This practice-oriented course differs from many of the other courses you may have taken. We will focus heavily on the hands-on computational skills you need to extract biological information from large 'omics datasets, including genomes, transcriptomes, metagenomes and more. Delivered through a range of practical activities, this course is assessed solely through assignments, and spans topics from the dynamic nature of the genome, through to sequence analysis, data visualization and data interpretation. This introduction to computational analysis is geared towards biologists and assumes no previous knowledge or familiarity with computational methods.
| Week | Module | Topic |
|---|---|---|
| 1 | Bootcamp | Introduction to R |
| 2 | Bootcamp | Introduction to UNIX |
| 3 | Bootcamp | Introduction to Visualization |
| 4 | Molecular Evolution | Sequencing and Mapping |
| 5 | Molecular Evolution | Variants and Phylogenies |
| 6 | Molecular Evolution | Evolutionary Visualization |
| 7 | Science Communication | Science and the Public |
| 8 | Microbial Diversity | Barcodes and Diversity |
| 9 | Microbial Diversity | Metagenomics |
| 10 | Microbial Diversity | Metagenomic Visualization |
| 11 | Human Genomics | Transcriptomics |
| 12 | Human Genomics | Transcriptomic Visualization |
NB: This year, the mid-semester break is between Weeks 7 and 8.