Predicting tumor cell line response to drug pairs with deep learning. - Fangfang Xia; Maulik Shukla; Thomas S. Brettin; Cristina Garcia-Cardona; Judith D. Cohn; Jonathan E. Allen; Sergei Maslov; Susan L. Holbeck; James H. Doroshow; Yvonne A. Evrard; Eric A. Stahlberg; Rick L. Stevens (BMC Bioinform., 2018)

Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response. - Yitan Zhu; Thomas S. Brettin; Yvonne A. Evrard; Alexander Partin; Fangfang Xia; Maulik Shukla; Hyun Seung Yoo; James H. Doroshow; Rick Stevens (CoRR, 2020)

Learning curves for drug response prediction in cancer cell lines. - Alexander Partin; Thomas S. Brettin; Yvonne A. Evrard; Yitan Zhu; Hyun Seung Yoo; Fangfang Xia; Songhao Jiang; Austin Clyde; Maulik Shukla; Michael Fonstein; James H. Doroshow; Rick L. Stevens (BMC Bioinform., 2021)

A cross-study analysis of drug response prediction in cancer cell lines. - Fangfang Xia; Jonathan E. Allen; Prasanna Balaprakash; Thomas S. Brettin; Cristina Garcia-Cardona; Austin Clyde; Judith D. Cohn; James H. Doroshow; Xiaotian Duan; Veronika Dubinkina; Yvonne A. Evrard; Ya Ju Fan; et al. (Briefings Bioinform., 2022)

TPWshiny: an interactive R/Shiny app to explore cell line transcriptional responses to anti-cancer drugs. - Peter Zhang; Alida Palmisano; Ravindra Kumar; Ming-Chung Li; James H. Doroshow; Yingdong Zhao (Bioinform., 2022)

Entropy-Based Regularization on Deep Learning Models for Anti-Cancer Drug Response Prediction. - Oleksandr Narykov; Yitan Zhu; Thomas S. Brettin; Yvonne A. Evrard; Alexander Partin; Maulik Shukla; Priyanka Vasanthakumari; James H. Doroshow; Rick Stevens (SC Workshops, 2023)

Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting. - Oleksandr Narykov; Yitan Zhu; Thomas S. Brettin; Yvonne A. Evrard; Alexander Partin; Fangfang Xia; Maulik Shukla; Priyanka Vasanthakumari; James H. Doroshow; Rick L. Stevens (Briefings Bioinform., 2025)