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Methods for the Analysis of Intracellular Signal Transduction Systems

Methods for the Analysis of Intracellular Signal Transduction Systems

Takashi Nakakuki, Mariko Okada-Hatakeyama
Copyright: © 2013 |Pages: 7
ISBN13: 9781466621961|ISBN10: 1466621966|EISBN13: 9781466621978
DOI: 10.4018/978-1-4666-2196-1.ch034
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MLA

Nakakuki, Takashi, and Mariko Okada-Hatakeyama. "Methods for the Analysis of Intracellular Signal Transduction Systems." Technological Advancements in Biomedicine for Healthcare Applications, edited by Jinglong Wu, IGI Global, 2013, pp. 347-353. https://doi.org/10.4018/978-1-4666-2196-1.ch034

APA

Nakakuki, T. & Okada-Hatakeyama, M. (2013). Methods for the Analysis of Intracellular Signal Transduction Systems. In J. Wu (Ed.), Technological Advancements in Biomedicine for Healthcare Applications (pp. 347-353). IGI Global. https://doi.org/10.4018/978-1-4666-2196-1.ch034

Chicago

Nakakuki, Takashi, and Mariko Okada-Hatakeyama. "Methods for the Analysis of Intracellular Signal Transduction Systems." In Technological Advancements in Biomedicine for Healthcare Applications, edited by Jinglong Wu, 347-353. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2196-1.ch034

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Abstract

This chapter introduces some practical methods for the analysis of intracellular signal transduction systems. If a biological system is described by a linear ordinary differential equation, various analytical tools are available to elucidate a control mechanism for the system in question. However, few systematic methods are available for nonlinear systems in which it is more capable of wide application for practical problems to describe a biological phenomenon by nonlinear modeling. Here, three effective methods for nonlinear systems analysis are demonstrated with a practical example involving a large-scale nonlinear model that includes signal transduction pathways, nucleocytoplasmic shuttling, and both transcriptional and translational control. Two methods of metabolic control analyses (MCA) are explained; the classical type can be applied to static conditions, and the alternative method can be used to analyze dynamic properties, such as peak, duration, and integral of time-course responses. Unlike MCA that cannot be experimentally verified because of technical limitations, the authors next explain an analytical method with a large perturbation. Finally, they introduce a parameter sensitivity analysis and explain that, by changing input characteristics, such as amplitude and frequency, some analysis of robustness can be achieved.

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