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Mathematical models provide a way to capture the essential features of complex systems, which often help scientists to gain insight and understanding, and crucially allow the behaviour of the system to be accurately predicted. Such models are pervasive in physics and chemistry but have been slower to develop in biology and medicine due to the perceived complexity and heterogeneity of biological systems. However, mathematical models are increasingly being applied to make sense of the huge volumes of biological data produced by modern technologies.

This module exposes the student to the range of applications of mathematical models in biomedicine, through coursework and a series of seminars and tutorials by experts from across ÂÒÂ×Ðã. The course will cover mathematical models operating at widely different time and length scales, ranging from models of molecular structure, enzyme and receptor kinetics, gene regulation, cellular and organ imaging, neuronal processing and brain function, to epidemiology and evolution. By way of these examples, the course will introduce key modelling approaches including deterministic, stochastic, mechanistic and statistical models.

Methods of Assessment

• 1-page Scientific Poster (40%)
• Mini Project (1500 words) (60%)

Learning outcomes

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

• Describe the main approaches to representing biological and medical processes by mathematical models.
• Read, understand and critically evaluate primary literature in this field.
• Conceptualise and develop mathematical models of biological processes, discuss their value and identify their limitations.
• Explain the importance and impact of mathematical modelling in diverse areas of medicine and biomedical research.