Bioinformatics Applications in Biomedicine

Graduate / Professional

This advanced graduate course prepares students to analyze real-world biomedical data at scale across omics data and electronic health record (EHR) data. Emphasizing reproducible workflows, statistical rigor, and clinical translation, students work directly with large-scale omics datasets and biobank resources, including the All of Us Research Program. Through coding-intensive assignments, students develop Linux-based pipelines, Slurm-driven HPC workflows, cloud-native analyses, and EHR-based cohort construction for translational investigations. Student-led journal presentations strengthen algorithmic understanding, reproducibility, and translational thinking. Designed to complement theory-driven coursework, the course focuses on practical execution—equipping students to build scalable pipelines, generate biologically and clinically meaningful insights, and communicate methods with professional technical clarity. Proficiency in Python and R for data analysis. M 2:30pm-5pm