COMPGI10 - Bioinformatics
This database contains 2016-17 versions of the syllabuses. For current versions please see here.
|Code||COMPGI10 (Also taught as: COMPM058 Bioinformatics)|
|Prerequisites||It is expected that students will already be familiar with the principles of techniques such as neural networks, Support Vector Machines, Hidden Markov Models from earlier parts of the course.|
|Taught By||David Jones (66%), Kevin Bryson (33%)|
|Aims||The overall aim of this course is to introduce students to the new field of bioinformatics (computational biology) and how machine learning techniques can be employed in this area. The course is aimed at students who have no previous knowledge of biology and so the aim of Part 1 of the course is to give a basic introduction to molecular biology as a background for bioinformatics. Part 2 will concentrate on modern bioinformatics applications, particularly those which make good use of pattern recognition and machine learning methods.|
|Learning Outcomes||To have a basic knowledge of modern molecular biology and genomics. To understand the advantages and disadvantages of different machine learning techniques in bioinformatics and how the relative merits of different approaches can be evaluated by correct benchmarking techniques. To understand how theoretical approaches can be used to model and analyse complex biological systems.|
Method of Instruction:
Lecture presentations with associated class problems and group presentation/discussion of key research papers.
The course has the following assessment components:
- Written Examination (2.5 hours, 85%)
- Coursework Section (1 individual mini-project, 15%)
To pass this module, students must:
- Obtain an overall pass mark of 50% for all components combined.
Biochemistry - Lubert Stryer, WH Freeman and Co.
Post-genome Informatics, M. Kanehisa, Oxford University Press.
Bioinformatics - Genes, Proteins and Computers, C.A. Orengo, D.T. Jones and
J.M. Thornton, BIOS Scientific Publishers, 2003
Mathematical Biology, J.D. Murray, Springer, 1993.
Other references (including research papers) to be confirmed.