Big Data vs. Reading a Paper, Approaches to Discovering New Cancer Drugs (Science Seminar Series)

Science Center 103

Open to the public

/ Tuesday


Our laboratory studies transcriptional regulation that governs the interaction between viral infection and the development of cancer. In doing so, we can identify protein regulators of genome organization and chromatin essential for cellular immortalization. This basic science forms the foundation for our translational approaches using small molecule inhibitors as potential interventions against virus-associated cancer. Basically, we study large data sets to connect changes in gene regulation with proteins that may ultimately be the target of novel therapeutic strategies. This sometimes works. More often than not, the approach usually fails. Sometimes, however, we ignore big data and discover new treatments by reading a single paper and connecting basic concepts. We’ll discuss examples of both approaches to discovering new cancer drugs.

JJ grew up in California and was advised by one of his first research mentors to go to a liberal arts school and surround himself with some serious scholars. He therefore received his BA from Reed College and then his PhD from Harvard. After graduation, he joined the faculty of the University of California, San Francisco and the Gladstone Institutes. JJ recently moved back to the east coast to return his liberal arts school roots at Barnard College in the Department of Biology where his team studies the interface of virology, cancer, and gene regulation.