Martinez, J. and Kircher, M. and Fu, Q. and Burbano, H. A. and Lalueza-Fox, C. and de la Rasilla, M. and Rosas, A. and Rudan, P. and Brajkovic, D. and Kucan, Z. and Gusic, I. and Marques-Bonet, T. and Andres, A. M. and Viola, B. and Paabo, S. and Meyer, M. and Siepel, A. and Castellano, S. (2016) Ancient gene flow from early modern humans into Eastern Neanderthals. Nature, 530(7591) pp. 429-433.
Gulko, B. and Hubisz, M. J. and Gronau, I. and Siepel, A. (2015) A method for calculating probabilities of fitness consequences for point mutations across the human genome. Nature Genetics, 47(3) pp. 276-283.
Rasmussen, M. D. and Hubisz, M. J. and Gronau, I. and Siepel, A. (2014) Genome-wide inference of ancestral recombination graphs. PLoS Genetics, 10(5) pp. e1004342.
Gronau, I. and Hubisz, M. J. and Gulko, B. and Danko, C. G. and Siepel, A. (2011) Bayesian inference of ancient human demography from individual genome sequences. Nat Genet, 43(10) pp. 1031-4.
Pollard, K. S. and Hubisz, M. J. and Rosenbloom, K. R. and Siepel, A. (2010) Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res, 20(1) pp. 110-21.Additional materials of the author at
CSHL Institutional Repository