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SUMMARY:Inference for stochastic models - Dr Lorenz Wernisch ( MRC Biostat
 istics Unit)
DTSTART:20081023T110500Z
DTEND:20081023T113000Z
UID:TALK14676@talks.cam.ac.uk
CONTACT:Duncan Simpson
DESCRIPTION:Mathematical models are able to capture the essence of dynamic
  biological processes. There is still a gap between the precision and deta
 il of mathematical models and the limitations of experimental data. Flow c
 ytometry techniques\, for instance\, provide data on gene regulation in si
 ngle cells but usually only on very few variables. Many of the processes r
 esponsible for variety between cells are unobserved and are best modelled 
 by general noise terms. Noise due to fluctuation on the molecular level mi
 ght also play a role. That is\, simplification of models and explicit mode
 lling of noise is required if such models are fitted to currently availabl
 e data.
LOCATION:Kaetsu Centre\, New Hall
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