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Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas

1 Apr 2018

Abstract excerpt

Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these "hidden responders" may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq, copy...

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PMID: 29617658
DOI: 10.1016/j.celrep.2018.03.046

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