We're developing databases and web applications to empower the scientific community in their pharmacogenomic analysis of cancer model systems.

Web Apps
Orchestrate and reproduce pharmacogenomic data processing
Explore multi-layer similarities between chemical compounds
Investigate the pathways triggered by exposure to toxic substances
Visualize and analyze xenographic pharmacogenomic data
Mine pharmacogenomic profiles of cancer cell lines treated with single agent
Explore synergistic drug combinations in cancer cell lines
Authenticate genotype and stability of cancer cell lines
Check quality-assurance for radiotherapy target delineation
Quantify therapy response to drug treatment in xenografts
Investigate predictive and prognostic values of genes. Predict patient response to ICB therapy
Core infrastructure which serve as the foundation for other Gx packages
Analysis of large-scale pharmacogenomic datasets
Biomarker discovery for Radiation Treatment using in vitro models
Analysis of large-scale toxicogenomic datasets
Clustering of Genomic REgions Analysis Method
Parallelized minimum Redundancy, Maximum Relevance ensemble feature selection
Similarity Identification in Gene Expression
R implementation of Logic Optimization for Binary Input to Continuous Output
XEnograft Visualization and Analysis
Pancreatic Ductal Adenocarcinoma Tool-Kit
Computation of Gene Expression-Based Signatures in Breast Cancer
Assessment and Comparison for Performance of Risk Prediction (Survival) Models
Parallelized minimum Redundancy, Maximum Relevance ensemble feature selection
Modelling tumor growth curves using Kullback-Leibler divergence and Gaussian processes