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Potential circRNA-Disease Association Prediction Using DeepWalk and Nonnegative Matrix Factorization.

, , , , , and . IEEE ACM Trans. Comput. Biol. Bioinform., 20 (5): 3154-3162 (September 2023)

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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)Optimizing Berth-quay Crane Allocation considering Economic Factors Using Chaotic Quantum SSA., , , , and . Appl. Artif. Intell., (2022)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)Potential circRNA-Disease Association Prediction Using DeepWalk and Nonnegative Matrix Factorization., , , , , and . IEEE ACM Trans. Comput. Biol. Bioinform., 20 (5): 3154-3162 (September 2023)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 End-to-End Deep Hybrid Autoencoder Based Method for Single-Cell RNA-Seq Data Analysis., , , , and . IEEE ACM Trans. Comput. Biol. Bioinform., 20 (6): 3889-3900 (November 2023)scGCC: Graph Contrastive Clustering With Neighborhood Augmentations for scRNA-Seq Data Analysis., , , , and . IEEE J. Biomed. Health Informatics, 27 (12): 6133-6143 (December 2023)MELPMDA: A New Method Based on Matrix Enhancement and Label Propagation for Predicting miRNA-Disease Association., , , , and . ICIC (3), volume 12838 of Lecture Notes in Computer Science, page 536-548. Springer, (2021)