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SUMMARY:Evolutionary computation: optimization and inference - Michele For
 lin\, CoSBi
DTSTART:20090311T110000Z
DTEND:20090311T120000Z
UID:TALK14749@talks.cam.ac.uk
CONTACT:Dr Fabien Petitcolas
DESCRIPTION:*Abstract*: Evolutionary computation is a general class of com
 putational tools\, which\ndraw their inspiration from nature. The most fam
 ous evolutionary algorithm\nis the Genetic Algorithm (GA)\, firstly introd
 uced by Holland in the early\n1970s. \nThese kinds of algorithms are usual
 ly based on population of individuals\nthat are iteratively evolved throug
 h an objective\, and they are widely used\nto tackle combinatorial optimiz
 ation problems. \nThe aim of the seminar is to give an overview on evoluti
 onary techniques\,\nmainly focusing on GA\, and their application to syste
 ms biology.\nI will also present an application of integration of evolutio
 nary\nalgorithms and stochastic modelling and simulation (using BlenX lang
 uage)\nto infer reaction rates of a metabolic pathway where just part of t
 he\nexperimental data are available.\n\n\n*Biography*: Michele Forlin obta
 ined a Bachelor's degree (2003) and a Master's degree (2006) in Statistics
  at the University Ca' Foscari of Venice. His tesis focused on the problem
  of experimental design (DoE) for high dimensional biochemical experimenta
 tion using an information theoretical approach. In 2006/2007 he attended t
 he Second level International Master in Computational and Systems Biology 
 at the Microsoft Research - University of Trento Centre for Computational 
 and Systems Biology. From 2005 to 2007 he collaborated with the University
  of Venice Group at the Department of Statistics on the European Project P
 rogrammable Artificial Cell Evolution (PACE). 
LOCATION:Small public lecture room\, Microsoft Research Ltd\, 7 J J Thomso
 n Avenue (Off Madingley Road)\, Cambridge
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