Kathleen T DiNapoli, Douglas N Robinson, Pablo A Iglesias
{"title":"细胞机械生物学中移动边界问题的计算分析工具。","authors":"Kathleen T DiNapoli, Douglas N Robinson, Pablo A Iglesias","doi":"10.1002/wsbm.1514","DOIUrl":null,"url":null,"abstract":"<p><p>A cell's ability to change shape is one of the most fundamental biological processes and is essential for maintaining healthy organisms. When the ability to control shape goes awry, it often results in a diseased system. As such, it is important to understand the mechanisms that allow a cell to sense and respond to its environment so as to maintain cellular shape homeostasis. Because of the inherent complexity of the system, computational models that are based on sound theoretical understanding of the biochemistry and biomechanics and that use experimentally measured parameters are an essential tool. These models involve an inherent feedback, whereby shape is determined by the action of regulatory signals whose spatial distribution depends on the shape. To carry out computational simulations of these moving boundary problems requires special computational techniques. A variety of alternative approaches, depending on the type and scale of question being asked, have been used to simulate various biological processes, including cell motility, division, mechanosensation, and cell engulfment. In general, these models consider the forces that act on the system (both internally generated, or externally imposed) and the mechanical properties of the cell that resist these forces. Moving forward, making these techniques more accessible to the non-expert will help improve interdisciplinary research thereby providing new insight into important biological processes that affect human health. This article is categorized under: Cancer > Cancer>Computational Models Cancer > Cancer>Molecular and Cellular Physiology.</p>","PeriodicalId":49254,"journal":{"name":"Wiley Interdisciplinary Reviews-Systems Biology and Medicine","volume":" ","pages":"e1514"},"PeriodicalIF":7.9000,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tools for computational analysis of moving boundary problems in cellular mechanobiology.\",\"authors\":\"Kathleen T DiNapoli, Douglas N Robinson, Pablo A Iglesias\",\"doi\":\"10.1002/wsbm.1514\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A cell's ability to change shape is one of the most fundamental biological processes and is essential for maintaining healthy organisms. When the ability to control shape goes awry, it often results in a diseased system. As such, it is important to understand the mechanisms that allow a cell to sense and respond to its environment so as to maintain cellular shape homeostasis. Because of the inherent complexity of the system, computational models that are based on sound theoretical understanding of the biochemistry and biomechanics and that use experimentally measured parameters are an essential tool. These models involve an inherent feedback, whereby shape is determined by the action of regulatory signals whose spatial distribution depends on the shape. To carry out computational simulations of these moving boundary problems requires special computational techniques. A variety of alternative approaches, depending on the type and scale of question being asked, have been used to simulate various biological processes, including cell motility, division, mechanosensation, and cell engulfment. In general, these models consider the forces that act on the system (both internally generated, or externally imposed) and the mechanical properties of the cell that resist these forces. Moving forward, making these techniques more accessible to the non-expert will help improve interdisciplinary research thereby providing new insight into important biological processes that affect human health. 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Tools for computational analysis of moving boundary problems in cellular mechanobiology.
A cell's ability to change shape is one of the most fundamental biological processes and is essential for maintaining healthy organisms. When the ability to control shape goes awry, it often results in a diseased system. As such, it is important to understand the mechanisms that allow a cell to sense and respond to its environment so as to maintain cellular shape homeostasis. Because of the inherent complexity of the system, computational models that are based on sound theoretical understanding of the biochemistry and biomechanics and that use experimentally measured parameters are an essential tool. These models involve an inherent feedback, whereby shape is determined by the action of regulatory signals whose spatial distribution depends on the shape. To carry out computational simulations of these moving boundary problems requires special computational techniques. A variety of alternative approaches, depending on the type and scale of question being asked, have been used to simulate various biological processes, including cell motility, division, mechanosensation, and cell engulfment. In general, these models consider the forces that act on the system (both internally generated, or externally imposed) and the mechanical properties of the cell that resist these forces. Moving forward, making these techniques more accessible to the non-expert will help improve interdisciplinary research thereby providing new insight into important biological processes that affect human health. This article is categorized under: Cancer > Cancer>Computational Models Cancer > Cancer>Molecular and Cellular Physiology.
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