Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information.

Abstract excerpt

BACKGROUND: High-throughput technology allows for genome-wide measurements at different molecular levels for the same patient, e.g. single nucleotide polymorphisms (SNPs) and gene expression. Correspondingly, it might be beneficial to also integrate complementary information from different molecular levels when building multivariable risk prediction models for a clinical endpoint, such as treatment response or...

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