203. Bioinformatics III: Data Wrangling in Bioinformatics

4 credits

The course introduces OMICS data modalities and key algorithms for their analysis. The first part of the course covers algorithmic paradigms like keyword filters, bloom filters, sketching, and random projections for transforming OMICS data into abstract forms. The second part of the course focuses on statistical and combinatorial methods for querying these representations in a domain-agnostic way, emphasizing foundational work underlying emerging tools. Recommended preparation: Experience with algorithms, nonnumerical algorithms such as sorting, searching, pattern matching, and graph and network algorithms is recommended. Students will not receive credit for both CSE 283 and BENG 203.