A 3-D Computational Model for Multicellular Tissue Growth
We report the development of a computational model for the growth of multicellular tissues using a discrete approach based on cellular automata to study the tissue growth rates and population dynamics of two different populations of migrating and proliferating mammalian cells. Cell migration is modeled using a discrete-time Markov chain approach and each population of cells has its own division and motion characteristics that are based on experimental data. A large number of parameters allow for a detailed study of the population dynamics. This permits the exploration of the relative influence of various system parameters on the proliferation rate and some other aspects of cell behavior such as average speed of locomotion.
KeywordsCellular Automaton Migration Speed Cellular Space Uniform Topology Segmented Distribution
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