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Received February 4, 2015
Accepted April 7, 2015
- This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Modeling and simulation of biopolymer networks: Classification of the cytoskeleton models according to multiple scales
The Department of Chemical and Biochemical Engineering, Missouri University of Science and Technology, Rolla, MO 65409, USA
parkjoon@mst.edu
Korean Journal of Chemical Engineering, July 2015, 32(7), 1207-1217(11), 10.1007/s11814-015-0071-5
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Abstract
We reviewed numerical/analytical models for describing rheological properties and mechanical behaviors of biopolymer networks with a focus on the cytoskeleton, a major component of a living cell. The cytoskeleton models are classified into three categories: the cell-scale continuum-based model, the structure-based model, and the polymerbased model, according to the length scales of the phenomena of interest. The criteria for classification of the models are modified and extended from those used by Mofrad [M. R. K. Mofrad, Annual Rev. Fluid Mech. 41, 433 (2009)]. The main principles and characteristics of each model are summarized and discussed by comparison with each other. Since the stress-deformation relation of cytoskeleton is dependent on the length scale of stress elements, our model classification helps systematic understanding of biopolymer network modeling.
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Broederz CP, Storm C, MacKintosh FC, Phys. Rev. Lett., 101, 118103 (2008)
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Wilhelm J, Frey E, Phys. Rev. Lett., 91, 108103 (2003)
Onck PR, Koeman T, van Dillen T, van der Giessen E, Phys. Rev. Lett., 95, 178102 (2005)
Conti E, MacKintosh FC, Phys. Rev. Lett., 102, 088102 (2009)
Abhilash AS, Purohit PK, Joshi SP, Soft Matter, 8, 7004 (2012)
Alonso R, Young J, Cheng Y, Cell. Mol. Bioeng.,, 7, 58 (2014)
Cucker F, Smale S, IEEE Trans. Autom. Control, 52(5), 852 (2007)
Fallqvist B, Kulachenko A, Kroon M, J. Theor. Biol., 350, 57 (2014)
Huisman EM, van Dillen T, Onck PR, van der Giessen E, Phys. Rev. Lett., 99, 208103 (2007)
Huisman EM, Storm C, Barkema GT, Phys. Rev. E, 78, 051801 (2008)
Huisman EM, Storm C, Barkema GT, Phys. Rev. E, 82, 061902 (2010)
Kim T, Hwang W, Lee H, Kamm RD, PLoS Comput. Biol., 5, e10004 (2009)
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Kim T, Gardel ML, Munro E, Biophys. J., 106, 526 (2014)
Mak M, Zaman M, Kamm R, Med. Phys., 41, 164 (2014)
Cyron C, Baush AR, Muller KW, Wall WA, J. Comput. Phys., 244, 236 (2013)
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Fan J, Saunders MG, Voth GA, Biophys. J., 103, 1334 (2012)
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