- Series
- Mathematical Biology Seminar
- Time
- Wednesday, February 3, 2010 - 11:00am for 1 hour (actually 50 minutes)
- Location
- Skiles 255
- Speaker
- Ilya Nemenman – Emory University
- Organizer
- Leonid Bunimovich

Even the simplest biochemical networks often have more degrees of freedoms than one can (or
should!) analyze. Can we ever hope to do the physicists' favorite trick of coarse-graining,
simplifying the networks to a much smaller set of effective dynamical variables that still
capture the relevant aspects of the kinetics? I will argue then that methods of statistical
physics provide hints at the existence of rigorous coarse-grained methodologies in modeling
biological information processing systems, allowing to identify features of the systems that are
relevant to their functions. While a general solution is still far away, I will focus on a
specific example illustrating the approach. Namely, for a a general stochastic network
exhibiting the kinetic proofreading behavior, I will show that the microscopic parameters of the
system are largely important only to the extent that they contribute to a single aggregate
parameter, the mean first passage time through the network, and the higher cumulants of the
escape time distribution are related to this parameter uniquely. Thus a phenomenological model
with a single parameter does a good job explaining all of the observable data generated by this
complex system.