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A Comparison of Computational Models for Eukaryotic Cell Shape and Motility

Eukaryotic cell motility involves complex interactions of signalling molecules, cytoskeleton, cell membrane, and mechanics interacting in space and time. Collectively, these components are used by the cell to interpret and respond to external stimuli, leading to polarization, protrusion, adhesion fo...

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Detalles Bibliográficos
Autores principales: Holmes, William R., Edelstein-Keshet, Leah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531321/
https://www.ncbi.nlm.nih.gov/pubmed/23300403
http://dx.doi.org/10.1371/journal.pcbi.1002793
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author Holmes, William R.
Edelstein-Keshet, Leah
author_facet Holmes, William R.
Edelstein-Keshet, Leah
author_sort Holmes, William R.
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description Eukaryotic cell motility involves complex interactions of signalling molecules, cytoskeleton, cell membrane, and mechanics interacting in space and time. Collectively, these components are used by the cell to interpret and respond to external stimuli, leading to polarization, protrusion, adhesion formation, and myosin-facilitated retraction. When these processes are choreographed correctly, shape change and motility results. A wealth of experimental data have identified numerous molecular constituents involved in these processes, but the complexity of their interactions and spatial organization make this a challenging problem to understand. This has motivated theoretical and computational approaches with simplified caricatures of cell structure and behaviour, each aiming to gain better understanding of certain kinds of cells and/or repertoire of behaviour. Reaction–diffusion (RD) equations as well as equations of viscoelastic flows have been used to describe the motility machinery. In this review, we describe some of the recent computational models for cell motility, concentrating on simulations of cell shape changes (mainly in two but also three dimensions). The problem is challenging not only due to the difficulty of abstracting and simplifying biological complexity but also because computing RD or fluid flow equations in deforming regions, known as a “free-boundary” problem, is an extremely challenging problem in applied mathematics. Here we describe the distinct approaches, comparing their strengths and weaknesses, and the kinds of biological questions that they have been able to address.
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spelling pubmed-35313212013-01-08 A Comparison of Computational Models for Eukaryotic Cell Shape and Motility Holmes, William R. Edelstein-Keshet, Leah PLoS Comput Biol Review Eukaryotic cell motility involves complex interactions of signalling molecules, cytoskeleton, cell membrane, and mechanics interacting in space and time. Collectively, these components are used by the cell to interpret and respond to external stimuli, leading to polarization, protrusion, adhesion formation, and myosin-facilitated retraction. When these processes are choreographed correctly, shape change and motility results. A wealth of experimental data have identified numerous molecular constituents involved in these processes, but the complexity of their interactions and spatial organization make this a challenging problem to understand. This has motivated theoretical and computational approaches with simplified caricatures of cell structure and behaviour, each aiming to gain better understanding of certain kinds of cells and/or repertoire of behaviour. Reaction–diffusion (RD) equations as well as equations of viscoelastic flows have been used to describe the motility machinery. In this review, we describe some of the recent computational models for cell motility, concentrating on simulations of cell shape changes (mainly in two but also three dimensions). The problem is challenging not only due to the difficulty of abstracting and simplifying biological complexity but also because computing RD or fluid flow equations in deforming regions, known as a “free-boundary” problem, is an extremely challenging problem in applied mathematics. Here we describe the distinct approaches, comparing their strengths and weaknesses, and the kinds of biological questions that they have been able to address. Public Library of Science 2012-12-27 /pmc/articles/PMC3531321/ /pubmed/23300403 http://dx.doi.org/10.1371/journal.pcbi.1002793 Text en © 2012 Holmes, Edelstein-Keshet http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Review
Holmes, William R.
Edelstein-Keshet, Leah
A Comparison of Computational Models for Eukaryotic Cell Shape and Motility
title A Comparison of Computational Models for Eukaryotic Cell Shape and Motility
title_full A Comparison of Computational Models for Eukaryotic Cell Shape and Motility
title_fullStr A Comparison of Computational Models for Eukaryotic Cell Shape and Motility
title_full_unstemmed A Comparison of Computational Models for Eukaryotic Cell Shape and Motility
title_short A Comparison of Computational Models for Eukaryotic Cell Shape and Motility
title_sort comparison of computational models for eukaryotic cell shape and motility
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531321/
https://www.ncbi.nlm.nih.gov/pubmed/23300403
http://dx.doi.org/10.1371/journal.pcbi.1002793
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