This graduate course introduces the computational, statistical and algorithmic foundations for analysing modern biological data. It covers sequence analysis, genome and transcriptome analysis, statistical inference and machine learning for high-dimensional omics data, biological databases, and networks and pathways, with a strong emphasis on hands-on practice using command-line tools and the R and Python ecosystems. Reproducible, well-documented workflows are emphasised throughout. The course equips students to design, execute and critically interpret computational analyses that support biomedical research and to prepare for data-intensive doctoral study.
Grad Scheme
Letter
Prerequisites
None