An Evolutionary Computation Model of Intracellular Signaling Networks
Zou, Lihua
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https://hdl.handle.net/2142/85438
Description
Title
An Evolutionary Computation Model of Intracellular Signaling Networks
Author(s)
Zou, Lihua
Issue Date
2004
Doctoral Committee Chair(s)
Mittenthal, Jay E.
Department of Study
Biophysics and Computational Biology
Discipline
Biophysics and Computational Biology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Biophysics, General
Language
eng
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.
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