Michael C Getz, Jasmine A Nirody, Padmini Rangamani
{"title":"Stability analysis in spatial modeling of cell signaling.","authors":"Michael C Getz, Jasmine A Nirody, Padmini Rangamani","doi":"10.1002/wsbm.1395","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":49254,"journal":{"name":"Wiley Interdisciplinary Reviews-Systems Biology and Medicine","volume":"10 1","pages":""},"PeriodicalIF":7.9000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/wsbm.1395","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wiley Interdisciplinary Reviews-Systems Biology and Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/wsbm.1395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2017/8/8 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 7
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.
期刊介绍:
Journal Name:Wiley Interdisciplinary Reviews-Systems Biology and Medicine
Focus:
Strong interdisciplinary focus
Serves as an encyclopedic reference for systems biology research
Conceptual Framework:
Systems biology asserts the study of organisms as hierarchical systems or networks
Individual biological components interact in complex ways within these systems
Article Coverage:
Discusses biology, methods, and models
Spans systems from a few molecules to whole species
Topical Coverage:
Developmental Biology
Physiology
Biological Mechanisms
Models of Systems, Properties, and Processes
Laboratory Methods and Technologies
Translational, Genomic, and Systems Medicine