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Discrete Dynamic Modeling of Signal Transduction Networks

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Computational Modeling of Signaling Networks

Part of the book series: Methods in Molecular Biology ((MIMB,volume 880))

Abstract

Newly available experimental data characterizing different processes involved in signaling pathways have provided the opportunity for network analysis and modeling of these interacting pathways. Current approaches in studying the dynamics of signaling networks fall into two major groups, namely, continuous and discrete models. The lack of kinetic information for biochemical interactions has limited the wide applicability of continuous models. To address this issue, discrete dynamic models, based on a qualitative description of a system’s variables, have been applied for the analysis of biological systems with many unknown parameters. The purpose of this chapter is to give a detailed description of Boolean modeling, the simplest type of discrete dynamic modeling, and the ways in which it can be applied to analyze the dynamics of signaling networks. This is followed by practical examples of a Boolean dynamic framework applied to the modeling of the abscisic acid signal transduction network in plants as well as the T-cell survival signaling network in humans.

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Acknowledgment

This work was supported by NSF grant CCF-0643529.

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Correspondence to Réka Albert .

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Saadatpour, A., Albert, R. (2012). Discrete Dynamic Modeling of Signal Transduction Networks. In: Liu, X., Betterton, M. (eds) Computational Modeling of Signaling Networks. Methods in Molecular Biology, vol 880. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-833-7_12

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  • DOI: https://doi.org/10.1007/978-1-61779-833-7_12

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-61779-832-0

  • Online ISBN: 978-1-61779-833-7

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