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 *

226 related articles for article (PubMed ID: 35590258)

  • 1. MAGCNSE: predicting lncRNA-disease associations using multi-view attention graph convolutional network and stacking ensemble model.
    Liang Y; Zhang ZQ; Liu NN; Wu YN; Gu CL; Wang YL
    BMC Bioinformatics; 2022 May; 23(1):189. PubMed ID: 35590258
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Learning global dependencies and multi-semantics within heterogeneous graph for predicting disease-related lncRNAs.
    Xuan P; Wang S; Cui H; Zhao Y; Zhang T; Wu P
    Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 36088549
    [TBL] [Abstract][Full Text] [Related]  

  • 3. LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks.
    Zhang B; Wang H; Ma C; Huang H; Fang Z; Qu J
    BMC Bioinformatics; 2024 Oct; 25(1):332. PubMed ID: 39407120
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Graph Convolutional Network and Convolutional Neural Network Based Method for Predicting lncRNA-Disease Associations.
    Xuan P; Pan S; Zhang T; Liu Y; Sun H
    Cells; 2019 Aug; 8(9):. PubMed ID: 31480350
    [TBL] [Abstract][Full Text] [Related]  

  • 5. CNNDLP: A Method Based on Convolutional Autoencoder and Convolutional Neural Network with Adjacent Edge Attention for Predicting lncRNA-Disease Associations.
    Xuan P; Sheng N; Zhang T; Liu Y; Guo Y
    Int J Mol Sci; 2019 Aug; 20(17):. PubMed ID: 31480319
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Attentional multi-level representation encoding based on convolutional and variance autoencoders for lncRNA-disease association prediction.
    Sheng N; Cui H; Zhang T; Xuan P
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32444875
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Multi-task prediction-based graph contrastive learning for inferring the relationship among lncRNAs, miRNAs and diseases.
    Sheng N; Wang Y; Huang L; Gao L; Cao Y; Xie X; Fu Y
    Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37529914
    [TBL] [Abstract][Full Text] [Related]  

  • 8. MCA-Net: Multi-Feature Coding and Attention Convolutional Neural Network for Predicting lncRNA-Disease Association.
    Zhang Y; Ye F; Gao X
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(5):2907-2919. PubMed ID: 34283719
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Prediction of lncRNA and disease associations based on residual graph convolutional networks with attention mechanism.
    Wang S; Qiao J; Feng S
    Sci Rep; 2024 Mar; 14(1):5185. PubMed ID: 38431702
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Graph Triple-Attention Network for Disease-Related LncRNA Prediction.
    Xuan P; Zhan L; Cui H; Zhang T; Nakaguchi T; Zhang W
    IEEE J Biomed Health Inform; 2022 Jun; 26(6):2839-2849. PubMed ID: 34813484
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. LDAPred: A Method Based on Information Flow Propagation and a Convolutional Neural Network for the Prediction of Disease-Associated lncRNAs.
    Xuan P; Jia L; Zhang T; Sheng N; Li X; Li J
    Int J Mol Sci; 2019 Sep; 20(18):. PubMed ID: 31510011
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Heterogeneous graph attention network based on meta-paths for lncRNA-disease association prediction.
    Zhao X; Zhao X; Yin M
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34585231
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A machine learning framework that integrates multi-omics data predicts cancer-related LncRNAs.
    Yuan L; Zhao J; Sun T; Shen Z
    BMC Bioinformatics; 2021 Jun; 22(1):332. PubMed ID: 34134612
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting lncRNA-disease associations using multiple metapaths in hierarchical graph attention networks.
    Yao D; Deng Y; Zhan X; Zhan X
    BMC Bioinformatics; 2024 Jan; 25(1):46. PubMed ID: 38287236
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Specific topology and topological connection sensitivity enhanced graph learning for lncRNA-disease association prediction.
    Xuan P; Bai H; Cui H; Zhang X; Nakaguchi T; Zhang T
    Comput Biol Med; 2023 Sep; 164():107265. PubMed ID: 37531860
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Learning Association Characteristics by Dynamic Hypergraph and Gated Convolution Enhanced Pairwise Attributes for Prediction of Disease-Related lncRNAs.
    Xuan P; Lu S; Cui H; Wang S; Nakaguchi T; Zhang T
    J Chem Inf Model; 2024 Apr; 64(8):3569-3578. PubMed ID: 38523267
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Fully connected autoencoder and convolutional neural network with attention-based method for inferring disease-related lncRNAs.
    Xuan P; Gong Z; Cui H; Li B; Zhang T
    Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35362511
    [TBL] [Abstract][Full Text] [Related]  

  • 19. GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest.
    Wu QW; Xia JF; Ni JC; Zheng CH
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33415333
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Graph embedding ensemble methods based on the heterogeneous network for lncRNA-miRNA interaction prediction.
    Zhao C; Qiu Y; Zhou S; Liu S; Zhang W; Niu Y
    BMC Genomics; 2020 Dec; 21(Suppl 13):867. PubMed ID: 33334307
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.