Source code and data for "GraphCDR: A graph neural network method with contrastive learning for cancer drug response prediction"
- Python >= 3.6
- PyTorch >= 1.4
- PyTorch Geometry >= 1.6
- hickle >= 3.4
- DeepChem >= 2.4
- RDkit >= 2020.09
- please unzip the file: data/Drug/drug_graph_feat.zip first.
- python graphCDR.py <parameters>
- python graphCDR-ccle.py <parameters>
As GDSC database only measured IC50 of part cell line and drug pairs. We applied GraphCDR to predicted the missing types of responses. The predicted results can be find at data/Case study (missing pairs).xlsx