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Graph regularized L2, 1-nonnegative matrix factorization for miRNA-disease association prediction.

, , , , and . BMC Bioinform., 21 (1): 61 (2020)

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SCMFMDA: Predicting microRNA-disease associations based on similarity constrained matrix factorization., , , , , , and . PLoS Comput. Biol., (2021)GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder., , , , , and . PLoS Comput. Biol., (2021)GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest., , , and . Briefings Bioinform., (2021)Extra Trees Method for Predicting LncRNA-Disease Association Based On Multi-Layer Graph Embedding Aggregation., , , , , and . IEEE ACM Trans. Comput. Biol. Bioinform., 19 (6): 3171-3178 (2022)MiRNA-disease association prediction via hypergraph learning based on high-dimensionality features., , , , and . BMC Medical Informatics Decis. Mak., 21 (1): 133 (2021)Robust Visual Tracking Using Hierarchical Vision Transformer with Shifted Windows Multi-Head Self-Attention., , , , and . IEICE Trans. Inf. Syst., 107 (1): 161-164 (January 2024)Graph regularized L2, 1-nonnegative matrix factorization for miRNA-disease association prediction., , , , and . BMC Bioinform., 21 (1): 61 (2020)AEMDA: inferring miRNA-disease associations based on deep autoencoder., , , , , and . Bioinform., 37 (1): 66-72 (2021)Cell Classification Based on Stacked Autoencoder for Single-Cell RNA Sequencing., , , , , and . ICIC (2), volume 13394 of Lecture Notes in Computer Science, page 245-259. Springer, (2022)RWRNCP: Random Walking with Restart Based Network Consistency Projection for Predicting miRNA-Disease Association., , , , , and . ICIC (3), volume 12838 of Lecture Notes in Computer Science, page 522-535. Springer, (2021)