Yale University

Biological and Biomedical Sciences

Biological and Biomedical Sciences, Yale School of Medicine

BBS Program
Yale University
P.O. Box 208084
New Haven, CT 06520-8084
Tel: 203.785.3735
Fax: 203.785.3734
bbs@yale.edu

Mark Gerstein

 

Molecular Biophysics & Biochemistry; Computational Biology & Bioinformatics; Molecular Cell Biology, Gentics and Development

Professor of Biomedical Informatics, Molecular Biophysics & Biochemistry, and Computer Science

Education

A.B. Harvard 1989
Ph.D. Cambridge 1993

Research Interests

We do research in bioinformatics, applying computational approaches to problems in molecular biology. Broadly, we are interested in large-scale analyses of genome sequences, macromolecular structures, and functional-genomics datasets. It is hoped that these will allow us to address a number of overall statistical questions about macromolecules, relating to their physical properties, cellular function, interactions, and phylogenetic distribution. We are especially focused on the human genome and proteome. Our research involves a number of quantitative techniques, including database design, systematic datamining and machine learning, visualization of high-dimensional data, and molecular simulation. More specifically, we focus on three questions. First, we are interested in annotating the raw human genome sequence, especially in characterizing the vast intergenic regions and one of their most important elements, pseudogenes. Next, we are trying to get at the function of all the protein elements encoded by the genome. Here, we try to characterize function on a large-scale through the use of molecular networks. Finally, for the population of proteins that have known 3D structures, we are trying to see how their function is carried out through motion and how motion can be predicted from packing geometry.

Links

Recent Publications

  • Gerstein, M. and Zheng, D. (2006). The real life of pseudogenes. Sci. Am. 295: 48-55.
  • Kim, P.M., Lu, L.J., Xia, Y., and Gerstein, M.B. (2006). Relating three-dimensional structures to protein networks provides evolutionary insights. Science 314:1938-41.

Mark Gerstein

Contact

E-mail
mark.gerstein@yale.edu