Stochastic mathematical models of cell proliferation assays

Cell proliferation assays are routinely used to study collective cell behaviour, and can be interpreted with mathematical models. In this thesis, we apply a computational Bayesian technique to calibrate stochastic discrete mathematical models of cell migration and cell proliferation in the context of a cell proliferation assay. Initially, we use a lattice-based model to explore the optimal duration of a cell proliferation assay. Next, we estimate the parameters in a lattice-free model using three independent experimental data sets. Our model is able to both describe and predict the evolution of the population and spatial structure in a cell proliferation assay