The course covers the basic elements in the pipeline of high-throughput data analysis:
- crash course on molecular biology
- overview on sequencing technologies
- alignment and normalization algorithms
- QC criteria
- unsupervised learning methods for subtyping and data exploration
- supervised learning methods for variable selection
- functional characterisation
- network reconstruction algorithms.
Two ninth of the credit are obtained through a final project.
Associate Professor of Computer Science
- Outside Preparation