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Steve Pressé Ph.D.
Assistant Professor, Physics
Postdoctoral Fellow, Biophysics, University of California, San Francisco, CA
Ph.D. Chemical Physics, Massachusetts Institute of Technology, Cambridge, MA
B.Sc.Hon. Bio-organic Chemistry, McGill University, Montreal QC
American Chemical Society (ACS)
American Physical Society (APS)
Biophysical Society (BPS)
Recitation Physics 251 -- Heat, Electricity and Optics
I am looking for highly motivated undergraduate and graduate students. If you are 1) interested in building models relevant to biological problems or doing biophysical experiments, 2) like math/programming, then please don't hesitate to send me your CV regardless of your major. See my Lab webpage (statphysbio.physics.iupui.edu) for more details.
My work involves theoretical studies from the level of single molecule to the level of systems biology in collaboration with experiment. At the length scale and time scale relevant to biology, most events are random. That is, events are described using probabilistic models. Often models are necessary to make sense of the data. Yet data is limited and noisy while extracting probabilistic models from data is a challenging (inverse) problem. I develop the theoretical and numerical tools to tackle these problems using techniques motivated from statistical mechanics and stochastic processes.
For instance, my experimental collaborators and I work on a variety of problems which include protein diffusion as it undergoes catalytic reactions and the single molecule mechanics of protein translocation and degradation by molecular motors. I am also interested in chemotaxis from the motor protein to the organismal level.
On the pure theory side, I am interested in two problems primarily. 1) Developing information criteria for model discrimination specifically targeted at single molecule fluorescence and force spectroscopy experiments. 2) Developing an information theoretic basis for ubiquitous models in biophysics (say the Markov process as a simple example). The purpose would be to derive principled generalizations of these models broadly applicable to biophysical problems. For this last project, see our latest two articles in J. Chem. Phys.
S. Pressé, J. Lee, K. Dill, “Extracting conformational memory from single-molecule kinetic data”, J. Phys. Chem. B, 117, 495 (2013)
S. Pressé, K. Ghosh, J. Lee, K. Dill, “Principles of maximum entropy and maximum caliber in statistical physics”, Rev. Mod. Phys., accepted (2013)
J. Lee, S. Pressé, “Microcanonical origin of the maximum entropy principle for open systems”, Phys. Rev. E, 86, 041126 (2012)
J. Lee, S. Pressé, “A derivation of the master equation from path entropy maximization”, J. Chem. Phys., 137, 074103 (2012)
G.J. Peterson, S. Pressé, K. Peterson, K.A. Dill, “Simulated evolution of protein-protein interaction networks with realistic topology”, PLoS ONE, 7, e39052 (2012)
Hao Ge, S. Pressé, K. Ghosh, K.A. Dill, “Markov processes follow from the principle of maximum caliber”, J. Chem. Phys., 136, 064108 (2012) – Selected by the Editors as a Research Highlight.
S. Pressé, K. Ghosh, K.A. Dill, “Modeling stochastic dynamics in biochemical systems with feedback using maximum caliber”, J. Phys. Chem. B, 115, 6202 (2011)
G. J. Peterson, S. Pressé, K.A. Dill, “Nonuniversal power law scaling in the probability distribution of scientific citations”, Proc. Natl. Acad. Sc., 107, 16023 (2010).
For full list of publications, see CV.
Awards & Honors
2008-2010 FQRNT Postdoctoral Fellowship
2007-2008 FQRNT Doctoral Fellowship
2005-2007 NSERC Doctoral Fellowship
2003-2005 NSERC Master’s Fellowship
2004 Outstanding Teaching Award, MIT Chemistry Dept.
For full list of awards, see CV.