Stability analysis in spatial modeling of cell signaling.

Michael C Getz, Jasmine A Nirody, Padmini Rangamani

Journal: Wiley interdisciplinary reviews. Systems biology and medicine 2018;10(1):

PMID: 28787545

Abstract

Advances in high-resolution microscopy and other techniques have emphasized the spatio-temporal nature of information transfer through signal transduction pathways. The compartmentalization of signaling molecules and the existence of microdomains are now widely acknowledged as key features in biochemical signaling. To complement experimental observations of spatio-temporal dynamics, mathematical modeling has emerged as a powerful tool. Using modeling, one can not only recapitulate experimentally observed dynamics of signaling molecules, but also gain an understanding of the underlying mechanisms in order to generate experimentally testable predictions. Reaction-diffusion systems are commonly used to this end; however, the analysis of coupled nonlinear systems of partial differential equations, generated by considering large reaction networks is often challenging. Here, we aim to provide an introductory tutorial for the application of reaction-diffusion models to the spatio-temporal dynamics of signaling pathways. In particular, we outline the steps for stability analysis of such models, with a focus on biochemical signal transduction. WIREs Syst Biol Med 2018, 10:e1395. doi: 10.1002/wsbm.1395 This article is categorized under: Biological Mechanisms > Cell Signaling Analytical and Computational Methods > Dynamical Methods Models of Systems Properties and Processes > Mechanistic Models.

© 2017 Wiley Periodicals, Inc.

Address: Chemical Engineering Graduate Program, University of California San Diego, La Jolla, CA, USA.; Biophysics Graduate Program, University of California, Berkeley, CA, USA.; Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA, USA.

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