Speaker
Ramon Grima
(University of Edinburg)
Description
Exact solutions of the chemical master equation are only
known for a handful of simple chemical systems. In the past
decade, the linear-noise approximation (LNA) has become a
popular means to systematically approximate the master
equation and to hence obtain insight into the effect of
noise on the dynamics of biochemical systems. However a
number of assumptions underlying the LNA considerably limit
its application to realistic biochemical networks; these are
the assumptions that molecule numbers are not too small and
that the probability distribution is unimodal. In this talk,
I will discuss recent theoretical developments which (i)
extend the LNA to multimodal systems, and (ii) correct the
LNA estimates of mean concentrations and variances by
consideration of higher-order terms in the system-size
expansion. The usefulness of these methods to obtaining a
more complete picture of stochastic biochemical dynamics
will be showcased on various biochemical systems involving
gene expression, feedback control, enzyme-mediated catalysis
and circadian rhythms.
