By Yu (Tom) Gao @ College of Pharmacy, University of Illinois Chicago
Target audience:
Graduate students in Pharmaceutical Sciences, Medicinal Chemistry, Biochemistry and other similar fields with no formal data science training.
Learning objectives:
1. Learn basic bioinformatics techniques in Python or R
2. Learn how to process RNA-seq data, proteomics data, metabolomics data
3. Learn basic statistics and software packages to perform differential analysis
4. Learn the basic of pathway enrichment and gene ontology analysis
5. Learn the basic of machine learning and how to apply basic machine learning approches
The first part of the course is self-paced, online study of the basic grammar of Python or R (depends on your preference), please use this to learn the basics of Python and R programming.
Once completed, please do the practice problems and test your own ability.
Before the formal in-person class, please summarize your bioinformatics related problems/challenges in your research projects and bring these to the class. We will use these as example problems for the class.
