Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas
Abstract
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 …
Keywords
Tumor
National Center for Biotechnology Information
NCBI
NLM
MEDLINE
gene expression regulation
humans
pubmed abstract
nih
national institutes of health
national library of medicine
research support
non-u.s. gov't
N.I.H.
Extramural
machine learning*
cell line
neoplasms / genetics*
genome
human
neoplasms / metabolism
signal transduction
neoplastic
pmid:29617658
pmc5918694
doi:10.1016/j.celrep.2018.03.046
gregory p way
francisco sanchez-vega
casey s greene
ras proteins / genetics*
ras proteins / metabolism
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118027
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