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Model simplification of signal transduction pathway networks via a hybrid inference strategy

Jia, J.F. and Yue, H. (2008) Model simplification of signal transduction pathway networks via a hybrid inference strategy. In: Proceedings of the 17th IFAC World Congress. International Federation of Automatic Control, Seoul, Korea, pp. 10307-10312. ISBN 978-3-902661-00-5

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    Abstract

    A full-scale mathematical model of cellular networks normally involves a large number of variables and parameters. How to effectively develop manageable and reliable models is crucial for effective computation, analysis and design of such systems. The aim of model simplification is to eliminate parts of a model that are unimportant for the properties of interest. In this work, a model reduction strategy via hybrid inference is proposed for signal pathway networks. It integrates multiple techniques including conservation analysis, local sensitivity analysis, principal component analysis and flux analysis to identify the reactions and variables that can be considered to be eliminated from the full-scale model. Using an I·B-NF-·B signalling pathway model as an example, simulation analysis demonstrates that the simplified model quantitatively predicts the dynamic behaviours of the network.

    Item type: Book Section
    ID code: 7336
    Keywords: cellular, metabolic, cardiovascular, neurosystems, Model formulation, experimental design, Electrical engineering. Electronics Nuclear engineering
    Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
    Department: Faculty of Engineering > Electronic and Electrical Engineering
    Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 05 Feb 2009 13:07
    Last modified: 06 Sep 2014 13:17
    URI: http://strathprints.strath.ac.uk/id/eprint/7336

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