PDXGEM data download page
All PDXGEM biomarkers, Random Forest variable importance, Prediction scores, processed gene expression data, and clinical data can be download here. Please click the drug name of interest with link below.
Kim, Y. CGNA: a strategy for anti-cancer drug response prediction based on pharmacogenomic data of heterogeneous cancer cell lines with application to ovarian cancer (Under revision)
- Kim Y et al. (2020) PDXGEM: Patient-Derived Tumor Xenograft based Gene Expression Model for Predicting Clinical Response to Anticancer Therapy in Cancer Patients, BMC Bioinformatics (in press; preprint available at
- Chen et al. (2018) Single drug biomarker prediction for ER- breast cancer outcome from chemotherapy, Endocrine-Related Cancer, 25:6, 595-605
- Kim et al. (2017) CONCORD biomarker prediction for novel drug introduction to different cancer types, Oncotarget, 9(1):1091-1106
- Kim et al. (2014) Restrospective analysis of survival improvement by molecular biomarker-based personalized chemotherapy for recurrent ovarian cancer, PLOS one, 2014, v9 (2) e86532
- Costello et al. (2014) A community effort to assess and improve drug sensitivity prediction algorithms, Nature Biotechnology, 32(12), 1202-1212
NOTE: This space will contain the previous publications by the site authors.