BMS5021 · Introduction to Bioinformatics

Overview

This unit will train you in the principles and practical approaches of computational biology algorithms for Bioinformatics analyses of data derived from genes and proteins. The unit will start by building solid foundational knowledge of the biology of the gene focusing on basic concepts of biological information stored in DNA and its translation to functional biomolecules. You will learn to critically evaluate leading existing bioinformatics tools used to address biological questions. The unit completes the cycle of learning by asking you to apply this knowledge to the analysis of big datasets from biomedical and genomics experiments.

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

1. Describe the relationships between DNA, RNA, and proteins and their roles in cell functioning.
2. Explain the health data life cycle and the relevance of computation in modern life sciences research.
3. Explain how nucleotide and protein sequence and structure data are represented and processed in computational biology.
4. Evaluate the merits and limitations of the major bioinformatics databases to solve specific computational biomedical problems.
5. Use bioinformatic tools and databases to analyse nucleotide or protein sequences.
6. Perform elementary statistical analysis on biomolecular and “omics” datasets and represent the outcomes in informative graphical displays and data summaries.

Workload

Per week: 6 hours of direct learning + 6 hours of self-directed learning.

Student experience, not official rules. Nothing here changes what the Handbook says.