BIO436 Applied Bioinformatics & AI in the Life Sciences

[3–0, 3 cr.]

This course introduces computational approaches for analyzing biological data by integrating bioinformatics methods with artificial intelligence techniques. Students develop foundational programming skills in Python and/or R and apply computational tools to sequence analysis, genomics, transcriptomics, and other omics applications. The course introduces molecular modeling approaches, including molecular docking and protein structure prediction using tools such as AlphaFold, as well as introductory machine-learning methods for biological data analysis. Through hands-on projects, students learn to process, analyze, and interpret biological datasets to address challenges in modern life sciences research.