Modelling diffusional neighbourhoods of cancer cell migration

Mathematical and computational models are emerging as effective complements and, in some cases, alternatives to in vitro and in vivo research. Particularly in the area of cancer research, such models allow for simulation testing of a diverse combination of parameters and variables, some of which would not be possible to examine empirically. One of the most-common criticisms of mathematical and computational models is the extent to which they can accurately mimic, and subsequently predict, actual biological events. Because many complex biological processes involve multiple independent but simultaneous events, portraying these events computationally is difficult, because the processes must be calculated sequentially by computer. An example of these processes is cancer cell diffusion, which can be represented by a variety of methods. Using a two-dimensional computer program developed to simulate cancer cell growth and diffusion, we compared the effects of using two of the most-prevalent diffusion patterns. We applied the Local Interaction Simulation Approach (LISA) and obtained different results, graphically and numerically, using von Neumann and Moore neighbourhoods. Our results are compared to determine which method is more-accurate in providing a realistic representation. Copyright © 2007 by the International Society for Computers and Their Applications (ISCA).