Mathematical modelling and analysis
Mathematical models can be used to describe core biological mechanisms in order to help develop insight into the way that systems behave and predict behaviour. Ultimately, this may inform policy decisions, for example, when and who to vaccinate for infectious diseases, drug design or optimal light patterns for healthy circadian rhythmicity.
The kind of models that occur depend strongly on the nature of the research question and the particular system. Members of our centre have expertise in developing models in a variety of forms including ordinary differential equations, partial differential equations and agent-based models. Depending on the application, models may be deterministic or stochastic.
Models are analysed using a broad range of techniques including geometric singular perturbation methods, multiple spatial and/or time scale analysis, asymptotics and nonlinear dynamical systems techniques including bifurcation theory.
Members of our centre are also actively involved in developing novel numerical methods, for example for model data fusion (data assimilation).
- Elasticity theory and mechanics of cell growth
- Evolutionary biology
- Open quantum systems
- Population models
- Sleep and circadian rhythms
- Skin adsorption of chemicals
- Stem cell differentiation modelling
- Systems pharmacology (PKPD).
Meet the team
Dr Matteo Barberis
Reader in Systems Biology, FHMS Coordinator of Centre for Mathematical and Computational Biology (CMCB), School International Lead
Professor David Lloyd
Professor in Mathematics, Deputy Head of School of Mathematics & Physics, Director of Learning and Teaching School of Mathematics & Physics