Stochastic modeling of gene expression: exact results and large deviations
This event is part of the Biophysics/Condensed Matter Seminar Series.
Abstract: In several biological systems, phenotypic variations are seen even among geneticallyidentical cells in homogeneous environments. Recent research indicates that such `non-genetic individuality' can be driven by rare events arising from the intrinsic stochasticity of gene expression. Correspondingly there is a need to develop analytical approaches for modeling fluctuations and rare events in stochastic gene expression
In this talk, I will discuss analytical approaches developed by mygroup for stochastic models of gene expression. By developing a
mapping to systems analyzed in queueing theory, we derive
analytical results characterizing mRNA and protein distributions for
general kinetic schemes of gene expression. For models with Poisson
arrivals of mRNAs, we develop a novel approach that leads to
exact analytical results for protein distributions. We combine approaches fromqueueing theory and non-equilibrium statistical mechanics to
characterize large deviations in activity fluctuations for general models of gene expression with promoter-based regulation.