BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

287 related articles for article (PubMed ID: 36530425)

  • 1. Recent advances in machine learning methods for predicting LncRNA and disease associations.
    Tan J; Li X; Zhang L; Du Z
    Front Cell Infect Microbiol; 2022; 12():1071972. PubMed ID: 36530425
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Recent advances in predicting lncRNA-disease associations based on computational methods.
    Yan J; Wang R; Tan J
    Drug Discov Today; 2023 Feb; 28(2):103432. PubMed ID: 36370992
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Long non-coding RNAs and complex diseases: from experimental results to computational models.
    Chen X; Yan CC; Zhang X; You ZH
    Brief Bioinform; 2017 Jul; 18(4):558-576. PubMed ID: 27345524
    [TBL] [Abstract][Full Text] [Related]  

  • 4. LncRNA-Disease Associations Prediction Using Bipartite Local Model With Nearest Profile-Based Association Inferring.
    Cui Z; Liu JX; Gao YL; Zhu R; Yuan SS
    IEEE J Biomed Health Inform; 2020 May; 24(5):1519-1527. PubMed ID: 31478878
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Computational prediction of disease related lncRNAs using machine learning.
    Khalid R; Naveed H; Khalid Z
    Sci Rep; 2023 Jan; 13(1):806. PubMed ID: 36646775
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Predicting lncRNA-disease associations using network topological similarity based on deep mining heterogeneous networks.
    Zhang H; Liang Y; Peng C; Han S; Du W; Li Y
    Math Biosci; 2019 Sep; 315():108229. PubMed ID: 31323239
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Predicting binary, discrete and continued lncRNA-disease associations via a unified framework based on graph regression.
    Shi JY; Huang H; Zhang YN; Long YX; Yiu SM
    BMC Med Genomics; 2017 Dec; 10(Suppl 4):65. PubMed ID: 29322937
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. 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]  

  • 11. Recent Advances in Predicting Protein-lncRNA Interactions Using Machine Learning Methods.
    Yu H; Shen ZA; Zhou YK; Du PF
    Curr Gene Ther; 2022; 22(3):228-244. PubMed ID: 34254917
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. HOPEXGB: A Consensual Model for Predicting miRNA/lncRNA-Disease Associations Using a Heterogeneous Disease-miRNA-lncRNA Information Network.
    He J; Li M; Qiu J; Pu X; Guo Y
    J Chem Inf Model; 2024 Apr; 64(7):2863-2877. PubMed ID: 37604142
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 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. DMFLDA: A Deep Learning Framework for Predicting lncRNA-Disease Associations.
    Zeng M; Lu C; Fei Z; Wu FX; Li Y; Wang J; Li M
    IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(6):2353-2363. PubMed ID: 32248123
    [TBL] [Abstract][Full Text] [Related]  

  • 17. CRlncRC: a machine learning-based method for cancer-related long noncoding RNA identification using integrated features.
    Zhang X; Wang J; Li J; Chen W; Liu C
    BMC Med Genomics; 2018 Dec; 11(Suppl 6):120. PubMed ID: 30598114
    [TBL] [Abstract][Full Text] [Related]  

  • 18. LDAEXC: LncRNA-Disease Associations Prediction with Deep Autoencoder and XGBoost Classifier.
    Lu C; Xie M
    Interdiscip Sci; 2023 Sep; 15(3):439-451. PubMed ID: 37308797
    [TBL] [Abstract][Full Text] [Related]  

  • 19. GAE-LGA: integration of multi-omics data with graph autoencoders to identify lncRNA-PCG associations.
    Gao M; Liu S; Qi Y; Guo X; Shang X
    Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36305456
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Computational models for lncRNA function prediction and functional similarity calculation.
    Chen X; Sun YZ; Guan NN; Qu J; Huang ZA; Zhu ZX; Li JQ
    Brief Funct Genomics; 2019 Feb; 18(1):58-82. PubMed ID: 30247501
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.