Introductory description

Mathematical modelling of biological systems and processes is a growing field that uses multiple mathematical modelling and analysis techniques. This course will cover a range of these techniques.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

This is a specialist course so the syllabus changes depending on the interests and expertise of lecturer.

Learning outcomes

By the end of the module, students should be able to:

• To gain an insight into modelling techniques and dynamic principles in biology through building and analysing a range of mathematical models;
• to consolidate basic mathematical techniques used in these approaches, such as ODEs, PDEs, probability theory, branching processes and Markov Chains.

Indicative reading list

A classic text (only deterministic modelling, I is predominantly ODEs, II is PDEs) is Mathematical Biology I & II. James Murrey. Springer. See also Methods and Models in Mathematical Biology, Müller, Johannes, Kuttler, Christina, Lecture Notes in Mathematical Modelling in the Life Sciences, Springer. ISBN 978-3-642-27251-6, containing good examples. Specialist texts will also be indicated depending on module focus.

Subject specific skills

Students will primarily acquire skills on formulating and solving complex problems, turning a biology question into a mathematical question through construction of an appropriate mathematical model, either deterministic or stochastic. An ability to use a range of techniques will also be acquired to solve these problems, e.g. stability theory, bifurcation analysis, master equation approaches, including solving with the method of characteristics. Such skills are widely transferable to other problems in biology, and to other arenas, including engineering, financial modelling, population modelling etc.

Transferable skills

Students will acquire key reasoning and problem solving skills which will empower them to address new problems with confidence. Such skills are a major selling point of the Warwick mathematics degree, but with the biology underpinning that this course gives them, they will also have a background that will enable them to approach biotechnology and data science companies in addition to financial, engineering and management vocations.