Abstract

Although tissues are typically studied in isolation, such situations rarely occur in biology, as cells, tissues, and organs coexist and interact across various scales, shaping both form and function. In this study, we adopt a quantitative approach that combines recent experimental data, mathematical modelling, and Bayesian parameter inference to describe the dynamics of freely expanding and colliding epithelial monolayers. Two simple and extensively studied continuum models are employed, where cells move either randomly or in response to population pressure gradients. Following appropriate calibration, both models successfully replicate the primary features of individual tissue expansions. However, our findings demonstrate that when tissues are not isolated and interactions become relevant, assuming random cell motion can lead to unrealistic behaviour. In such cases, a model that considers population pressure from different cell populations proves more suitable and facilitates comparison with experimental measurements. Additionally, we investigate the dynamics of cell division within epithelial monolayers and demonstrate how a combination of minimal modelling and Bayesian inference can capture mechanical checkpoints in cell-cycle progression.