A statistical framework for assessing pharmacological responses and biomarkers using uncertainty estimates

A statistical framework for assessing pharmacological responses and biomarkers using uncertainty estimates

High-throughput testing of drugs across molecular-characterised cell lines can identify candidate treatments and discover biomarkers. However, the cells’ response to a drug is typically quantified by a summary statistic from a best-fit dose-response curve, whilst neglecting the uncertainty of the cu...

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Bibliographic Details
Main Authors: Dennis Wang, James Hensman, Ginte Kutkaite, Tzen S Toh, Ana Galhoz, GDSC Screening Team, Jonathan R Dry, Julio Saez-Rodriguez, Mathew J Garnett, Michael P Menden, Frank Dondelinger
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2020-12-01
Series:eLife
Subjects:
pharmacogenomics
biomarkers
machine learning
drug prediction
statistical inference
uncertainty estimation
Online Access:https://elifesciences.org/articles/60352

Internet

https://elifesciences.org/articles/60352

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