Module Information

Module Identifier
MA34810
Module Title
Mathematical Models of Biological Systems
Academic Year
2015/2016
Co-ordinator
Semester
Semester 2
External Examiners
  • Dr Andrew Hazel (Reader - University of Manchester)
 
Other Staff

Course Delivery

Delivery Type Delivery length / details
Lecture 33 x 1 Hour Lectures
 

Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment Coursework (4 assignments)  20%
Semester Exam 2 Hours   (written examination)  80%
Supplementary Exam 2 Hours   (written examination)  100%

Learning Outcomes

On successful completion of this module students should be able to:

1. Identify key parameters in a complex system upon which to base a model.

2. Demonstrate an understanding of the stability of the solutions to a mathematical model.

3. Demonstrate an ability to solve differential and difference equations, including those representing population balances.

4. Explain the use of computers as a tool to explore complex dynamics.

Aims

Mathematical Biology is an area of interest that is growing rapidly in popularity; with a little knowledge of biology, mathematicians are now able to develop appropriate models of biological phenomena which are also of mathematical interest in their own right. Mathematicians who are familiar with rigorous biological modelling have extremely attractive employment prospects in this and related areas such as medicine.

Brief description

This course aims to develop students' ability to identify the key parameters in a complex system and create and solve a comparatively simple model, the results of which can then be related back to the original system. Examples will include chaotic population models and waves in reaction-diffusion systems.

Content

Continuous and Discrete Single Species Population Models; Logistic Map; Fixed points; Linear Stability Analysis; Transition to Chaos.
Two species population models; Lotka Volterra; Predator Prey.
Spread of Epidemics.
Reaction Diffusion Equations; Propagating Wave Solutions; Travelling Fronts; Spatial Pattern Formation; Animal Coat Patterns.

Module Skills

Skills Type Skills details
Application of Number Necessary throughout.
Communication Written answers to exercises must be clear and well-structured. Good listening skills are essential to successful progress in this course.
Improving own Learning and Performance Students will be expected to develop their own approach to time-management in their attitude to the completion of work on time, and in doing the necessary preparation between lectures.
Information Technology Students will be set exercises involving the use of computer and library facilities.
Personal Development and Career planning Completion of tasks (problem sheets) to set deadlines will aid personal development. The course will give clear indications of the range of possible employment opportunities available to students who successfully complete it.
Problem solving In addition to problem classes, further exercises will be set and marked. These will involve the identification and derivation of appropriate solutions.
Research skills Computer classes will allow students to explore the parameter space of a dynamical system, and draw conclusions about determining solutions relevant to the physical system.

Notes

This module is at CQFW Level 6