Undergraduate Programme and Module Handbook 2026-2027
Module MATH3171: Mathematical Biology III
Department: Mathematical Sciences
MATH3171: Mathematical Biology III
| Type | Open | Level | 3 | Credits | 20 | Availability | Available in 2026/2027 | Module Cap | Location | Durham |
|---|
Prerequisites
- Mathematical Methods II (MATH2811) OR Mathematical Methods in Physics (PHYS2611) OR Analysis in Many Variables II (MATH2031)
Corequisites
- None.
Excluded Combination of Modules
- None.
Aims
- Study of non-linear differential equations in biological models, building on level 1 and 2 Mathematics.
Content
- Introduction to application of mathematics to biological systems and environments.
- Core applied modelling techniques such as stability analysis, bifurcation analysis, travelling wave solutions.
- ODE models in biology.
- Reaction diffusion equations.
- Pattern formation in nature: Turing analysis.
- Examples taken from the following: diffusion of insects and other species; the formation of spiral wave patterns in nature; enzyme kinetics; the chemostat for bacteria production; modelling the life cycle of the cellular slime mould Dictyostelium discoideum, and the phenomenon of chemotaxis; epidermal and dermal wound healing; epidemic models and the spatial spread of infectious diseases.
Learning Outcomes
Subject-specific Knowledge:
- Models for diffusion of insect populations.
- Formation of spiral wave patterns.
- Mathematics of enzyme kinetics.
- Mathematics of the Chemostat.
- Chemotaxis and aggregation of species.
- Pattern formation mechanisms.
- Spread of infectious diseases.
Subject-specific Skills:
- Be able to solve novel and/or complex problems in Mathematical Biology.
- Demonstrate an understanding of theoretical mathematics relevant to Mathematical Biology and the ability to apply it appropriately.
Key Skills:
- Basic mathematical skills in the following areas: problem solving, modelling, computation.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Lectures demonstrate what is required to be learned and the application of the theory to practical examples.
- Problem classes show how to solve example problems in an ideal way, revealing also the thought processes behind such solutions.
- Assignments for self-study develop problem-solving skills and enable students to test and develop their knowledge and understanding.
- Formatively and summatively assessed assignments provide practice in the application of logic and a high level of rigour as well as feedback for the students and the lecturer on the students’ progress.
- The end-of-year examination assesses the knowledge acquired and the ability to solve predictable and unpredictable problems.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | Attendance Monitored |
|---|---|---|---|---|---|
| Lectures | 40 | 2 per week for in Michaelmas and Epiphany | 1 Hour | 40 | |
| Problem Classes | 10 | 4 in Michaelmas and Epiphany, 2 in Easter | 1 Hour | 10 | Yes ■ |
| Preparation and Reading | 150 | ||||
| Total | 200 |
Summative Assessment
| Component: Examination | Component Weighting: 70% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| On Campus Written Examination | 2 Hours | 100% | |
| Component: Summative Assignments | Component Weighting: 30% | ||
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Assignment | 4 assignments | 100% | |
Formative Assessment:
Four assignments to be submitted.
■ Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.