Module 23836 (2012)
Syllabus page 2012/2013
06-23836
Computational Modelling with MATLAB
Level 4/M
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus
The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)
Relevant Links
Outline
This module will introduce practical computational techniques used for modelling dynamic systems. The concepts of dynamic systems, especially biological systems will be introduced. We will then introduce two main computational modelling techniques for modelling dynamic systems: (1) equation-based and (2) individual based modelling techniques. By using examples drawn from real-world dynamic systems, especially biological systems, students will explore and understand both modelling techniques, in particular their underlying assumptions and limitations and how to apply them appropriately to model new dynamic systems. Students will learn how to use MATLAB to construct computation models based on the two modelling techniques to simulate biological systems such as gene regulatory networks and animal swarms. Students will also be introduced to the advanced MATLAB toolboxes: Systems Biology Toolbox and Probabilistic Boolean Networks Toolbox, and will use them for the modelling of biological systems.
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: | Assessed by: | |
| 1 | Formulate dynamic models of biological systems, using equation based and individual based techniques | Examination, computer practicals |
| 2 | 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 | Examination, computer practicals |
| 3 | Implement these models using MATLAB | Examination, computer practicals |
| 4 | Apply the MATLAB toolboxes: Systems Biology Toolbox and Probabilistic Boolean Networks Toolbox to model biological systems as appropriate | Examination, computer practicals |
Restrictions, Prerequisites and Corequisites
Restrictions:
None
Prerequisites:
None
Co-requisites:
None
Teaching
Teaching Methods:
Lectures, computer laboratories
Contact Hours:
Assessment
- Sessional: Formal written exam (80%), assessed computer practicals (20%)
- Supplementary (where allowed): Formal written exam (100%)
Recommended Books
| Title | Author(s) | Publisher, Date |
| The Nature of Mathematical Modelling | Neil Gershenfeld | Cambridge University Press, |
| Agent-based Models | Nigel Gilbert | Sage Publications, |
| Applied Numerical Methods with MATLAB for Engineering and Science | Steven C. Chapra | McGrow Hill Press, |
Detailed Syllabus
- Lectures: Introduction to dynamic systems modelling (Week1, 2 hours)
- Lectures: Brief Introduction to MATLAB (Week 2, 2 hours)
- 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)
- 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)
- Lectures: Introduction to MATLAB modelling toolboxes (Week 9, 2 hours)
- Lectures: Methods for analysing computational models (Week 10, 2 hours)
- Lectures: Summary (Week 11, 2 hours)
- 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)
- Computer lab: MATLAB implementation of agent-based models
- Cellular automata (Week 7, 2 hour)
- Flocking model (Week 8, 2 hour)
- Computer lab: Using Systems Biology toolbox for MATLAB (week 9, 2 hours)
Last updated: 14 June 2011
Source file: /internal/modules/COMSCI/2012/xml/23836.xml
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus