This course focuses on using computational modelling to explore biological systems and test specific hypotheses. Students learn to construct exact models and analyse their behaviour to gain insight into the original biological system. The course draws on a broad range of biological questions across evolutionary, developmental, ecological, and molecular biology.
Topics include evolutionary dynamics such as genome evolution, robustness, and host-pathogen co-evolution; developmental dynamics such as pattern formation, cell differentiation, morphogenesis, and the evolution of development (EVO-DEVO); network dynamics including gene regulation, metabolic networks, and RNA interference; and behaviour, including self-structuring through local interactions and the relationship between learning and evolution. Both plant and animal models are used.
A central theme throughout is spatial pattern formation and emergent properties, which are introduced as a general theoretical module. Model formalisms taught include non-linear differential and difference equations (ODE, maps), partial differential equations (PDE), cellular automata, event-based models, individually oriented models, evolutionary computation, and hybrid models. Analysis methods include bifurcation analysis, sensitivity analysis, and pattern analysis techniques.