DCFA_DMP uses a divergence-convergence multi-view feature augmentation framework with graph transformer learning to predict drug-microbe associations, reporting AUROC of 0.9894 on the MDAD dataset.
Gnaemda: microbe-drug associations prediction on graph normalized convolutional network
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A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction
DCFA_DMP uses a divergence-convergence multi-view feature augmentation framework with graph transformer learning to predict drug-microbe associations, reporting AUROC of 0.9894 on the MDAD dataset.