School of Computer Science

Module 06-23836 (2011)

Computational Modelling with MATLAB

Level 4/M

Shan He Semester 2 10 credits
Co-ordinator: Shan He
Reviewer: Iain Styles

The Module Description is a strict subset of this Syllabus Page.

Aims

The aims of this module are to:

  • Introduce computational techniques for modelling dynamic systems
  • Demonstrate how to use MATLAB to construct computation models to simulate dynamic systems
  • Gain practical experience of modelling biological systems using MATLAB

Learning Outcomes

On successful completion of this module, the student should be able to:

  • Formulate dynamic models of biological systems, using equation based and individual based techniques
  • Select an appropriate technique for modelling given biological problems such as gene regulatory networks and animal swarms. Be able to explain the underlying assumptions and limitations
  • Implement these models using MATLAB
  • Apply the MATLAB toolboxes: Systems Biology Toolbox and Probabilistic Boolean Networks Toolbox to model biological systems as appropriate

Teaching methods

Lectures, computer laboratories

Assessment

  • Sessional: Formal written exam (80%), assessed computer practicals (20%)
  • Supplementary: Formal written exam (100%)

Detailed Syllabus

  1. Lectures: Introduction to dynamic systems modelling (Week1, 2 hours)
  2. Lectures: Brief Introduction to MATLAB (Week 2, 2 hours)
  3. Lectures: Equation-based modelling techniques
    • Ordinary Differential Equations (Week 3, 2 hours)
    • Partial Differential Equations (Week 4, 2 hours)
    • Numerical methods for solving differential equations (Week 5, 2 hours)
  4. Lectures:Agent-based modelling techniques
    • Basic concepts and modelling strategies (Week 6, 2 hours)
    • Cellular automata and random Boolean networks (Week 7, 2 hours)
    • Modelling flocking behaviour and its evolution (Week 8, 2 hours)
  5. Lectures: Introduction to MATLAB modelling toolboxes (Week 9, 2 hours)
  6. Lectures: Methods for analysing computational models (Week 10, 2 hours)
  7. Lectures: Summary (Week 11, 2 hours)
  8. Computer lab: MATLAB implementation of equation-based models
    • The Lotka-Volterra model (Week 3, 2 hour)
    • Two species competition and predator-prey models (Week 4, 2 hour)
    • Runge-Kutta methods (Week 5, 2 hour)
  9. Computer lab: MATLAB implementation of agent-based models
    • Cellular automata (Week 7, 2 hour)
    • Flocking model (Week 8, 2 hour)
  10. Computer lab: Using Systems Biology toolbox for MATLAB (week 9, 2 hours)

Programmes containing this module