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Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17
C. H. Dagli
C. H. Dagli
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We developed a computational model to simulate the growth of multicellular tissues using a discrete approach based on cellular automata. The model allows us to study the tissue growth rates and population dynamics of different populations of migrating and proliferating mammalian cells. Cell migration is modeled using a discrete-time Markov chain approach. We report simulation results describing cell collision and aggregation for two cell populations each having its own division and motion characteristics. Heterotypic and homotypic cell-cell interactions play important roles in cell and tissue functions. 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 seeding topologies and cell heterogeneity ratios.

Related Work
Modeling of Cell Collision and Aggregation
Simulation Results and Discussion
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