Postgraduate Course: Bioinformatics Algorithms (PGBI11057)
Course Outline
| School | School of Biological Sciences |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 10 |
| Home subject area | Postgraduate |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | Algorithms are a set of rules that allow a problem to be solved, often encoded in a computer programme. Algorithms are ubiquitous in bioinformatics and are often at the interface of computer science and biology.
All bioinformatics students need a good understanding of algorithms, in order to select appropriate methods to solve a given task, to understand the outputs of bioinformatics software and to write software that solves particular bioinformatics problems. |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
| Additional Costs | None |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | No |
Course Delivery Information
| Not being delivered |
Summary of Intended Learning Outcomes
* Students will be able to characterise a given algorithm class and describe the basic properties of this algorithm.
* Students will be able to write a computer programme encoding a given algorithm using a programming language of their choice.
* Students will be able to select an appropriate algorithm to solve a given task. |
Assessment Information
1. Examination (80%)
2. Written Assessment (20%) |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
In this course we will cover:
- The theory of algorithms - e.g. how to formally describe an algorithm, what makes a good algorithm, classes of algorithm.
- The implementation of algorithms in software applications
- Searching algorithms - both exhaustive and heuristic
- Dynamic programming algorithms - such as Smith-Waterman local sequence alignment
- Graph-based algorithms
- Clustering and Tree-based algorithms
- Hidden Markov Models
- Genetic Algorithms |
| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | BioinfAlgor |
Contacts
| Course organiser | Dr Simon Tomlinson
Tel: (0131 6)51 7252
Email: |
Course secretary | Miss Vicky Mactaggart
Tel: (0131 6)51 7052
Email: |
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