MATH30920: Mathematical Biology

• Analysis in Many Variables.

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• Study of non-linear differential equations in biological models.

• Introduction to application of mathematics to biological systems and environments.
• Core applied modelling techniques such as stability analysis, weakly non-linear analysis, travelling wave solutions.
• ODE models in biology.
• Reaction diffusion equations.
• Pattern formation in nature: Turing analysis.
• Examples taken from the following: diffusion of insects and other species; the formation of spiral wave patterns in nature; hyperbolic models of insect dispersal and migration of a school of fish; glia aggregation in the human brain and possible connection with Alzheimer's disease; enzyme kinetics; the chemostat for bacteria production; branching growth of organisms; modelling the life cycle of the cellular slime mold Dictyostelium discoideum, and the phenomenon of chemotaxis; epidermal and dermal wound healing; epidemic models and the spatial spread of infectious diseases.

Subject-specific Knowledge:

• By the end of the module students will: be able to solve novel and/or complex problems in Mathematical Biology.
• have a systematic and coherent understanding of theoretical mathematics in the fields Mathematical Biology.
• have acquired coherent body of knowledge of these subjects demonstrated through one or more of the following topic areas:
• Models for diffusion of insect populations.
• Formation of spiral wave patterns.
• Mathematics of enzyme kinetics.
• Mathematics of the Chemostat.
• Chemostaxis and coalgulation of species.
• Pattern formation mechanisms.
• Spread of infectious diseases.

Subject-specific Skills:

• In addition students will have specialised mathematical skills in the following areas which can be used with minimal guidance: Modelling.

Key Skills:

• Lectures develop technical ideas and methodology and introduce motivating examples.
• Solution by students of problems in written assignments as part of formative assessment deepens and tests understanding of technical material and helps to develop modelling skills.
• Students will also be expected on occasion to find additional material from the Internet.
• Summative assessment by examination measures degree of technical mastery, grasp of basic ideas in modelling and skill carrying through necessary calculations.

Eight written or electronic assignments to be assessed and returned. Other assignments are set for self-study and complete solutions are made available to students.

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