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DRPS : Course Catalogue : School of Biological Sciences : Postgraduate

Postgraduate Course: Bioinformatics Algorithms (PGBI11057)

Course Outline
SchoolSchool of Biological Sciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryAlgorithms 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.
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:  33
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 (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:
  1. characterise a given algorithm class and describe the basic properties of this algorithm.
  2. write a computer programme encoding a given algorithm using a programming language of their choice.
  3. select an appropriate algorithm to solve a given task.
Reading List
None
Additional Information
Graduate Attributes and Skills Not entered
KeywordsBioinfAlgor
Contacts
Course organiserDr Simon Tomlinson
Tel: (0131 6)51 7252
Email: simon.tomlinson@ed.ac.uk
Course secretaryMs Louise Robertson
Tel: (0131 6)50 5988
Email: Louise.K.M.Robertson@ed.ac.uk
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