These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

164 related articles for article (PubMed ID: 39227405)

  • 21. DAEMDA: A Method with Dual-Channel Attention Encoding for miRNA-Disease Association Prediction.
    Dong B; Sun W; Xu D; Wang G; Zhang T
    Biomolecules; 2023 Oct; 13(10):. PubMed ID: 37892196
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Multi-view Multichannel Attention Graph Convolutional Network for miRNA-disease association prediction.
    Tang X; Luo J; Shen C; Lai Z
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 33963829
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Variational graph auto-encoders for miRNA-disease association prediction.
    Ding Y; Tian LP; Lei X; Liao B; Wu FX
    Methods; 2021 Aug; 192():25-34. PubMed ID: 32798654
    [TBL] [Abstract][Full Text] [Related]  

  • 24. SFGAE: a self-feature-based graph autoencoder model for miRNA-disease associations prediction.
    Ma M; Na S; Zhang X; Chen C; Xu J
    Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 36037084
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Multi-channel graph attention autoencoders for disease-related lncRNAs prediction.
    Sheng N; Huang L; Wang Y; Zhao J; Xuan P; Gao L; Cao Y
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35108355
    [TBL] [Abstract][Full Text] [Related]  

  • 26. NEMPD: a network embedding-based method for predicting miRNA-disease associations by preserving behavior and attribute information.
    Ji BY; You ZH; Chen ZH; Wong L; Yi HC
    BMC Bioinformatics; 2020 Sep; 21(1):401. PubMed ID: 32912137
    [TBL] [Abstract][Full Text] [Related]  

  • 27. HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction.
    Li Z; Wan L; Wang L; Wang W; Nie R
    Brief Bioinform; 2024 Jul; 25(5):. PubMed ID: 39175132
    [TBL] [Abstract][Full Text] [Related]  

  • 28. AMHMDA: attention aware multi-view similarity networks and hypergraph learning for miRNA-disease associations identification.
    Ning Q; Zhao Y; Gao J; Chen C; Li X; Li T; Yin M
    Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36907654
    [TBL] [Abstract][Full Text] [Related]  

  • 29. HGCLAMIR: Hypergraph contrastive learning with attention mechanism and integrated multi-view representation for predicting miRNA-disease associations.
    Ouyang D; Liang Y; Wang J; Li L; Ai N; Feng J; Lu S; Liao S; Liu X; Xie S
    PLoS Comput Biol; 2024 Apr; 20(4):e1011927. PubMed ID: 38652712
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Biolinguistic graph fusion model for circRNA-miRNA association prediction.
    Guo LX; Wang L; You ZH; Yu CQ; Hu ML; Zhao BW; Li Y
    Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38426324
    [TBL] [Abstract][Full Text] [Related]  

  • 31. PmDNE: Prediction of miRNA-Disease Association Based on Network Embedding and Network Similarity Analysis.
    Li J; Liu Y; Zhang Z; Liu B; Wang Y
    Biomed Res Int; 2020; 2020():6248686. PubMed ID: 33354569
    [TBL] [Abstract][Full Text] [Related]  

  • 32. MHCLMDA: multihypergraph contrastive learning for miRNA-disease association prediction.
    Peng W; He Z; Dai W; Lan W
    Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38243694
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Integration of pairwise neighbor topologies and miRNA family and cluster attributes for miRNA-disease association prediction.
    Xuan P; Wang D; Cui H; Zhang T; Nakaguchi T
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34634106
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Toward drug-miRNA resistance association prediction by positional encoding graph neural network and multi-channel neural network.
    Zhao C; Wang H; Qi W; Liu S
    Methods; 2022 Nov; 207():81-89. PubMed ID: 36167292
    [TBL] [Abstract][Full Text] [Related]  

  • 35. MHGTMDA: Molecular heterogeneous graph transformer based on biological entity graph for miRNA-disease associations prediction.
    Zou H; Ji B; Zhang M; Liu F; Xie X; Peng S
    Mol Ther Nucleic Acids; 2024 Mar; 35(1):102139. PubMed ID: 38384447
    [TBL] [Abstract][Full Text] [Related]  

  • 36. DF-MDA: An effective diffusion-based computational model for predicting miRNA-disease association.
    Li HY; You ZH; Wang L; Yan X; Li ZW
    Mol Ther; 2021 Apr; 29(4):1501-1511. PubMed ID: 33429082
    [TBL] [Abstract][Full Text] [Related]  

  • 37. A Semi-Supervised Learning Method for MiRNA-Disease Association Prediction Based on Variational Autoencoder.
    Ji C; Wang Y; Gao Z; Li L; Ni J; Zheng C
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(4):2049-2059. PubMed ID: 33735084
    [TBL] [Abstract][Full Text] [Related]  

  • 38. GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder.
    Li L; Wang YT; Ji CM; Zheng CH; Ni JC; Su YS
    PLoS Comput Biol; 2021 Dec; 17(12):e1009655. PubMed ID: 34890410
    [TBL] [Abstract][Full Text] [Related]  

  • 39. NGCICM: A Novel Deep Learning-Based Method for Predicting circRNA-miRNA Interactions.
    Ma Z; Kuang Z; Deng L
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(5):3080-3092. PubMed ID: 37027645
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Heterogeneous graph inference with range constrainted L
    Wang S; Liu T; Ren C; Zhao Y; Qiao S; Zhang Y; Pang S
    Comput Biol Chem; 2024 Jun; 110():108078. PubMed ID: 38677013
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.