Associate Professor of Biology, Physics
Ph.D. (Physics), Harvard.
|New York University|
|Department of Biology|
|Center for Genomics and Systems Biology|
|12 Waverly Place, Room 206|
|New York, NY 10003|
Areas of Research/Interest:
Computational biology, evolution, and biological physics
Classical studies of molecular biology revealed how cells sense their environment and respond to change, establishing the centrality of gene regulation in cellular physiology. Numerous mechanisms in bacteria, however, function in a largely deregulated way, generating a diversity of responses across the population, without necessarily sensing the environment. The existence of such stochastic mechanisms raises several (increasingly difficult) questions: (1) How do microorganisms employ stochasticity to their advantage? (2) Can we distinguish such adaptive stochasticity from useless noise that is simply too costly for cells to avoid? (3) How, and under what circumstances, do sensing mechanisms evolve? My research employs theoretical and computational modeling of bacteria populations in fluctuating environments, and comparative genomics of experimentally-characterized stochastic switches.
Closely related topics of research include the evolution of mutation rates, mutator phenotypes, and mutational hotspots in genomes. My other interests include protein folding and protein evolution.
I received my Ph.D in Biophysics from Harvard University, where I worked with Eugene Shakhnovich on physical aspects of protein folding, including relaxation dynamics and packing of protein sidechains, high-resolution Monte Carlo simulation of folding, and theory related to protein evolution. I went on to do post-doctoral work with Stanislas Leibler at The Rockefeller University where, starting with simple models of antibiotic persistence in E. coli, we worked towards understanding in some generality the evolutionary advantage of stochastic phenotype switches in microorganisms. We eventually found that these mechanisms are intimately connected with information acquisition in a general sense, and that in certain cases the evolutionary advantage of phenotype switching can be expressed in purely information theoretic terms. I joined the NYU faculty in the Department of Biology in September 2006, where I am working on theory and modeling of evolution in microorganisms.
Biol-GA.1131 (cross-listed as MATH-GA.2852/PHYS-GA.2081) Biophysical Modeling of Cells and Populations
PubMed Search Results:
- Search: Kussell E[Author]
- Retrieved: January 04 2017