Mandatory for MSc in Industrial Biotechnology | Elective for MSc in Digital Health Systems

None

Lectures: 10 hours  |  Tutorials: 5 hours  |  Labs: 10 hours  |  Self-directed study: 75 hours

1. First coursework assignment (50%): Students will be asked to conduct a piece of research using techniques and approaches introduced in the first half of the module, submitting their work in Jupyter notebook format. The focus will be on the ability to identify and integrate data from multiple sources, as well as reproducibility, understanding and presentation of results.
2. Second coursework assignment (50%): Students will be asked to conduct a piece of research using techniques and approaches from across the entire module, submitting their work as a report in pdf format. The focus will be on identifying and integrating data from multiple sources, appropriateness of analysis, as well as understanding and presentation of results.

Learning objectives (LOs) - After completing this module, students will be able to:
1) apply core concepts of genetics and genomics (such as gene structure and expression) to interpret biological datasets;
2) evaluate major DNA/RNA sequencing technologies and common bioinformatics tools for defined research problems;
3) integrate, process and analyse real-world biological data from multiple scientific databases and in various formats;
4) design and implement reproducible bioinformatics workflows in Jupyter Notebook using existing libraries and tools;
5) communicate analytical findings and justify methodological decisions in a structured and concise scientific report.

The assessments are mapped to the LOs above in the following way:
- coursework 1: LOs 1, 2, 3, 4
- coursework 2: LOs 1, 2, 3, 5

Single coursework assignment (100%): Students will be asked to conduct a piece of research using techniques and approaches from across the entire module, submitting their work as a report in pdf format. The focus will be on identifying and integrating data from multiple sources, appropriateness of analysis, as well as understanding and presentation of results.