Course overviewExtensive efforts to profile genomic alterations in thousands of tumors have produced massive datasets, and the major burden has shifted from data generation to data interpretation. This course will focus on computational analyses of cancer data, primarily high-throughput "omic" data (i.e. genomic, transcriptomic, proteomic, etc.). Topics have been selected to illuminate 1) important problems in cancer biology that can be addressed by computational and statistical techniques and 2) general-purpose computational biology strategies that have proven useful in cancer. This course will only be offered in the Spring 2015 semester and is not likely to become a regular course in the future.
Students will present and discuss research articles and work in groups to complete a project analyzing large-scale cancer datasets such as those from The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia.