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)

  • 1. A method for miRNA diffusion association prediction using machine learning decoding of multi-level heterogeneous graph Transformer encoded representations.
    Wen S; Liu Y; Yang G; Chen W; Wu H; Zhu X; Wang Y
    Sci Rep; 2024 Sep; 14(1):20490. PubMed ID: 39227405
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. NMCMDA: neural multicategory MiRNA-disease association prediction.
    Wang J; Li J; Yue K; Wang L; Ma Y; Li Q
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33778850
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Global-local aware Heterogeneous Graph Contrastive Learning for multifaceted association prediction in miRNA-gene-disease networks.
    Si Y; Huang Z; Fang Z; Yuan Z; Huang Z; Li Y; Wei Y; Wu F; Yao YF
    Brief Bioinform; 2024 Jul; 25(5):. PubMed ID: 39256197
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predicting miRNA-disease association via graph attention learning and multiplex adaptive modality fusion.
    Jin Z; Wang M; Tang C; Zheng X; Zhang W; Sha X; An S
    Comput Biol Med; 2024 Feb; 169():107904. PubMed ID: 38181611
    [TBL] [Abstract][Full Text] [Related]  

  • 6. SGLMDA: A Subgraph Learning-Based Method for miRNA-Disease Association Prediction.
    Ji C; Yu N; Wang Y; Ni J; Zheng C
    IEEE/ACM Trans Comput Biol Bioinform; 2024; 21(5):1191-1201. PubMed ID: 38446654
    [TBL] [Abstract][Full Text] [Related]  

  • 7. PDMDA: predicting deep-level miRNA-disease associations with graph neural networks and sequence features.
    Yan C; Duan G; Li N; Zhang L; Wu FX; Wang J
    Bioinformatics; 2022 Apr; 38(8):2226-2234. PubMed ID: 35150255
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Synchronous Mutual Learning Network and Asynchronous Multi-Scale Embedding Network for miRNA-Disease Association Prediction.
    Sun W; Zhang P; Zhang W; Xu J; Huang Y; Li L
    Interdiscip Sci; 2024 Sep; 16(3):532-553. PubMed ID: 38310628
    [TBL] [Abstract][Full Text] [Related]  

  • 9. PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs.
    Chen L; Gu J; Zhou B
    Brief Bioinform; 2024 Jul; 25(5):. PubMed ID: 39154195
    [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 miRNA-Disease Associations Based On Multi-View Variational Graph Auto-Encoder With Matrix Factorization.
    Ding Y; Lei X; Liao B; Wu FX
    IEEE J Biomed Health Inform; 2022 Jan; 26(1):446-457. PubMed ID: 34111017
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks.
    Xuan P; Sun H; Wang X; Zhang T; Pan S
    Int J Mol Sci; 2019 Jul; 20(15):. PubMed ID: 31349729
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predicting MiRNA-disease associations by multiple meta-paths fusion graph embedding model.
    Zhang L; Liu B; Li Z; Zhu X; Liang Z; An J
    BMC Bioinformatics; 2020 Oct; 21(1):470. PubMed ID: 33087064
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A graph auto-encoder model for miRNA-disease associations prediction.
    Li Z; Li J; Nie R; You ZH; Bao W
    Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 34293850
    [TBL] [Abstract][Full Text] [Related]  

  • 15. MGCNSS: miRNA-disease association prediction with multi-layer graph convolution and distance-based negative sample selection strategy.
    Tian Z; Han C; Xu L; Teng Z; Song W
    Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38622356
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predicting miRNA-disease associations based on PPMI and attention network.
    Xie X; Wang Y; He K; Sheng N
    BMC Bioinformatics; 2023 Mar; 24(1):113. PubMed ID: 36959547
    [TBL] [Abstract][Full Text] [Related]  

  • 17. MDformer: A transformer-based method for predicting miRNA-Disease associations using multi-source feature fusion and maximal meta-path instances encoding.
    Dong B; Sun W; Xu D; Wang G; Zhang T
    Comput Biol Med; 2023 Dec; 167():107585. PubMed ID: 37890424
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Predicting miRNA-disease association from heterogeneous information network with GraRep embedding model.
    Ji BY; You ZH; Cheng L; Zhou JR; Alghazzawi D; Li LP
    Sci Rep; 2020 Apr; 10(1):6658. PubMed ID: 32313121
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Multi-Kernel Graph Attention Deep Autoencoder for MiRNA-Disease Association Prediction.
    Jiao CN; Zhou F; Liu BM; Zheng CH; Liu JX; Gao YL
    IEEE J Biomed Health Inform; 2024 Feb; 28(2):1110-1121. PubMed ID: 38055359
    [TBL] [Abstract][Full Text] [Related]  

  • 20. EOESGC: predicting miRNA-disease associations based on embedding of embedding and simplified graph convolutional network.
    Pang S; Zhuang Y; Wang X; Wang F; Qiao S
    BMC Med Inform Decis Mak; 2021 Nov; 21(1):319. PubMed ID: 34789236
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.