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SUMMARY:The Executable Pathway to Biological Networks - Jasmin Fisher\, Mi
 crosoft Research Cambridge
DTSTART:20090608T150000Z
DTEND:20090608T160000Z
UID:TALK17508@talks.cam.ac.uk
CONTACT:Laura Blackburn
DESCRIPTION:Computational modelling of biological systems is becoming incr
 easingly\nimportant in efforts to better understand complex biological beh
 aviours.\n'Executable Biology' is a pioneering approach focused on the des
 ign of\nexecutable computer programs that mimic biological phenomena. Whil
 e\ntraditional mechanistic models in biology are usually described by diag
 rams\n(giving a fairly static picture of cellular processes)\, executable 
 biology\nseeks to translate such static diagrams into dynamic models using
  formal\ncomputational methods that were originally designed for the const
 ruction and\nanalysis of complex man-made systems (e.g.\, computers and co
 mputer\nprograms). \n\nIn this talk\, I will illustrate the usefulness of 
 this framework\nto model signalling pathways using the following examples:
  \n(1) our modelling\nwork of the EGFR/Notch signalling crosstalk during t
 he process of cells fate\ndetermination in C. elegans vulval development. 
 This model brings forward\nintricate timing considerations in the operatio
 n of these signals\, which\nwere also validated experimentally\; \n(2) a m
 ore recent model describing\nmetabolic disturbance in fat tissue with rela
 tion to diabetes and obesity.\nConstructing this model and running it agai
 nst the experimental observations\nhas highlighted two key nodes in the pr
 ocesses of early obesity: the\ntranscription factor Mlxipl\, and the metab
 olic intermediate acetyl CoA. The\nmodel suggests that these act synergist
 ically to affect fatty acid\nproduction\, which is likely to be a key inte
 rmediate phase along the obesity\ntimeline. These provide focus points for
  further biological study\; and \n(3) a\ndetailed analysis of a molecular 
 model describing the EGFR pathway\, leading\nto a more abstract view of th
 e different modules of this network. Our\nanalysis suggests that the pathw
 ay contains regions of functional redundancy\nin the upstream modules. Dow
 nstream modules\, like Ras and ERK\, have fewer\nredundancies\, and strong
  inhibition of specific reactions in those modules\ngreatly attenuates sig
 nal response. We have also identified positive\nfeedback loops whose role 
 is to prolong the active state of key components\,\nand negative feedback 
 loops that help promote signal adaptation and\nstabilization.\n\n
LOCATION:Cancer Research UK Cambridge Research Institute\, Lecture Theatre
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