Agent-Based Modelling of Pattern Formation in Pluripotent Stem Cells: Initial Experiments and Results

Abstract

The underlying mechanisms of pluripotent stem cell behaviours are complicated and not fully understood. However, this need not be a barrier to prediction of pattern formation in colonies of cells if a high-level model of their social interaction decisions gives sufficient predictive power. This is analogous to prediction of behaviours in crowds of people, where we cannot model individuals in detail, but we can predict aggregate crowd behaviour from comparatively simple agent-based models of their social conventions. In this research, agent-based modelling was applied to study pattern formation in pluripotent stem cells. The aim of this study is to develop a modelling approach towards investigating the social and dynamic behaviours of pluripotent stem cells from their high-level features. We establish six agent-based models with different behavioural protocols and present the results of a set of experiments. Simulated experiments provide evidence of potential behavioural rules of stem cells. This study provides an intuitive framework for the investigation of social pattern behaviours in pluripotent stem cells.