Lattice-gas Cellular Automaton Models for the Analysis of Pattern Formation in Interacting Cell Populations

Abstract

Lattice-gas cellular automaton (LGCA) models are introduced as models for the analysis of pattern formation in interacting cell populations. LGCA models are cell-based, computationally efficient, and allow to integrate statistical and biophysical models for different levels of biological knowledge. Moreover, LGCA models permit multiscale analysis of collective phenomena emerging at multiple temporal and spatial scales.