Module manager: Dr David Starns
Email: D.E.Starns@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2025/26
| BIOL2113 | Introduction to Omics Biology |
BIOL2112 Genes and Genomes, 20c, S1
This module is not approved as a discovery module
Biology is central to addressing many of the global challenges facing society today, including the rise of antimicrobial resistance, the spread of infectious diseases, and the urgent need for sustainable food production. Modern high-throughput Omics techniques—such as genomics, transcriptomics, and proteomics are revolutionizing biological research by generating vast and complex datasets. The ability to interpret and utilize these data effectively has only been made possible through the integration of computational and data science, creating a powerful interdisciplinary approach to discovery. This module introduces students to these cutting-edge technologies and their implications, with a strong emphasis on practical skills in Omics data analysis using the platform, Galaxy. Students will explore scientific dimensions of data-driven biology and apply their learning through individual research projects, preparing them to contribute meaningfully to the evolving landscape of biological science and global health.
The objective of the module is to provide students with an overview of modern omics and big data approaches to understand how these concepts are driving discovery in modern biology. Students will consolidate these concepts by applying them to real-world data to evaluate data-driven research.
By the end of this module, students will be able to:
1. Describe ways in which ‘omics-based methods have advanced understanding of prokaryotic and eukaryotic biology and evolution;
2. Analyse and interpret omics data within an experimental context and draw evidence based conclusions;
3. Evaluate the most appropriate approaches to experimental design and apply to experimental problems;
4. Critically evaluate the scientific literature from journal articles and incorporate relevant material into written assignments.
Computer and bioinformatic skills - Data interpretation - Data and research paper evaluation - Managing knowledge - Problem solving - Recording practical data - lab book management - Report writing – Group working – Project Management – Data management – analysis of Omics data
The module is composed of three main sections covering three principal Omics areas of biology's central dogma.
· Unit one – Genomics. This unit covers both prokaryote and eukaryote systems.
· Unit two – Translatomics. This unit looks at gene expression related omics.
· Unit three – Proteomics. This unit covers the theory outcomes and analysis of protein
The remainder of the module will focus on deepening our understanding of key technologies and their practical applications. This will include sessions with guest speakers and cover topics such as:
· Metagenomics and microbial profiling
· Machine learning, big data, and ontologies
· Statistical analysis of omics data
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lectures | 12 | 1 | 12 |
| Practicals | 6 | 2 | 12 |
| Independent online learning hours | 8 | ||
| Private study hours | 168 | ||
| Total Contact hours | 24 | ||
| Total hours (100hr per 10 credits) | 200 | ||
Formative self-directed bioinformatics exercises (4x 2hrs)
Formative bioinformatics workshops in computer cluster (6x 2hrs)
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Report | Individual report (2000 words) | 70 |
| Total percentage (Assessment Coursework) | 70 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
| Exam type | Exam duration | % of formal assessment |
|---|---|---|
| Standard exam (closed essays, MCQs etc) | 1.0 Hrs 30 Mins | 30 |
| Total percentage (Assessment Exams) | 30 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Check the module area in Minerva for your reading list
Last updated: 09/09/2025
Errors, omissions, failed links etc should be notified to the Catalogue Team