Computational Genetics focuses on the large-scale analysis of genes and genomes. By modelling DNA sequence variation, gene expression, epigenetic data, and other molecular features, researchers formulate and test quantitative hypotheses about how genetic information is organised, regulated, and evolves. These approaches are used across the biosciences, from evolutionary and phylogenetic studies to understanding fundamental biological mechanisms underpinning health and disease. Together, these tools help explain how genetic information shapes biological processes, supporting research from molecular to ecological scales.
People
| Name | Department |
|---|---|
| Aida Andres | UCL Genetics Institute |
| Jurg Bahler | Institute of Healthy Ageing |
| Chris Barnes | Cell and Developmental Biology |
| David Curtis | UCL Genetics Institute |
| James GIlbert | Genetics, Evolution and Environment |
| Richard Mott | UCL Genetics Institute |
| Maria Secrier | UCL Genetics Institute |
| Ziheng Yang | Centre for Life’s Origins and Evolution |
Modules
| Code | Title |
|---|---|
| BIOL0003 | Introduction to Genetics |
| CELL0013 | Functional Genetics of Model Systems |
| BIOL0010 | Introduction to Human Genetics |
| BIOL0021 | Advanced Human Genetics |
| BIOL0025 | Regulatory Genomics and Evolution |
| BIOL0029 | Computational Biology |
| BIOL0034 | Applications in Human Genetics |
| BIOL0050 | Advanced Computational Biology |