Bayesian Statistics Seminar
North Carolina State University
presents
Dr. Grzegorz A. Rempala
University of Louisville
"Estimating reaction constants in stochastic intracellular networks"
ABSTRACT
One of the key issues of interest in analyzing stochastic kinetic models of reaction networks
involving RNA and DNA molecules.(like e.g., gene transcription) is how to infer the values of
the reaction constants. Under mass action kinetics assumption this is relatively straightforward
when the system trajectories are fully observed, however, this is rarely the case in practice.
The talk shall summarize some recent developments in the area of Bayesian inference for reaction
constants using MCMC methodology in "data-poor " settings. In particular, it shall attempt to
indicate the benefits as well as the challenges of this approach with some examples of inferences
for well-known biochemical networks models like e.g., gene transcription and auto-regulation.
The presented research is partially funded by the NSF-DMS "Focused Research Group" grant
Tuesday, November, 14, 2006
3:30 - 4:30 pm
208 Patterson Hall