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SUMMARY:Stochastic models of gene transcription with upstream drives: Exac
 t solution and sample path characterisation - Justine Dattani (Imperial Co
 llege London)
DTSTART:20160613T140000Z
DTEND:20160613T150000Z
UID:TALK66430@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Gene transcription is a highly stochastic\, dynamic process. A
 s a result\, the mRNA copy number of a given gene is heterogeneous both be
 tween cells and across time. I will present a framework to model gene tran
 scription in populations of cells with time-varying (stochastic or determi
 nistic) transcription and degradation rates. Such rates can be understood 
 as upstream cellular drives representing the effect of different aspects o
 f the cellular environment\, e.g. external signalling\, circadian rhythms\
 , or chromatin remodelling. I will show that the full solution of the gene
 ric master equation for gene transcription contains two components:   a mo
 del-specific\, upstream effective drive\, which encapsulates the effect of
  the cellular drives (e.g.\, entrainment\, periodicity or promoter randomn
 ess)\, and a downstream transcriptional Poissonian part\, which is common 
 to all models. This analytical framework allows us to treat cell-to-cell a
 nd dynamic variability consistently\, unifying several approaches in the l
 iterature.  &nbsp\;  Our general solution confers to us two broad advantag
 es. The first is  pragmatic: the theory provides us with new approaches fo
 r solving non-stationary gene transcription models\, analysing single-cell
  snapshot and time-course data\, and reducing the computational cost of sa
 mpling solutions via stochastic simulation. The second advantage is concep
 tual:   studying the solution of a broad class of models in generality pro
 vides us with physical intuition for the sources of noise and their charac
 teristics\, and the ability to deduce which models are analytically solvab
 le (along with the form and structure of their solutions). I will demonstr
 ate some such benefits by applying our solution to several biologically-re
 levant examples.
LOCATION:Seminar Room 2\, Newton Institute
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