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2009/10 Taught Postgraduate Module Catalogue
MATH5840M Hidden Markov Models for Biological Sequence Analysis
15 creditsClass Size: 25
Module manager: Professor W. Gilks
Email: wally@maths.leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2009/10
Pre-requisites
| MATH1725 | Introduction to Statistics |
This module is not approved as an Elective
Objectives
On completion of this module, students should be able to:(a) understand hidden Markov models and dynamic programming algorithms
(b) understand bioinformatic sequence alignment algorithms
(c) be familiar with applications of HMMs in bioinformatics
(d) use bioinformatic software to analyse biological sequences.
Skills outcomes
Transferable Skills: programming skills.
Syllabus
(a) Pairwise sequence alignment
(b) Dynamic programming
(c) Alignment algorithms
(d) Hidden Markov models
(e) Bioinformatics applications of HMMs
(f) Software and web resources.
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Example Class | 7 | 1.00 | 7.00 |
| Laboratory | 2 | 1.00 | 2.00 |
| Lecture | 26 | 1.00 | 26.00 |
| Private study hours | 115.00 | ||
| Total Contact hours | 35.00 | ||
| Total hours (100hr per 10 credits) | 150.00 | ||
Opportunities for Formative Feedback
Examples sheets.Methods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| Report | 15-30 pages | 25.00 |
| Total percentage (Assessment Coursework) | 25.00 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Exams
| Exam type | Exam duration | % of formal assessment |
| Standard exam (closed essays, MCQs etc) | 3 hr 00 mins | 75.00 |
| Total percentage (Assessment Exams) | 75.00 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Reading list
The reading list is available from the Library websiteLast updated: 22/03/2010
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