Data Science Methods in Biological & Health Sciences

This course introduces students to modern computational approaches for studying biology through DNA and protein sequence data. The course develops a unifying view of sequence count data across gene expression, microbiome studies, and deep mutational scanning. Students explore machine learning methods for protein analysis and design, including protein language models, variant effect prediction, functional annotation, active learning, and generative AI approaches for protein discovery. Throughout the course, emphasis is placed on understanding data-generating processes, statistical structure, modeling assumptions, and practical limitations of biological measurement, enabling students to critically evaluate and apply modern AI methods in biological research.