Biomedical Data Science Courses
Study with the foremost scientists in the field
BIODS 299: Directed Reading and Research (Aut, Wtr, Spr, Sum)
Instructors: Bustamante, Carlos; Hastie, Trevor; Olshen, Richard; Rivas, Manuel; Sabatti, Chiara; Salzman, Julia; Tibshirani, Rob; Zou, James
For students wishing to receive credit for directed reading or research time.
BIODS 232: Consulting Workshop on Biomedical Data Science (Aut, Wtr, Spr)
The Data Studio is a collaboration between Spectrum (The Stanford Center for Clinical and Translational research and Education) and the Department of Biomedical Data Science (BDS). The educational goal of this workshop is to provide data science consultation training for students. The Studio is open to the Stanford community, and we expect it to have educational value for students and postdocs interested in biomedical data science. Most sessions are workshops that provide an extensive and in-depth consultation for a Medical School researcher based on research questions, data, statistical models, and other material prepared by the researcher with the aid of our facilitator. At the workshop, the researcher explains the project, goals, and needs. Experts in the area across campus will be invited and contribute to the brainstorming. After the workshop, the facilitator will follow up, helping with immediate action items and summary of the discussion.
Instructors: Lu, Ying; Sabatti, Chiara; Tian, Lu; Desai, Manisha; Efron, Bradley; Narasimhan, Naras; Stell, Laurel
BIODS 237: Deep Learning in Genomics and Biomedicine, crosslisted as BIOMEDIN 273B, CS 273B, GENE 236 (Aut)
Instructors: Kundaje, Anshul; Zou, James
Recent breakthroughs in high-throughput genomic and biomedical data are transforming biological sciences into "big data" disciplines. In parallel, progress in deep neural networks are revolutionizing fields such as image recognition, natural language processing and, more broadly, AI. This course explores the exciting intersection between these two advances. The course will start with an introduction to deep learning and overview the relevant background in genomics and high-throughput biotechnology, focusing on the available data and their relevance. It will then cover the ongoing developments in deep learning (supervised, unsupervised and generative models) with the focus on the applications of these methods to biomedical data, which are beginning to produced dramatic results.
BIODS 248: Clinical Trial Design in the Age of Precision Medicine and Health, crosslisted as STATS 248 (Aut)
Instructors: Lai, Tze Leung
Advances in pan-omic technologies and system biology have led to novel therapies in the era of precision medicine. This course introduces innovative study designs to meet the challenges in designing confirmatory (pivotal) randomized controlled trials to evaluate these new treatments, including enrichment designs and master protocols, and examples of their recent successes in gaining regulatory approval of novel stroke and cancer therapies.
BIODS 260A: Workshop in Biostatistics, crosslisted as STATS 260A (Aut, Wtr, Spr, Sum)
Instructors: Palacios, Julia; Sabatti, Chiara
Applications of statistical techniques to current problems in medical science. To receive credit for one or two units, a student must attend every workshop. To receive two units, in addition to attending every workshop, the student is required to write an acceptable one-page summary of two of the workshops, with choices made by the student.