Statistic Research Group

TITLE: Some new results on estimating reaction constants in stochastic intracellular networks
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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.