AITL: Adversarial Inductive Transfer Learning with input and output space adaptation for pharmacogenomics

Dr.VAE: Improving drug response prediction via modeling of drug perturbation effects

(2019) Ladislav Rampášek et al.   BIOINFORMATICS

MOLI: multi-omics late integration with deep neural networks for drug response prediction

(2019) Hossein Sharifi-Noghabi et al.   BIOINFORMATICS

PRECISE: a domain adaptation approach to transfer predictors of drug response from pre-clinical models to tumors

(2019) Soufiane Mourragui et al.   BIOINFORMATICS

A Deep Learning Framework for Predicting Response to Therapy in Cancer

(2019) Theodore Sakellaropoulos et al.   Cell Reports

Discovering novel pharmacogenomic biomarkers by imputing drug response in cancer patients from large genomics studies

(2017) Paul Geeleher et al.   GENOME RESEARCH

Precision Oncology beyond Targeted Therapy: Combining Omics Data with Machine Learning Matches the Majority of Cancer Cells to Effective Therapeutics

(2017) Michael Q. Ding et al.   MOLECULAR CANCER RESEARCH

PharmacoDB: an integrative database for mining in vitro anticancer drug screening studies

(2017) Petr Smirnov et al.   NUCLEIC ACIDS RESEARCH

Evaluating the molecule-based prediction of clinical drug responses in cancer

(2016) Zijian Ding et al.   BIOINFORMATICS

A Landscape of Pharmacogenomic Interactions in Cancer

(2016) Francesco Iorio et al.   CELL

RECIST 1.1—Update and clarification: From the RECIST committee

(2016) Lawrence H. Schwartz et al.   EUROPEAN JOURNAL OF CANCER

High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response

(2015) Hui Gao et al.   NATURE MEDICINE

Gene expression profile alone is inadequate in predicting complete response in multiple myeloma

(2014) S B Amin et al.   LEUKEMIA

Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines

(2014) Paul Geeleher et al.   GENOME BIOLOGY

The Cancer Genome Atlas Pan-Cancer analysis project

(2013) John N Weinstein et al.   NATURE GENETICS

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

(2012) Jordi Barretina et al.   NATURE

BAD Phosphorylation Determines Ovarian Cancer Chemosensitivity and Patient Survival

(2011) D. C. Marchion et al.   CLINICAL CANCER RESEARCH

A Genomic Predictor of Response and Survival Following Taxane-Anthracycline Chemotherapy for Invasive Breast Cancer

(2011) Christos Hatzis   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies

(2011) Brian D. Lehmann et al.   JOURNAL OF CLINICAL INVESTIGATION

Identification of Markers of Taxane Sensitivity Using Proteomic and Genomic Analyses of Breast Tumors from Patients Receiving Neoadjuvant Paclitaxel and Radiation

(2010) J. A. Bauer et al.   CLINICAL CANCER RESEARCH

Efficacy of Neoadjuvant Cisplatin in Triple-Negative Breast Cancer

(2010) Daniel P. Silver et al.   JOURNAL OF CLINICAL ONCOLOGY

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING