Stochastic individual-based mathematical models are attractive for modelling biological
phenomena because they naturally capture the stochasticity and variability that is often …

Collective cell spreading takes place in spatially continuous environments, yet it is often
modelled using discrete lattice-based approaches. Here, we use data from a series of cell …

Estimating model parameters is a crucial step in mathematical modelling and typically
involves minimizing the disagreement between model predictions and experimental data …

Many commonly used mathematical models in the field of mathematical biology involve
challenges of parameter non-identifiability. Practical non-identifiability, where the quality and …

Throughout the life sciences, we routinely seek to interpret measurements and observations
using parametrized mechanistic mathematical models. A fundamental and often overlooked …

In various fields, statistical models of interest are analytically intractable and inference is
usually performed using a simulation-based method. However elegant these methods are …

This chapter provides a brief introduction to the theory and practice of spatial stochastic
simulations. It begins with an overview of different methods available for biochemical …

Understanding how cells proliferate, migrate and die in various environments is essential in
determining how organisms develop and repair themselves. Continuum mathematical …

Background Utilizing kinetic models of biological systems commonly require computational
approaches to estimate parameters, posing a variety of challenges due to their highly non …

When modeling complex biological systems, exploring parameter space is critical, because
parameter values are typically poorly known a priori. This exploration can be challenging …