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SUMMARY:Biochemical network reconstruction from data - Jorge Goncalves\, D
 epartment of Engineering
DTSTART:20091102T160000Z
DTEND:20091102T170000Z
UID:TALK18993@talks.cam.ac.uk
CONTACT:Laura Blackburn
DESCRIPTION:One of the fundamental interests in systems biology is the dis
 covery\nof the specific biochemical mechanisms that explain the observed\n
 behaviour of a particular system. These mechanisms are composed of a\ncomp
 lex network of reactions between various chemical species\;\ndetailing the
  species and interactions forming this network can be an\noverwhelming tas
 k\, even for the simplest of biochemical systems.\n\nIn spite of the intri
 nsic difficulty of network reconstruction\, our\nresearch outlines the exp
 erimentation process that makes such\ndiscovery possible. If nothing is kn
 own about the network between\nmeasured species\, then experiments must be
  performed as follows: \n# \nfor a network composed of p measured species\
 , the same number of\nexperiments p must be performed\; \n#  each experime
 nt must\nindependently control a measured specie\, i.e.\, control input i 
 must\nfirst affect measured specie i (e.g. experiments involving gene\nsil
 encing or inducible overexpression). \n\nIf something is known about\nthe 
 system\, then these experiments may be relaxed. The network\nrepresentatio
 n resulting from this process yields a predictive model\ncommensurate with
  the informativity of the data used to create it:\nsteady-state data yield
  static network information\, while time series\ndata generate a dynamic r
 epresentation of the system suitable for\nsimulation.\n\nFurther\, we demo
 nstrate that in the absence of this essential\nexperimental design\, the n
 etwork cannot be reconstructed and every\nconceivable network structure be
 tween species (e.g. a fully decoupled network or a fully connected network
 ) can be equally descriptive of\nany particular set of input-output data. 
 Unless this correct\nmethodology is followed\, any best-fit measure for ne
 twork\nreconstruction can yield arbitrarily poor and misleading results.\n
LOCATION:Cancer Research UK Cambridge Research Institute\, Lecture Theatre
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