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 Java programming language (by default). 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
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| Academic year 2020/21, Not available to visiting students (SS1)
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Quota: 54 |
| 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
80 %,
Coursework
20 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
1. Examination (80%)
2. Written Assessment (20%) |
| 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 | Ms Louise Robertson
Tel: (0131 6)50 5988
Email: Louise.K.M.Robertson@ed.ac.uk |
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