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SUMMARY:'Analyses for Rule-Based Models of Cellular Signalling' - Dr Jean 
 Yang\, Assistant Professor\,Department of Computer Science\, Carnegie Mell
 on University\, Pittsburgh USA 
DTSTART:20170525T140000Z
DTEND:20170525T150000Z
UID:TALK72730@talks.cam.ac.uk
CONTACT:Mala Jayasundera
DESCRIPTION:*Abstract*:\nIn prediction and diagnosis\, important questions
  include “when?” and “how?” For instance\, in cellular signalling\
 , we may want to understand the events that lead to apoptosis\, both in te
 rms of what events may trigger apoptosis\, and the specific mechanism of t
 he apoptosis.  Typically\, understanding these systems have involved trans
 lating intuitions about cause and mechanism into low-level models\, and th
 en matching the low-level models to experimental data.\n\nMy work focuses 
 on a modeling approach that provides enough structure to allow for automat
 ed analysis of mechanism and cause.  We have been using Kappa\, a rule-bas
 ed graph-rewrite language that supports the modeling of intracellular sign
 alling as stochastic transformations over graphs of protein agents\, where
  edges represent protein complexes.  One of the main advantages of using K
 appa is that we can leverage the structure of the rules\, combined with a 
 precise understanding of Kappa’s semantics\, for interesting and useful 
 analyses.  My research group has been focused on analyses involving causal
 ity between rules: given two rules r and s\, does rule r need to trigger b
 efore rule s in order to reach the event of interest?  In this talk\, I wi
 ll introduce Kappa\, present an overview of our formulation of causality\,
  and discuss our work on combining causal analysis with statistical model 
 checking techniques.  I will present ongoing work on tools for 1) relative
  frequency analysis for different pathways in a model and 2) finer-grained
  inhibition analysis.\n\n*Bio.* Jean Yang is an Assistant Professor positi
 on in the Computer Science Department at Carnegie Mellon University.  She 
 received her AB from Harvard and PhD from MIT.  Her research interests are
  in developing programming models and tools towards making provable guaran
 tees ubiquitous.  During her PhD she created a programming language\, Jeev
 es\, that factors information flow checks out of the rest of the program. 
  Her paper on Verve\, and operating system verified for type safety\, rece
 ived Best Paper Award at PLDI 2010.  Jean also works on analysis tools for
  modeling intracellular signalling using rule-based graph-rewrite programs
 .
LOCATION:Sackler Lecture Theatre (Level 7)\, Cambridge Institute for Medic
 al Research
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