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Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitors

2020-11-15

Abstract excerpt

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This study utilizes machine learning to derive multi-gene expression signatures that predict individual patient responses to specific tyrosine kinase inhibitors, including erlotinib, gefitinib, sorafenib, sunitinib, lapatinib and imatinib. Support Vector Machine learning was used to train mathematical m...

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Identifiers and source

Literature Corpus work
28447321-aa99-5f60-b1b2-da5da4d77bb2
DOI
10.1101/2020.11.13.381798
Open publication

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Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitorsDOI 10.1101/2020.11.13.381798
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