BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Structure Ranking and System Identification for Non-Linear Biochem
 ical Process Models: Inferring the Structure of the ERK Pathway via Bayes 
 Factors - Mark Girolami\, University of Glasgow
DTSTART:20080610T133000Z
DTEND:20080610T143000Z
UID:TALK8552@talks.cam.ac.uk
CONTACT:Nikolaos Demiris
DESCRIPTION:Mechanistic mathematical models of biochemical systems are imp
 ortant tools in the study of cellular processes.  Such models make explici
 t current assumptions about the structure and dynamics of the systems of i
 nterest whilst statistical methodology enables their evaluation against ex
 perimental observation. This talk will present Bayesian statistical method
 s for system identification\, that is\, for the estimation of unmeasured p
 arameters and the dynamics of unobserved species in biochemical models des
 cribed by systems of nonlinear Ordinary Differential Equations (ODE). In a
 ddition a  means of objectively ranking a number of plausible mathematical
 \nmodels based on their evidential support as assessed by Bayes factors wi
 ll be presented. A large scale study of the Extra-Cellular Regulated Kinas
 e(ERK) pathway will be discussed where recent Small Interfering RNA (siRNA
 ) experimental validation of the structural predictions made using the com
 puted Bayes factors is presented.
LOCATION:Large Seminar Room\, 1st Floor\, Institute of Public Health\, Uni
 versity Forvie Site\, Robinson Way\, Cambridge
END:VEVENT
END:VCALENDAR