BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

183 related articles for article (PubMed ID: 37284317)

  • 1. Drug-disease association prediction with literature based multi-feature fusion.
    Kang H; Hou L; Gu Y; Lu X; Li J; Li Q
    Front Pharmacol; 2023; 14():1205144. PubMed ID: 37284317
    [No Abstract]   [Full Text] [Related]  

  • 2. REDDA: Integrating multiple biological relations to heterogeneous graph neural network for drug-disease association prediction.
    Gu Y; Zheng S; Yin Q; Jiang R; Li J
    Comput Biol Med; 2022 Nov; 150():106127. PubMed ID: 36182762
    [TBL] [Abstract][Full Text] [Related]  

  • 3. MIFAM-DTI: a drug-target interactions predicting model based on multi-source information fusion and attention mechanism.
    Li J; Sun L; Liu L; Li Z
    Front Genet; 2024; 15():1381997. PubMed ID: 38770418
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Drug repositioning based on the heterogeneous information fusion graph convolutional network.
    Cai L; Lu C; Xu J; Meng Y; Wang P; Fu X; Zeng X; Su Y
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34378011
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Drug Repositioning Based on the Enhanced Message Passing and Hypergraph Convolutional Networks.
    Huang W; Li Z; Kang Y; Ye X; Feng W
    Biomolecules; 2022 Nov; 12(11):. PubMed ID: 36359016
    [TBL] [Abstract][Full Text] [Related]  

  • 6. DRGCL: Drug Repositioning via Semantic-enriched Graph Contrastive Learning.
    Jia X; Sun X; Wang K; Li M
    IEEE J Biomed Health Inform; 2024 Mar; PP():. PubMed ID: 38437145
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Computational drug repositioning based on multi-similarities bilinear matrix factorization.
    Yang M; Wu G; Zhao Q; Li Y; Wang J
    Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33147616
    [TBL] [Abstract][Full Text] [Related]  

  • 8. MDF-SA-DDI: predicting drug-drug interaction events based on multi-source drug fusion, multi-source feature fusion and transformer self-attention mechanism.
    Lin S; Wang Y; Zhang L; Chu Y; Liu Y; Fang Y; Jiang M; Wang Q; Zhao B; Xiong Y; Wei DQ
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34671814
    [TBL] [Abstract][Full Text] [Related]  

  • 9. EFMSDTI: Drug-target interaction prediction based on an efficient fusion of multi-source data.
    Zhang Y; Wu M; Wang S; Chen W
    Front Pharmacol; 2022; 13():1009996. PubMed ID: 36210804
    [TBL] [Abstract][Full Text] [Related]  

  • 10. PDDGCN: A Parasitic Disease-Drug Association Predictor Based on Multi-view Fusion Graph Convolutional Network.
    Wang X; Chen G; Hu H; Zhang M; Rao Y; Yue Z
    Interdiscip Sci; 2024 Mar; 16(1):231-242. PubMed ID: 38294648
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Learning multi-scale heterogenous network topologies and various pairwise attributes for drug-disease association prediction.
    Zhang H; Cui H; Zhang T; Cao Y; Xuan P
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35136910
    [TBL] [Abstract][Full Text] [Related]  

  • 12. MvKFN-MDA: Multi-view Kernel Fusion Network for miRNA-disease association prediction.
    Li J; Liu T; Wang J; Li Q; Ning C; Yang Y
    Artif Intell Med; 2021 Aug; 118():102115. PubMed ID: 34412838
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Prediction of microbe-drug associations based on a modified graph attention variational autoencoder and random forest.
    Wang B; Ma F; Du X; Zhang G; Li J
    Front Microbiol; 2024; 15():1394302. PubMed ID: 38881658
    [TBL] [Abstract][Full Text] [Related]  

  • 14. DDA-SKF: Predicting Drug-Disease Associations Using Similarity Kernel Fusion.
    Gao CQ; Zhou YK; Xin XH; Min H; Du PF
    Front Pharmacol; 2021; 12():784171. PubMed ID: 35095495
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Multi-view contrastive heterogeneous graph attention network for lncRNA-disease association prediction.
    Zhao X; Wu J; Zhao X; Yin M
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36528809
    [TBL] [Abstract][Full Text] [Related]  

  • 16. DTiGEMS+: drug-target interaction prediction using graph embedding, graph mining, and similarity-based techniques.
    Thafar MA; Olayan RS; Ashoor H; Albaradei S; Bajic VB; Gao X; Gojobori T; Essack M
    J Cheminform; 2020 Jun; 12(1):44. PubMed ID: 33431036
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Prediction of drug-target binding affinity based on multi-scale feature fusion.
    Yu H; Xu WX; Tan T; Liu Z; Shi JY
    Comput Biol Med; 2024 Jun; 178():108699. PubMed ID: 38870725
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. A novel graph attention model for predicting frequencies of drug-side effects from multi-view data.
    Zhao H; Zheng K; Li Y; Wang J
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34213525
    [TBL] [Abstract][Full Text] [Related]  

  • 20. In silico drug repositioning based on the integration of chemical, genomic and pharmacological spaces.
    Chen H; Zhang Z; Zhang J
    BMC Bioinformatics; 2021 Feb; 22(1):52. PubMed ID: 33557749
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.