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Convolution Neural Networks Using Deep Matrix Factorization for Predicting Circrna-Disease Association.

, , , , , and . IEEE ACM Trans. Comput. Biol. Bioinform., 20 (1): 277-284 (January 2023)

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GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest., , , and . Briefings Bioinform., (2021)GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder., , , , , and . PLoS Comput. Biol., (2021)SCMFMDA: Predicting microRNA-disease associations based on similarity constrained matrix factorization., , , , , , and . PLoS Comput. Biol., (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)Convolution Neural Networks Using Deep Matrix Factorization for Predicting Circrna-Disease Association., , , , , and . IEEE ACM Trans. Comput. Biol. Bioinform., 20 (1): 277-284 (January 2023)An Efficient Drug-Drug Interactions Prediction Technology for Molecularly Intelligent Manufacturing., , and . CoRR, (2022)GCNMFCDA: A Method Based on Graph Convolutional Network and Matrix Factorization for Predicting circRNA-Disease Associations., , , , , and . ICIC (2), volume 13394 of Lecture Notes in Computer Science, page 166-180. Springer, (2022)HGMDA: HyperGraph for Predicting MiRNA-Disease Association., , , , , and . ICIC (2), volume 11644 of Lecture Notes in Computer Science, page 265-271. Springer, (2019)A New Method Based on Matrix Completion and Non-Negative Matrix Factorization for Predicting Disease-Associated miRNAs., , , , , and . IEEE ACM Trans. Comput. Biol. Bioinform., 19 (2): 763-772 (2022)Predicting miRNA-Disease Association Based on Improved Graph Regression., , , , , and . IEEE ACM Trans. Comput. Biol. Bioinform., 19 (6): 3604-3613 (2022)