  Personalized drug response has received public awareness in recent years. How
to combine gene test result and drug sensitivity records is regarded as
essential in the real-world implementation. Research articles are good sources
to train machine predicting, inference, reasoning, etc. In this project, we
combine the patterns mined from biological research articles and categorical
data to construct a drug-gene interaction network. Then we use the cell line
experimental records on gene and drug sensitivity to estimate the edge
embeddings in the network. Our model provides white-box explainable predictions
of drug response based on gene records, which achieves 94.74% accuracy in
binary drug sensitivity prediction task.
