EPM5012 - Bioinformatics - 2017

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.

Upon successful completion of this unit, students should be able to:

1. Explain the core dogma of molecular biology and the central ideas of population genetics.
2. 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.
3. 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.
4. 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.

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

Professor Andrew Forbes

Biostatistics

EPM5002, EPM5003, EPM5004, EPM5014, MPH5040.

Must be enrolled in course code: 3420, 3421, 3422 or M6025.

This unit is only available to students enrolled in the Graduate Certificate, Graduate Diploma or Masters of Biostatistics.

http://www.med.monash.edu.au/epidemiology/pgrad