Adaptive deep propagation graph neural network for predicting miRNA-disease associations.

Briefings in functional genomics(2023)

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摘要
Experiments on human microRNA disease database v3.0 dataset show that ADPMDA achieves the mean AUC value of 94.75% under 5-fold cross-validation. We further conduct case studies on the esophageal neoplasm, lung neoplasms and lymphoma to confirm the effectiveness of our proposed model, and 49, 49, 47 of the top 50 predicted miRNAs associated with these diseases are confirmed, respectively. These results demonstrate the effectiveness and superiority of our model in predicting miRNA-disease associations.
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关键词
attention mechanism,deep learning,graph neural networks,heterogeneous graph,miRNA–disease associations,propagation
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