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Methods for the Analysis of Intracellular Signal Transduction Systems
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Author(s): Takashi Nakakuki (Kogakuin University, Japan)and Mariko Okada-Hatakeyama (Laboratory for Cellular Systems Modeling, RIKEN Research Center for Allergy and Immunology, Japan)
Copyright: 2013
Pages: 7
Source title:
Technological Advancements in Biomedicine for Healthcare Applications
Source Author(s)/Editor(s): Jinglong Wu (Okayama University, Japan)
DOI: 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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