We are a computational genomics group focused on understanding the genetics, development, and evolution of complex phenotypes and disease.
Our research is primarily computational, involving the development and application of techniques that fall within the disciplines of computational statistics and machine learning,
although we also complement these efforts with our own experimental research.
Current projects include regularized regression techniques for genome-wide association studies (GWAS),
probabilistic graphical modeling algorithms for biological network discovery,
application of next-generation sequencing data to problems in medical genomics,
and combined experimental and computational analysis of developmental network connections in Drosophila.
Our research also includes collaborations with groups working in medical, agricultural, and evolutionary fields.
Please see our “Research” pages for more information.
We have a dual appointment in the Department of Biological Statistics and Computational Biology
at Cornell in Ithaca and in the
Department of Genetic Medicine
at Weill Cornell Medical College in New York City. Our group includes members at both locations,
working on complimentary problems in computational biology and medical genomics. We are currently growing in both locations and we encourage you to look at
the Positions page
if you might be interested in joining us.
We are funded by the National Science Foundation and the
National Institutes of Health,
please see our Grants for more information.
We are members of and are supported by the Cornell Center for Comparative and Population Genomics,
the Cornell Center for Vertebrate Genomics,
and the Institute for Computational Biomedicine at Weill Cornell.