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 (Spring 2021, Virtual)

Anna Ritz: aritz-at-reed-dot-edu (Bio 200B)
Time & Place
Wed 6:10pm-8:00pm, Online (Zoom Link on Moodle)
Course Syllabus
Moodle Link (must be an enrolled student to access)
Schedule (including previous offerings)

Course Objectives

At the end of this course, students will be able to:
  • Understand the breadth of cancer biology research presented in review articles.
  • Critically read current primary scientific literature in the field of cancer biology and computational applications.
  • Identify and summarize the main steps of computational methods from a scientific article.
  • Participate in and lead a discussion around a specific scientific finding or set of findings.
  • Investigate a claim or story about cancer biology by identifying appropriate and reliable references.

Course Structure

The class will read and discuss review papers and technical, primary literature. We will center our focus on a pan-cancer analysis, which appeared in a recent Nature special collection called Pan-Cancer Analysis of Whole Genomes. Students will engage with the material in three ways:
  • Discussion Participant. Students who are not leading discussion will complete a short form about the paper and participate in discussion.
  • Discussion Leader. Pairs of students will lead two discussions about technical papers.
  • Cancer in the News. Students will have a semester long writing assignment to investigate a recent claim or story about cancer biology and emerging technologies.