Biomathematics Course

What will I learn?
You will develop a strong foundation in mathematical modelling, covering discrete and continuous dynamical systems, probability, and statistical inference. You will construct and analyse compartmental epidemiological models, derive key quantities like the basic reproduction number, and evaluate intervention strategies. The course covers enzyme kinetics, gene regulatory networks, and metabolic flux analysis at the molecular level. You will also explore population ecology, evolutionary game theory, and spatial models. Advanced topics include partial differential equations, agent-based models, sensitivity analysis, and biological network theory. Throughout, you will apply computational tools to simulate, fit, and visualise models using real biological data.
Elevify advantages
Develop skills
- Differential Equation Modelling: Build and analyse ODE systems for biological populations and processes.
- Epidemiological Analysis: Derive reproduction numbers and evaluate disease intervention strategies quantitatively.
- Biostatistical Inference: Apply regression, hypothesis testing, and Bayesian methods to biological datasets.
- Computational Simulation: Implement numerical solvers and visualise dynamic biological model outputs.
Suggested summary
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