Syllabus for Bio431: Computational Cancer Biology
Fall 2015
Cancer is a notoriously heterogeneous disease. 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 data cohorts such as The Cancer Genome
Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) provide an opportunity
to analyze biological measurements from hundreds to thousands of cancer samples. Focusing on
these data repositories, we will learn about state-of-the-art computational methods used to analyze
high-throughput cancer datasets by reading and discussing primary literature.
Professor: Anna Ritz (aritz@reed.edu)
Time & Place: M 6:10pm-8:00pm seminar, BIOL 200A
Website: http://reed.edu/biology/courses/bio431/compcancerbio
Moodle: https://moodle.reed.edu/course/view.php?id=619
Course Structure: After an introduction by Anna, each student will select one paper according
to a list of topics provided in the schedule and give an in-class presentation. Success in the class
will depend on a combination of the presentation and participation in discussion.
Readings:
• All students will read the paper(s) before each seminar. Bring the readings to seminar (either
in paper or on your laptops).
• There may be some reading suggestions to help focus the content. These will be posted on
Moodle along with the papers.
Presentations:
• Meet with Anna the week before to discuss the paper. Email her or let her know after class
to set up an appointment.
• Hand out an outline (no longer than one page) with important points and/or equations.
• The presentation may either be on a board or on slides. For the presentation:
– ∼10 minutes introducing background concepts not covered in the paper.
– ∼1 hour talk on the paper content.
– End with your thoughts and opinions.
– Refer to the presentation tips on Moodle.
• If you used slides, email Anna the PDF and she will post it on Moodle.
Last Updated August 28, 2015