Ph.D., Cornell University, 2002
Population genetics; bioinformatics; cancer; stochastic processes; statistical mechanics and information theory
A common thread in our research is the quest to understand collective biological phenomena from the perspective of the physical sciences. To this end, we develop and deploy mathematical and computational tools to address quantitative principles governing the behavior of many-body biological systems, ranging from molecular interactions in a single eukaryotic cell to the evolution of the species Homo sapiens.
Fueled by large-scale genotyping technologies, we have recently focused on population genetics with a view to understanding the evolutionary forces at play on the genome and to underpin the genetics of some human diseases. Patterns of genetic variation in a population, such as single nucleotide polymorphisms and copy number variants, are shaped by a number of confounding factors such as random mutation, sampling drift, recombination, population structure and natural selection. It remains a challenge in population genetics to address the so-called “inverse problem”, i.e. utilize the genetic variation data to uncover the evolutionary forces.
Some recent projects include:
(1) Recent natural selection in humans. We are combining Bayesian inference and information-theoretic techniques to determine population structure and evidence of recent natural selection in the human genome.
(2) Statistical physics of population genetics. We seek to use the language of statistical physics to provide a reduced description of the essential features of stochastic allelic evolution.
(3) Haplotype analysis of the p53 network. A collaborative effort has shown that some of the genes in the p53 tumor suppressor network play a role in the regulation of fertility in mice and humans.
Please visit Mickey's Lab home page.
Atwal, G.S., Kirchhoff, T., Bond, E.E., Montagna, M., Menin, C., Bertorelle, R., Scaini, M.C., Bartel, F., Böhnke, A., Pempe, C., Gradhand, E., Hauptmann, S., Offit, K., Levine, A.J., Bond, G.L. 2009. Altered tumor formation and evolutionary selection of genetic variants in the human MDM4 oncogene. Proc. Natl. Acad. Sci. USA 106: 10236-41.
Hu, W., Feng, Z., Atwal, G.S., and Levine, A.J. 2008. p53: A new player in reproduction. Cell Cycle 7: 848-852.
Atwal, G.S., Rabadan, R., Lozano, G., Strong, L.C., Ruijs, M.W., Schmidt, M K., Veer, L. J., Nevanlinna, H., Tommiska, J., Aittomaki, K., Bougeard, G., Frebourg, T., Levine, A.J., and Bond G.L, 2008. An information-theoretic analysis of genetics, gender and age in cancer patients. PLoS ONE 3: e1951.
Atwal, G.S., Bond, G.L., Metsuyanim, S., Papa, M., Friedman, E., Distelman-Menachem, T., Ben-Asher, E., Lancet, D., Ross, D.A., Sninsky, J., White, T., Levine, A.J., and Yarden, R. 2007. Haplotype structure and selection of the MDM2 oncogene in humans. Proc. Natl. Acad. Sci. USA 104: 4524-4529.
Slonim, N., Atwal, G.S., Tkacik G., and Bialek, W. 2005. Information based Clustering. Proc. Natl. Acad. Sci. USA 102: 18297-18302.