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Title:An Evolutionary Computation Model of Intracellular Signaling Networks
Author(s):Zou, Lihua
Doctoral Committee Chair(s):Mittenthal, Jay E.
Department / Program:Biophysics and Computational Biology
Discipline:Biophysics and Computational Biology
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Biophysics, General
Abstract:We use evolutionary computation (EC) methods to simulate the evolution of a particular class of intracellular signaling networks. This class of signaling networks mimics the cellular state transition (or mode switch) in a living cell in response to a specific number of prerequisites. Two different signaling regulations, namely absence receptor regulation and presence receptor regulation, are represented in our network model. An evolutionary argument based on a minimum evolution hypothesis accounts for the empirical observation that an absence receptor-regulated network is more likely to regulate a mode switch than a presence receptor-regulated network. We simulated the evolution of networks regulated by absence and/or presence receptors. The only simulation that produced networks of maximum fitness had only absence receptors. We developed a model to calculate the probability of evolving a maximum-fitness, minimum-evolution network. The calculation gives a qualitative view of the complexity of signaling network evolution.
Issue Date:2004
Description:63 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.
Other Identifier(s):(MiAaPQ)AAI3131064
Date Available in IDEALS:2015-09-25
Date Deposited:2004

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