AI RESEARCH
drGT: Attention-Guided Gene Assessment of Drug Response Utilizing a Drug-Cell-Gene Heterogeneous Network
arXiv CS.LG
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ArXi:2405.08979v3 Announce Type: replace A challenge in drug response prediction is result interpretation compared to established knowledge. drGT is a graph deep learning model that predicts sensitivity and aids in biomarker identification using attention coefficients (ACs). drGT leverages a heterogeneous graph composed of relationships drawn from drugs, genes, and cell line responses. The model is trained and evaluated using major benchmark datasets: Sanger GDSC, NCI60, and Broad CTRP, which cover a wide range of drugs and cancer cell lines.