COMS W4762
Machine Learning for Functional Genomics
This course will introduce modern probabilistic machine learning methods using applications in data analysis tasks from functional genomics, where massively-parallel sequencing is used to measure the state of cells: e.g. what genes are being expressed, what regions of DNA (“chromatin”) are active (“open”) or bound by specific proteins.
Prerequisites & course information
Prerequisites: Proficiency in a high level programming language Python/R/Julia. An introductory machine learning class such as COMS W4771 Machine Learning will be helpful but is not required.
Sources
- Course catalogue ↗2026-2027
- Catalogue entry ↗
Catalogue variants
- Machine Learning for Functional Genomics · 3 points · University catalogue