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SUMMARY:Model Abstraction Methodology for Temporal Behavior Analysis of Mu
 ltiscale Biological Systems - Hiroyuki Kuwahara\, CoSBi
DTSTART:20090513T100000Z
DTEND:20090513T110000Z
UID:TALK14754@talks.cam.ac.uk
CONTACT:Dr Fabien Petitcolas
DESCRIPTION:*Abstract*: As more and more critical biological data become a
 vailable and \nas the biological questions being addressed become more and
  more complex \nand sophisticated\, the complexity to analyze the systems 
 of interests \nbecomes so high that tackling such a problem only with wet-
 lab \nexperiments eventually becomes infeasible. Since /in silico/ experim
 ents \noffer virtually unlimited controllabilities and observabilities of 
 \nbiochemical systems\, computational methods can be an effective tool to 
 \nshed some light on dynamics of biological systems under various \ncondit
 ions. Thus\, integration of computational methods with the process \nof bi
 ological research becomes more imminent.  However\, this growing \nwealth 
 of knowledge about biological processes has also led to the \ndemand for p
 rogressively more sophisticated computational models\, and as \na result\,
  although detailed\, elementary-reaction level models can be \nconstructed
  for a number of experimentally observed systems\, their \neffectiveness i
 s typically limited because of substantial runtime \nrequirements caused b
 y the multi timescale characteristics nature of \nmany biological systems.
   This computational problem becomes more \npronounced with the emerging u
 nderstanding of the ubiquitous role played \nby nonlinear and discrete-sto
 chastic molecular dynamics in gene \nregulatory\, signal transduction\, an
 d other biological systems.  One \npowerful tool to alleviate such complex
  problems is model abstraction \nbased on a biological property of interes
 t.  In this talk\, we will \ndiscuss the automated model abstraction metho
 dology that we have \ndeveloped for multi timescale biological systems.  I
 n particular\, we \nwill focus on application of this methodology to gene 
 regulatory networks.\n\n*Biography*: Hiroyuki Kuwahara obtained his PhD in
  Computer Science from the University of Utah (USA) in 2007. His thesis de
 scribes systematic and automatic model abstraction methodology to efficien
 tly estimate temporal behaviors of genetic regulatory networks. Hiro joine
 d CoSBi in September 2007.
LOCATION:Small public lecture room\, Microsoft Research Ltd\, 7 J J Thomso
 n Avenue (Off Madingley Road)\, Cambridge
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