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JFCR39, a panel of 39 human cancer cell lines, and its application in the discovery and development of anticancer drugs.
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Development of the Histoculture Drug Response Assay (HDRA).
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Drug discovery strategies in the field of tumor energy metabolism: Limitations by metabolic flexibility and metabolic resistance to chemotherapy.
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Computational identification of multi-omic correlates of anticancer therapeutic response.
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DISIS: prediction of drug response through an iterative sure independence screening.
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Dual-Layer Strengthened Collaborative Topic Regression Modeling for Predicting Drug Sensitivity.
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Deep generative neural network for accurate drug response imputation.
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Impact of between-tissue differences on pan-cancer predictions of drug sensitivity.
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Anticancer drug synergy prediction in understudied tissues using transfer learning.
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Tissue-guided LASSO for prediction of clinical drug response using preclinical samples.
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Revisiting inconsistency in large pharmacogenomic studies.
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A Biobank of Breast Cancer Explants with Preserved Intra-tumor Heterogeneity to Screen Anticancer Compounds.
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Screening out irrelevant cell-based models of disease.
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Integrated Patient-Derived Models Delineate Individualized Therapeutic Vulnerabilities of Pancreatic Cancer.
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Assessment of pharmacogenomic agreement.
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A Landscape of Pharmacogenomic Interactions in Cancer.
Cell. 2016 Jul 28;166(3):740-754. doi: 10.1016/j.cell.2016.06.017. Epub 2016 Jul 7.
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Standards for Cell Line Authentication and Beyond.
PLoS Biol. 2016 Jun 14;14(6):e1002476. doi: 10.1371/journal.pbio.1002476. eCollection 2016 Jun.
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Reproducible pharmacogenomic profiling of cancer cell line panels.
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