The course is a natural continuation of MATH6100 Bioinformatics and Biological Modelling. However, MATH6100 is not a formal prerequisite for this course since it begins with a brief overview of the main concepts of MATH6100.

Topics covered include:

• The necessary concepts and techniques from the probability theory will be introduced. They will be applied to assessing the significance of the score of pairwise alignments of biological sequences.
• A brief introduction to maximum likelihood estimates and apply this general statistical theory to the Markov chains and hidden Markov models (HMMs) studied in MATH6100.
• Finally, the derivation of PAM and BLOSUM scoring matrices will be explained.

On satisfying the requirements of this course, students will have the knowledge and skills to:

1. Explain the fundamental concepts of a special topic in bioinformatics and its role in modern mathematics and applied contexts.
2. Demonstrate accurate and efficient use of specific bioinformatics techniques.
3. Demonstrate capacity for mathematical reasoning through analysing, proving and explaining concepts from bioinformatics.

Assessment is expected to be based on:

• Three assignments (worth 10% each; LO 1-3)
• Final examination (70%; LO 1-3)