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 *

127 related articles for article (PubMed ID: 38872515)

  • 1. HRGCNLDA: Forecasting of lncRNA-disease association based on hierarchical refinement graph convolutional neural network.
    Peng L; Yang Y; Yang C; Li Z; Cheong N
    Math Biosci Eng; 2024 Feb; 21(4):4814-4834. PubMed ID: 38872515
    [TBL] [Abstract][Full Text] [Related]  

  • 2. gGATLDA: lncRNA-disease association prediction based on graph-level graph attention network.
    Wang L; Zhong C
    BMC Bioinformatics; 2022 Jan; 23(1):11. PubMed ID: 34983363
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. 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]  

  • 5. 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]  

  • 6. Predicting lncRNA-disease associations based on heterogeneous graph convolutional generative adversarial network.
    Lu Z; Zhong H; Tang L; Luo J; Zhou W; Liu L
    PLoS Comput Biol; 2023 Nov; 19(11):e1011634. PubMed ID: 38019786
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Heterogeneous graph neural network for lncRNA-disease association prediction.
    Shi H; Zhang X; Tang L; Liu L
    Sci Rep; 2022 Oct; 12(1):17519. PubMed ID: 36266433
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. 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]  

  • 11. 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]  

  • 12. 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]  

  • 13. GCNFORMER: graph convolutional network and transformer for predicting lncRNA-disease associations.
    Yao D; Li B; Zhan X; Zhan X; Yu L
    BMC Bioinformatics; 2024 Jan; 25(1):5. PubMed ID: 38166659
    [TBL] [Abstract][Full Text] [Related]  

  • 14. IDSSIM: an lncRNA functional similarity calculation model based on an improved disease semantic similarity method.
    Fan W; Shang J; Li F; Sun Y; Yuan S; Liu JX
    BMC Bioinformatics; 2020 Jul; 21(1):339. PubMed ID: 32736513
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A random forest based computational model for predicting novel lncRNA-disease associations.
    Yao D; Zhan X; Zhan X; Kwoh CK; Li P; Wang J
    BMC Bioinformatics; 2020 Mar; 21(1):126. PubMed ID: 32216744
    [TBL] [Abstract][Full Text] [Related]  

  • 16. MVGCNMDA: Multi-view Graph Augmentation Convolutional Network for Uncovering Disease-Related Microbes.
    Hua M; Yu S; Liu T; Yang X; Wang H
    Interdiscip Sci; 2022 Sep; 14(3):669-682. PubMed ID: 35428964
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Graph Convolutional Auto-Encoders for Predicting Novel lncRNA-Disease Associations.
    Silva ABOV; Spinosa EJ
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(4):2264-2271. PubMed ID: 33819159
    [TBL] [Abstract][Full Text] [Related]  

  • 18. LncDisAP: a computation model for LncRNA-disease association prediction based on multiple biological datasets.
    Wang Y; Juan L; Peng J; Zang T; Wang Y
    BMC Bioinformatics; 2019 Dec; 20(Suppl 16):582. PubMed ID: 31787106
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Node-adaptive graph Transformer with structural encoding for accurate and robust lncRNA-disease association prediction.
    Li G; Bai P; Liang C; Luo J
    BMC Genomics; 2024 Jan; 25(1):73. PubMed ID: 38233788
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 7.