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The dynamic behaviour of epithelial cell sheets plays a central role during development, growth, disease and wound healing. These processes occur as a result of cell adhesion, migration, division, differentiation and death, and involve multiple processes acting at the cellular and molecular level. Computational models offer a useful means by which to investigate and test hypotheses about these processes, and have played a key role in the study of cell-cell interactions. However, the necessarily complex nature of such models means that it is difficult to make accurate comparison between different models, since it is often impossible to distinguish between differences in behaviour that are due to the underlying model assumptions, and those due to differences in the in silico implementation of the model. In this work, an approach is described for the implementation of vertex dynamics models, a discrete approach that represents each cell by a polygon (or polyhedron) whose vertices may move in response to forces. The implementation is undertaken in a consistent manner within a single open source computational framework, Chaste, which comprises fully tested, industrial-grade software that has been developed using an agile approach. This framework allows one to easily change assumptions regarding force generation and cell rearrangement processes within these models. The versatility and generality of this framework is illustrated using a number of biological examples. In each case we provide full details of all technical aspects of our model implementations, and in some cases provide extensions to make the models more generally applicable.

Original publication

DOI

10.1016/j.pbiomolbio.2013.09.003

Type

Journal article

Journal

Prog Biophys Mol Biol

Publication Date

11/2013

Volume

113

Pages

299 - 326

Keywords

Cell-based models, Chaste, Epithelial monolayers, Model comparison, Off-lattice, Algorithms, Animals, Cell Aggregation, Cell Communication, Computer Simulation, Epithelial Cells, Humans, Mechanotransduction, Cellular, Models, Biological, Stress, Mechanical