Postgraduate Course: Bioinformatics Algorithms (PGBI11057)
Course Outline
| School | School of Biological Sciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | 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.
The course has a strong practical component that concentrates on the implementation of algorithms using the Python programming language (with additional Java examples). We use the implementation of algorithms to explore the properties of algorithms in a bioinformatics setting. |
| Course description |
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 - eg Smith-Waterman local sequence alignment
- Graph-based algorithms
- Clustering and Tree-based algorithms
- Finding sequence patterns with algorithms
- Hidden Markov Models
- Genetic Algorithms
- Running algorithms on compute clusters concentrating on MapReduce and Apache Hadoop.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
|
| Academic year 2024/25, Not available to visiting students (SS1)
|
Quota: 40 |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 10,
Supervised Practical/Workshop/Studio Hours 10,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
76 )
|
| Assessment (Further Info) |
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
1. Examination (50%)
2. Written Assessment (50%) |
| Feedback |
Written feedback will be given for both the exam and ICA. |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- characterise a given algorithm class and describe the basic properties of this algorithm.
- write a computer programme encoding a given algorithm using a programming language of their choice.
- select an appropriate algorithm to solve a given task.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | BioinfAlgor |
Contacts
| Course organiser | Dr Simon Tomlinson
Tel: (0131 6)51 7252
Email: simon.tomlinson@ed.ac.uk |
Course secretary | Mr Alex Ramsay
Tel:
Email: gramsay3@ed.ac.uk |
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