BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

120 related articles for article (PubMed ID: 36110314)

  • 1. Corrigendum: Predicting multiple types of associations between miRNAs and diseases based on graph regularized weighted tensor decomposition.
    Ouyang D; Miao R; Wang J; Liu X; Xie S; Ai N; Dang Q; Liang Y
    Front Bioeng Biotechnol; 2022; 10():1006237. PubMed ID: 36110314
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Predicting Multiple Types of Associations Between miRNAs and Diseases Based on Graph Regularized Weighted Tensor Decomposition.
    Ouyang D; Miao R; Wang J; Liu X; Xie S; Ai N; Dang Q; Liang Y
    Front Bioeng Biotechnol; 2022; 10():911769. PubMed ID: 35910021
    [TBL] [Abstract][Full Text] [Related]  

  • 3. MLRDFM: a multi-view Laplacian regularized DeepFM model for predicting miRNA-disease associations.
    Ding Y; Lei X; Liao B; Wu FX
    Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35323901
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Combining non-negative matrix factorization with graph Laplacian regularization for predicting drug-miRNA associations based on multi-source information fusion.
    Wang MN; Li Y; Lei LL; Ding DW; Xie XJ
    Front Pharmacol; 2023; 14():1132012. PubMed ID: 36817132
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Tensor decomposition with relational constraints for predicting multiple types of microRNA-disease associations.
    Huang F; Yue X; Xiong Z; Yu Z; Liu S; Zhang W
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32725161
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Graph regularized L
    Gao Z; Wang YT; Wu QW; Ni JC; Zheng CH
    BMC Bioinformatics; 2020 Feb; 21(1):61. PubMed ID: 32070280
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Hyperspectral Image Restoration Using Weighted Group Sparsity-Regularized Low-Rank Tensor Decomposition.
    Chen Y; He W; Yokoya N; Huang TZ
    IEEE Trans Cybern; 2020 Aug; 50(8):3556-3570. PubMed ID: 31484156
    [TBL] [Abstract][Full Text] [Related]  

  • 8. LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction.
    Chen X; Huang L
    PLoS Comput Biol; 2017 Dec; 13(12):e1005912. PubMed ID: 29253885
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Hyper-Laplacian regularized multi-view subspace clustering with low-rank tensor constraint.
    Lu GF; Yu QR; Wang Y; Tang G
    Neural Netw; 2020 May; 125():214-223. PubMed ID: 32146353
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Data Integration Using Tensor Decomposition for the Prediction of miRNA-Disease Associations.
    Luo J; Liu Y; Liu P; Lai Z; Wu H
    IEEE J Biomed Health Inform; 2022 May; 26(5):2370-2378. PubMed ID: 34748505
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Robust hypergraph regularized non-negative matrix factorization for sample clustering and feature selection in multi-view gene expression data.
    Yu N; Gao YL; Liu JX; Wang J; Shang J
    Hum Genomics; 2019 Oct; 13(Suppl 1):46. PubMed ID: 31639067
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A New Method Based on Matrix Completion and Non-Negative Matrix Factorization for Predicting Disease-Associated miRNAs.
    Gao Z; Wang YT; Wu QW; Li L; Ni JC; Zheng CH
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(2):763-772. PubMed ID: 32991287
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predicting multiple types of MicroRNA-disease associations based on tensor factorization and label propagation.
    Yu N; Liu ZP; Gao R
    Comput Biol Med; 2022 Jul; 146():105558. PubMed ID: 35525071
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. SGNNMD: signed graph neural network for predicting deregulation types of miRNA-disease associations.
    Zhang G; Li M; Deng H; Xu X; Liu X; Zhang W
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34875683
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Weighted Graph Regularized Sparse Brain Network Construction for MCI Identification.
    Yu R; Qiao L; Chen M; Lee SW; Fei X; Shen D
    Pattern Recognit; 2019 Jun; 90():220-231. PubMed ID: 31579345
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Image Representation and Learning With Graph-Laplacian Tucker Tensor Decomposition.
    Jiang B; Ding C; Tang J; Luo B
    IEEE Trans Cybern; 2019 Apr; 49(4):1417-1426. PubMed ID: 29994464
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Predicting miRNA-Disease Associations From miRNA-Gene-Disease Heterogeneous Network With Multi-Relational Graph Convolutional Network Model.
    Peng W; Che Z; Dai W; Wei S; Lan W
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(6):3363-3375. PubMed ID: 35776822
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Corrigendum: A guide to conquer the biological network era using graph theory.
    Koutrouli M; Karatzas E; Paez-Espino D; Pavlopoulos GA
    Front Bioeng Biotechnol; 2023; 11():1182500. PubMed ID: 37064232
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Dual-network sparse graph regularized matrix factorization for predicting miRNA-disease associations.
    Gao MM; Cui Z; Gao YL; Liu JX; Zheng CH
    Mol Omics; 2019 Apr; 15(2):130-137. PubMed ID: 30723850
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.