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Simulation of Multiple Cell Population Dynamics Using a 3-D Cellular Automata Model for Tissue Growth

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  • Belgacem Ben Youssef

    (King Saud University, Saudi Arabia and Simon Fraser University, Canada)

  • Lenny Tang

    (Simon Fraser University, Canada)

Abstract

In this paper, the authors describe a computational model for the growth of multicellular tissues using a discrete approach based on cellular automata to simulate the tissue growth rates and population dynamics of multiple populations of proliferating and migrating cells. Each population of cells has its own division, motion, collision, and aggregation characteristics. These random dynamic processes can be modeled by appropriately choosing the governing rules of the state transitions of each computational site. This extended model contains a number of system parameters that allow their effects on the volume coverage, the overall tissue growth rate, and some other aspects of cell behavior like the average speed of locomotion to be explored. These discrete systems provide an alternative approach to continuous models for the purpose of describing the temporal dynamics of complex systems.

Suggested Citation

  • Belgacem Ben Youssef & Lenny Tang, 2010. "Simulation of Multiple Cell Population Dynamics Using a 3-D Cellular Automata Model for Tissue Growth," International Journal of Natural Computing Research (IJNCR), IGI Global, vol. 1(3), pages 1-18, July.
    • Handle: RePEc:igg:jncr00:v:1:y:2010:i:3:p:1-18
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    Cited by:

    1. Ortigoza, Gerardo M., 2015. "Unstructured triangular cellular automata for modeling geographic spread," Applied Mathematics and Computation, Elsevier, vol. 258(C), pages 520-536.

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