3 units, Fall Mon/Wed/Fri 2:00-2:50
The deluge of data in modern biology demands new statistical and computational approaches for analysis. To engage UA biology students in this exciting new field, MCB 315 focuses on applying machine learning approaches to big biological data, including genomic sequences and electronic health records. Topics covered include:
- R programming for data analysis
- Cluster analysis for data exploration
- Penalized regression for model building
- Classification of genomic sequences and patient records
- Deep learning
MCB 315 is intended for students in the life sciences interested in big data and machine learning. To promote interaction between students with differing expertise, class sessions focus not on lecturing but rather on group exercises involving computer problem solving.
The mathematical prerequisite for the course is Introductory Statistics. We focus not on mathematical details, but rather on understanding the conceptual basis of the different approaches we will apply.