Cancer is a notoriously heterogeneous disease, and individuals with the same cancer type may have vastly different mutations and patterns of gene regulation. How can we tell which mutations are important for cancer progression? Publicly-available datasets provide an opportunity to computationally analyze biological measurements from hundreds to thousands of cancer samples. We will learn about state-of-the-art computational methods used to analyze high-throughput cancer datasets by reading and discussing primary literature.

Course Details

Professor
Anna Ritz: aritz-at-reed-dot-edu (Bio 200B)
Time & Place
Th 6:10pm-8:00pm, Bio 215
Course details and eReserves are available on Moodle
Course Syllabus
Schedule of Topics (including previous offerings)