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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2014/2015
- ARCHIVE as at 1 September 2014

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DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Stochastic Models in Biology (MATH11116)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 11 (Year 4 Undergraduate) Credits10
Home subject areaMathematics Other subject areaNone
Course website https://info.maths.ed.ac.uk/teaching.html Taught in Gaelic?No
Course descriptionThis course focuses on stochastic models and analytical approaches for their solution. The models are introduced through various biological examples, including molecular motor motion, virus dynamics, population genetics and tumour progression.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
Displayed in Visiting Students Prospectus?No
Course Delivery Information
Not being delivered
Summary of Intended Learning Outcomes
Understanding the dynamics of certain living systems (molecular motors, genes, viruses, tumours, etc) in the light of recent experimental results. Learning how to construct models of these systems, and introducing some of the standard modelling approaches: branching processes, Moran and Wright-Fisher models of population genetics, and random walks. Acquiring techniques to solve these models exactly, asymptotically, or approximately.
Assessment Information
Coursework 20%, Examination 80%
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsSMB
Contacts
Course organiserDr Tibor Antal
Tel: (0131 6)51 7672
Email: Tibor.Antal@ed.ac.uk
Course secretaryMrs Alison Fairgrieve
Tel: (0131 6)50 5045
Email: Alison.Fairgrieve@ed.ac.uk
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