细胞信号空间建模中的稳定性分析。

IF 7.9 Q1 Medicine
Michael C Getz, Jasmine A Nirody, Padmini Rangamani
{"title":"细胞信号空间建模中的稳定性分析。","authors":"Michael C Getz,&nbsp;Jasmine A Nirody,&nbsp;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":"{\"title\":\"Stability analysis in spatial modeling of cell signaling.\",\"authors\":\"Michael C Getz,&nbsp;Jasmine A Nirody,&nbsp;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}","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

摘要

高分辨率显微镜和其他技术的进步强调了通过信号转导途径传递信息的时空性质。信号分子的区隔化和微结构域的存在被广泛认为是生物化学信号传导的关键特征。为了补充时空动力学的实验观察,数学建模已经成为一种强大的工具。利用建模,人们不仅可以概括实验观察到的信号分子动力学,而且还可以了解潜在的机制,以便产生实验可测试的预测。反应-扩散系统通常用于此目的;然而,考虑大型反应网络产生的耦合非线性偏微分方程组的分析往往具有挑战性。在这里,我们的目的是为反应扩散模型在信号通路时空动力学中的应用提供一个入门教程。特别是,我们概述了这些模型的稳定性分析的步骤,重点是生化信号转导。中国生物医学工程学报,2018,32(1):444 - 444。doi: 10.1002 / wsbm.1395本文分类为:生物学机制>细胞信号传导分析与计算方法>系统特性与过程的动力学方法模型>机制模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stability analysis in spatial modeling of cell signaling.

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
18.40
自引率
0.00%
发文量
0
审稿时长
>12 weeks
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
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信