Bayesian inference for stochastic intracellular reaction network<br/><br/>models

Tuesday, May 13, 2008 - 1:45pm - 2:45pm
EE/CS 3-180
Darren Wilkinson (University of Newcastle upon Tyne)
This talk will provide an overview of computationally intensive
methods for conducting Bayesian inference for the rate constants of
stochastic kinetic intracellular reaction network models using
single-cell time course data. Inference for the true Markov jump
process is extremely challenging in realistic scenarios, so the true
model will be replaced by a diffusion approximation, known in this
context as the Chemical Langevin Equation (CLE). Inference for the CLE
is also challenging, but the development of effective algorithms is
possible, and turns out to be extremely effective, even in scenarios
where one would expect the diffusion approximation to break down.

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