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Description
Algorithms for Survival Analysis of Mutations in Cancer
Deriving clinical utility from large genomic datasets requires the identification of statistically significant associations between genomic measurements and a clinical phenotype. An important instance of this problem is to identify genetic variants that distinguish patients with different survival time following diagnosis or treatment. I will present some of the algorithmic problems that arise in the identification of mutations associated with survival in cancer.
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