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Intelligent Engineering Systems through Artificial Neural Networks Volume 18

Cihan H. Dagli
Cihan H. Dagli
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We extend a previously developed computational model for the simulation of multicellular tissue growth using a discrete approach based on cellular automata. Our objective is to investigate the tissue growth rates and population dynamics of different populations of migrating and proliferating mammalian cells. The model extension is applied in the context of a wound-healing environment where it is assumed that nutrient and growth factor concentrations remain constant in space and time. We report simulation results describing cell collision and aggregation for two cell populations each having its own division and motion characteristics based on experimental data. Both heterotypic and homotypic cell-cell interactions play important roles in wound healing. The temporal evolution of the frequency of cell collision and aggregation and their relations to other variables that quantify the dynamics of cell populations can be predicted by this model for different cell heterogeneity ratios and cell population speeds.

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