Application of transfer learning for cancer drug sensitivity prediction

Extracting a low-dimensional description of multiple gene expression datasets reveals a potential driver for tumor-associated stroma in ovarian cancer

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Bias corrections for Random Forest in regression using residual rotation

(2015) Jongwoo Song   Journal of the Korean Statistical Society

Inconsistency in large pharmacogenomic studies

(2013) Benjamin Haibe-Kains et al.   NATURE

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

(2012) Jordi Barretina et al.   NATURE

Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells

(2012) Wanjuan Yang et al.   NUCLEIC ACIDS RESEARCH

Bias-corrected random forests in regression

(2011) Guoyi Zhang et al.   JOURNAL OF APPLIED STATISTICS

A Survey on Transfer Learning

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