Subject Summary

This course provides an introduction to mathematical biology. It involves mathematical, statistical, and computing methods, and is designed to approach these three elements from an integrated biological point of view. The underlying theme is the modelling and analysis of populations of molecules, cells, and organisms. The principal biological topics are: growth and decline of populations; probability and statistical methods, linear algebra and ecological and epidemiological modelling. A range of mathematical and statistical techniques, including ordinary differential equations, local stability analysis, coupled differential equations, hypothesis testing, linear regression, and probability distributions are introduced in the context of biological systems. The lectures are supplemented by practical classes using modern computing methods.

Mathematical Biology is designed for students who have continued with mathematics in their post-16 (e.g. sixth form) studies, and a certain level of prior knowledge is assumed. For students from England, Wales or Northern Ireland this would most likely have been gained by the study of Mathematics at A Level, but other equivalent qualifications, including for example the International Baccalaureate, Scottish Highers, Irish Leaving Certificate and German Abitur, are also sufficient. In certain cases some independent study will be required, and help from supervisors.

Programme Specification

This course is taught jointly by several department in the School of Biology.

Aims

This course aims to:

1. introduce students to the application of mathematical modelling in the analysis of biological systems including populations of molecules, cells and organisms;
2. show how mathematics, statistics and computing can be used in an integrated way to analyse biological systems;
3. develop students' skills in algebraic manipulation, the calculus of linear and non-linear differential equations, mathematical modelling, linear algebra, probability and statistical methods;
4. introduce students to scientific programming and data analysis.

Learning outcomes

At the end of the course, students should:

1. have an enhanced knowledge and understanding of mathematical modelling and statistical methods in the analysis of biological systems;
2. be better able to assess biological inferences that rest on mathematical and statistical arguments;
3. be able to analyse data from experiments and draw sound conclusions about the underlying processes using their understanding of mathematics and statistics;
4. understand the use of computers to assist them in using mathematical models and carrying out statistical tests.

Teaching and Learning Methods

These include lectures, supervisions, and computer practicals.

Assessment

Assessment for this course is through:

• one unseen written examination, based on lecture material (for aims 1-4 and learning outcomes 1-4);
• two assessed exercises, based on the lectures and practicals (for aims 1-4 and learning outcomes 1-4).

Courses of Preparation

Essential: A Level Mathematics or equivalent, as set out in the NST admissions entry requirements.

Additional Information

Further information is available on the Course Websites pages.