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SUMMARY:Inferring Signaling Pathway Topologies from Multiple Perturbation 
 Measurements of Specific Biochemical Species : A model-based approach - Ma
 rk Girolami\, University of Glasgow
DTSTART:20100121T110000Z
DTEND:20100121T120000Z
UID:TALK22775@talks.cam.ac.uk
CONTACT:Microsoft Research Cambridge Talks Admins
DESCRIPTION:The specification of biological decisions by signaling pathway
 s is encoded by the interplay between activation dynamics and network topo
 logies. While we can describe complex networks\, we cannot easily determin
 e which topology is actually realized to transduce a specific signal. Expe
 rimental testing of all plausible topologies is infeasible due to the comb
 inatorially large number of experiments required to explore the complete h
 ypothesis space. Here\, it is demonstrated that Bayesian inference-based m
 odeling provides a formal and systematic approach to explore and constrain
  this hypothesis space permitting the rational ranking of pathway models. 
 Importantly\, this approach can use measurements of a limited number of bi
 ochemical species when combined with multiple perturbations. As proof-of-c
 oncept the activation of the Extracellular signal regulated Kinase (ERK) p
 athway by Epidermal Growth Factor (EGF) was examined. The predicted and ex
 perimentally validated model shows that both Raf-1 and\, unexpectedly\, B-
 Raf are needed to fully activate ERK. Thus\, this formal methodology ratio
 nally infers evidentially supported pathway topologies even when a limited
  amount of measurements is available. \n
LOCATION:Small public lecture room\, Microsoft Research Ltd\, 7 J J Thomso
 n Avenue (Off Madingley Road)\, Cambridge
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