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DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Topics in Mathematical Biology (MATH10083)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 10 (Year 4 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryIntegrative course in Mathematical Biology for joint Honours students in Mathematics and Biology, with a focus on current opinions and topics in evolutionary and systems biology, and a discussion of relevant mathematical modelling techniques and the challenges faced by mathematical biologists in their application. The course will consist of a number of individual modules, to be delivered by a rota of lecturers from the School of Mathematics and the School of Biological Sciences; additional modules may be delivered on a case-by-case basis by academic visitors to either School.

Sample topics include an overview of current trends in both evolutionary and systems biology, as well as a more in-depth discussion of specific sub-areas such as quantitative genetics, epidemiology, and stochastic gene expression, and relevant mathematical techniques such as stochastic modelling, perturbation analysis, and statistical inference.

Throughout, an emphasis is placed on student participation through discussion and presentation, and on two-way interaction with lecturing staff. Correspondingly, the course is assessed by coursework only. Lectures are intertwined with workshop sessions in which the lectured material is discussed in a collaborative studio environment. A sample assessment may consist of a
synoptic study of published research in mathematical biology that is followed by a group presentation. Additionally, students will be expected to attend five seminar talks, to be taken from the Mathematical Biology seminar series, and subsequently to submit a written synopsis of these talks as part of their coursework.
Course description A sample syllabus for this course is given as follows.

Week 1 : Trends in evolutionary biology
Week 2 : Evolutionary genetics
Week 3 : Ecology and epidemiology
Week 4 : Stochastic and probabilistic modelling
Week 5 : Trends in systems biology
Week 7 : Stochastic gene expression
Week 8 : Multiple scales and perturbations
Week 9 : Computational molecular dynamics
Week 10 : Bayesian modelling and regression
Week 11 : Inference and model selection

Specific topics will vary by session, and will depend on the lecturing staff rota.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: ( Honours Differential Equations (MATH10066) AND Likelihood (MATH10004) AND Stochastic Modelling (MATH10007) AND Numerical Ordinary Differential Equations and Applications (MATH10060))
Students MUST have passed: ( Evolutionary and Ecological Genetics 3 (BILG09004) AND Molecular Genetics 3 (BILG09002)) OR ( Molecular Genetics 3 (BILG09002) AND Molecular Cell Biology 3 (BILG09001))
Prohibited Combinations Other requirements None
Information for Visiting Students
Course Delivery Information
Not being delivered
Learning Outcomes
1. Ability to identify current opinions, topics, and challenges in mathematical biology, with a focus on evolutionary and systems biology.
2. Ability to digest and critically assess a selection of published research in mathematical biology.
3. Facility in presenting complex mathematical concepts to non-specialists in an accessible fashion.
4. Knowledge of the state of the art in biological experimentation, data assimilation and processing, and the mathematical modelling of biological phenomena.
5. Ability to evaluate the relevance of both established and novel mathematical modelling techniques to emerging biological applications.
Reading List
Relevant original research articles and recent reviews, to be chosen as appropriate by the lecturing staff delivering the course in a given session.
Additional Information
Graduate Attributes and Skills Not entered
Course organiserDr Martin Dindos
Course secretaryMrs Alison Fairgrieve
Tel: (0131 6)50 5045
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