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The acceleration of data acquisition and the availability of increasing amounts of both genetic and functional data are changing the face of biomedical research. Computational approaches can take advantage of these data and bring the promise of improved understanding and treatment of cancer. I will describe some approaches that leverage multiple data types and emphasize the use of more biologically interpretable models to determine the underlying biological mechanisms of specific tumor subtypes, to stratify patients according to their relative risks of relapse, and to identify candidate compounds for new treatments. I’ll focus on our application of these methods to Medulloblastoma, one of the most common pediatric brain tumors, and our efforts to translate them into the clinic.

Department:  Biomedical Data Sciences Department

Contact: Pornprang Plangsrisakul | 6507215338 | pplangs@stanford.edu

Presenter(s):

• Jill Mesirov, PhD Assoc. Vice Chancellor for Computational Health Science

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