Combining experiments with multi-cell agent-based modeling to study biological tissue patterning

Agent-based modeling (ABM), also termed ‘Individual-basedmodeling (IBM)’, is a computational approach that simulatesthe interactions of autonomous entities (agents, or individualcells) with each other and their local environment to predicthigher level emergent patterns. A literature-derived rule setgoverns the actions of each individual agent. While this techniquehas been widely used in the ecological and social sciences,it has only recently been applied in biomedical research. Thepurpose of this review is to provide an introduction to ABMas it has been used to study complex multi-cell biological phenomena,underscore the importance of coupling models with experimentalwork, and outline future challenges for the ABM field and itsapplication to biomedical research. We highlight a number ofpublished examples of ABM, focusing on work that has combinedexperimental with ABM analyses and how this pairing producesnew understanding. We conclude with suggestions for moving forwardwith this parallel approach.