Motivation Due to cancer heterogeneity, the therapeutic effect may not be the same when a
cohort of patients of the same cancer type receive the same treatment. The anticancer drug …

Patients with the same cancer types may present different genomic features and therefore
have different drug sensitivities. Accordingly, correctly predicting patients' responses to the …

Genomic profiles of cancer patients such as gene expression have become a major source
to predict responses to drugs in the era of personalized medicine. As large-scale drug …

Drug response prediction in cancer cell lines is of great significance in personalized
medicine. In this study, we propose GADRP, a cancer drug response prediction model …

Motivation Accurate prediction of cancer drug response (CDR) is challenging due to the
uncertainty of drug efficacy and heterogeneity of cancer patients. Strong evidences have …

Predicting the response of a cancer cell line to a therapeutic drug is an important topic in
modern oncology that can help personalized treatment for cancers. Although numerous …

Background Drug resistance is a critical obstacle in cancer therapy. Discovering cancer drug
response is important to improve anti-cancer drug treatment and guide anti-cancer drug …

Background: Drug response prediction is an important problem in computational
personalized medicine. Many machine-learning-based methods, especially deep learning …

Different cancer patients may respond differently to cancer treatment due to the
heterogeneity of cancer. It is an urgent task to develop an efficient computational method to …

Precision medicine is devoted to discovering personalized therapy for complex and difficult
diseases like cancer. Many machine learning approaches have been developed for drug …