Visualization of spatial patterns of cells using a 3-D simulation model for multicellular tissue growth

Abstract

In this paper, we apply a previously developed computational model for the growth of multicellular tissues using a discrete approach based on cellular automata to simulate the tissue growth rates and visualize the spatial patterns of three populations of proliferating and migrating cells. We use the obtained 3-D time-varying data to visualize the generated spatial patterns of the simulated grown tissue. We then briefly compare the tissue growth rates for two seeding modes, mixed and segmented, using a uniform cell distribution. Slow, moderate, and fast moving cells are utilized with each cell population having its own division characteristics. Our visualization results show that the placement of fast cells may impact not only the tissue growth rate but also the spatial characteristics of the grown tissue pattern. The developed computational model contains a number of system parameters that allow us to explore their effects on many other aspects of cell behavior as well as to study the temporal dynamics of such a complex system.