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MA390 Topics in Mathematical biology

Lecturer: Professor Nigel Burroughs

Term(s): Term 1

Status for Mathematics students: List A

Commitment: 10 on-line live lectures, additional videos, 10 on-line live examples classes

Assessment: 3 hour examination (100%)

Prerequisites: There are no prerequisites but the following is advised: Probability A & B (ST111), Introduction to partial differential equations (MA250), Theory of ODEs (MA254), Introduction to Systems Biology (MA256).

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, using examples from primarily medical systems. Topics include:

1. Virus dynamics and mutation, including HIV/AIDS and basic immunology (ODEs, phase plane analysis - linearisation and stability analysis, ).

2. Small gene circuits (bifurcations, stochastic modeling using master equations and solving them with method of characteristics (PDEs reduced to ODEs)).

3. Cancer modelling (branching processes, solutions with method of characteristics).

4. Cancer treatment (possibly including game theory and control theory).

To introduce ideas and techniques of mathematical modelling (deterministic and stochastic) in biology.

To gain an insight into modelling techniques and principles in gene regulation, virus growth and cancer; to consolidate basic mathematical techniques used in these approaches, such as ODEs, PDEs, probability theory, branching processes and Markov Chains.

There is no dedicated text. A classic text (only deterministic modelling, I is predominantly ODEs and of more relevance to course, II is PDEs) is Mathematical Biology I & II. James Murrey. Springer. Useful texts for specific topics are: Branching process models of cancer. Richard Durrett. 2015. Springer. [], Virus dynamics : mathematical principles of immunology and virology. Martin Nowak and Robert May. 2000. OUP, 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.

Additional Resources

Archived Pages: Pre-2011 2011 2012 2013 2014 2015 2016 2018

Year 1 regs and modules
G100 G103 GL11 G1NC

Year 2 regs and modules
G100 G103 GL11 G1NC

Year 3 regs and modules
G100 G103

Year 4 regs and modules

Archived Material
Past Exams
Core module averages