On completion students will:
1. have a basic understanding of modern genetics;
2. understand the implications of bioinformatics for epidemiology, gene discovery and studies of gene function;
3. be able to apply appropriate statistical methods to the analysis of genetic data from studies of human subjects, both family and population-based.

The first component of the course is an introduction to various topics of elementary molecular biology, which is fundamental to the analysis of genetics data. Conducting database searches (of DNA, RNA, amino acids and proteins databases) is one of the most common tasks in bioinformatics, so a grounding in these methods is provided.
Students will also be given a grounding in important probability/statistical models (Mendelian inheritance, Hardy-Weinberg equilibrium, crossing over, and map distance). Descriptions of the various types of genetic studies (linkage and family studies, linkage disequilibrium and population studies) will also be provided.

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Epidemiology;
Mathematical Background for Biostatistics;
Principles of Statistical Inference;
Linear Models
Probability and Distribution Theory

Distance Learning : Paper Based

Self Directed Learning

Self Directed Learning: for 6 hour(s) per Week for Full Term