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A comparison of computational models for eukaryotic cell shape and motility
William R Holmes1, Leah Edelstein-Keshet
1Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada. wrholmes@uci.edu
Plos Computational Biology
|January 10, 2013
Summary
Computational models simplify complex eukaryotic cell motility, aiding understanding of shape changes and molecular interactions. This review explores various simulation approaches for cell movement dynamics.
Area of Science:
- Biophysics
- Computational Biology
- Cell Biology
Background:
- Eukaryotic cell motility is a complex process involving signaling molecules, cytoskeleton, and cell membrane dynamics.
- Understanding the intricate interactions and spatial organization of these components remains a significant challenge.
Purpose of the Study:
- To review recent computational models of eukaryotic cell motility.
- To focus on simulations of cell shape changes in two and three dimensions.
- To compare different modeling approaches and their biological applications.
Main Methods:
- Utilizing reaction-diffusion (RD) equations and viscoelastic flow equations to model motility machinery.
- Developing computational simulations for cell shape changes, addressing free-boundary problems.
- Analyzing and comparing distinct modeling strategies for their strengths and weaknesses.
Main Results:
- Identified numerous molecular constituents involved in cell motility through experimental data.
- Computational models offer simplified yet insightful representations of cell behavior.
- Simulation of RD and fluid flow in deforming regions presents significant mathematical challenges.
Conclusions:
- Computational approaches are crucial for deciphering the complexity of cell motility.
- Different models provide unique insights into specific aspects of cell shape change and movement.
- Further development in computational mathematics is needed to overcome simulation challenges.
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