Postgraduate - UnitEPM5012 - Bioinformatics

This unit entry is for students who completed this unit in 2013 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

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6 points, SCA Band 2, 0.125 EFTSL

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Level	Postgraduate
Faculty	Faculty of Medicine, Nursing and Health Sciences
Organisational Unit	Department of Epidemiology and Preventive Medicine
Offered	Not offered in 2013
Coordinator(s)	Professor Graham Wood

Synopsis

The unit begins with a brief review of elementary molecular biology: DNA, RNA, the central dogma, meiosis, mitosis and genes. Some fundamental mathematical tools for statistical analysis are also reviewed. The course then covers sequence alignment, database searching, Mendelian genetics and techniques for discovering connections between genes and disease: association, linkage and variance components studies.

Outcomes

At the completion of this unit the student should be able to:

Explain the core dogma of molecular biology and the central ideas of population genetics.
Given a problem which requires genome or proteome data for its solution, access appropriate web based sources for data, and download the data in suitable format.
Understand and apply core bioinformatics techniques for the analysis of DNA and protein sequence data, such as global sequence alignment, CLAST, Hidden Markov Models, evolutionary models and phylogenetic tree fitting.
Process large quantities of data (such as the expression profiles of thousands of genes resulting form microarray experiments) using R, and communicate results in language suitable for presentation to both a bioinformatics journal and a lay audience.

Assessment

The assessment for this subject will involve four written assignments, each worth 15% plus a comprehensive final assignment worth 40%. The assignments will each involve the application of theory to problems specific to the various analytical tasks in bioinformatics.