Investigation of model stacking for drug sensitivity prediction

Investigation of model stacking for drug sensitivity prediction

Abstract Background A significant problem in precision medicine is the prediction of drug sensitivity for individual cancer cell lines. Predictive models such as Random Forests have shown promising performance while predicting from individual genomic features such as gene expressions. However, acces...

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Bibliographic Details
Main Authors: Kevin Matlock, Carlos De Niz, Raziur Rahman, Souparno Ghosh, Ranadip Pal
Format: Article
Language:English
Published: BMC 2018-03-01
Series:BMC Bioinformatics
Subjects:
Drug sensitivity prediction
Stacking
Bias
Online Access:http://link.springer.com/article/10.1186/s12859-018-2060-2

Internet

http://link.springer.com/article/10.1186/s12859-018-2060-2

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