SFGAE: a self-feature-based graph autoencoder model for miRNA-disease associations prediction
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DOI: 10.1093/bib/bbac340
Abstract: Increasing evidence has suggested that microRNAs (miRNAs) are important biomarkers of various diseases. Numerous graph neural network (GNN) models have been proposed for predicting miRNA-disease associations. However, the existing GNN-based methods have over-smoothing issue-the learned… read more here.
Keywords: disease; feature embeddings; self feature; disease associations ... See more keywords