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 *

311 related articles for article (PubMed ID: 34864856)

  • 1. Predicting drug-drug interactions by graph convolutional network with multi-kernel.
    Wang F; Lei X; Liao B; Wu FX
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34864856
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Prediction of Drug-Drug Interaction Using an Attention-Based Graph Neural Network on Drug Molecular Graphs.
    Feng YH; Zhang SW
    Molecules; 2022 May; 27(9):. PubMed ID: 35566354
    [TBL] [Abstract][Full Text] [Related]  

  • 3. DPDDI: a deep predictor for drug-drug interactions.
    Feng YH; Zhang SW; Shi JY
    BMC Bioinformatics; 2020 Sep; 21(1):419. PubMed ID: 32972364
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Drug-Drug Interaction Predictions via Knowledge Graph and Text Embedding: Instrument Validation Study.
    Wang M; Wang H; Liu X; Ma X; Wang B
    JMIR Med Inform; 2021 Jun; 9(6):e28277. PubMed ID: 34185011
    [TBL] [Abstract][Full Text] [Related]  

  • 5. deepMDDI: A deep graph convolutional network framework for multi-label prediction of drug-drug interactions.
    Feng YH; Zhang SW; Zhang QQ; Zhang CH; Shi JY
    Anal Biochem; 2022 Jun; 646():114631. PubMed ID: 35227661
    [TBL] [Abstract][Full Text] [Related]  

  • 6. MM-GANN-DDI: Multimodal Graph-Agnostic Neural Networks for Predicting Drug-Drug Interaction Events.
    Feng J; Liang Y; Yu T
    Comput Biol Med; 2023 Nov; 166():107492. PubMed ID: 37820558
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A social theory-enhanced graph representation learning framework for multitask prediction of drug-drug interactions.
    Feng YH; Zhang SW; Feng YY; Zhang QQ; Shi MH; Shi JY
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36642408
    [TBL] [Abstract][Full Text] [Related]  

  • 8. DDI-GCN: Drug-drug interaction prediction via explainable graph convolutional networks.
    Zhong Y; Zheng H; Chen X; Zhao Y; Gao T; Dong H; Luo H; Weng Z
    Artif Intell Med; 2023 Oct; 144():102640. PubMed ID: 37783544
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Multi-type feature fusion based on graph neural network for drug-drug interaction prediction.
    He C; Liu Y; Li H; Zhang H; Mao Y; Qin X; Liu L; Zhang X
    BMC Bioinformatics; 2022 Jun; 23(1):224. PubMed ID: 35689200
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Leveraging syntactic and semantic graph kernels to extract pharmacokinetic drug drug interactions from biomedical literature.
    Zhang Y; Wu HY; Xu J; Wang J; Soysal E; Li L; Xu H
    BMC Syst Biol; 2016 Aug; 10 Suppl 3(Suppl 3):67. PubMed ID: 27585838
    [TBL] [Abstract][Full Text] [Related]  

  • 11. TMFUF: a triple matrix factorization-based unified framework for predicting comprehensive drug-drug interactions of new drugs.
    Shi JY; Huang H; Li JX; Lei P; Zhang YN; Dong K; Yiu SM
    BMC Bioinformatics; 2018 Nov; 19(Suppl 14):411. PubMed ID: 30453924
    [TBL] [Abstract][Full Text] [Related]  

  • 12. AMDE: a novel attention-mechanism-based multidimensional feature encoder for drug-drug interaction prediction.
    Pang S; Zhang Y; Song T; Zhang X; Wang X; Rodriguez-Patón A
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34965586
    [TBL] [Abstract][Full Text] [Related]  

  • 13. BioDKG-DDI: predicting drug-drug interactions based on drug knowledge graph fusing biochemical information.
    Ren ZH; Yu CQ; Li LP; You ZH; Guan YJ; Wang XF; Pan J
    Brief Funct Genomics; 2022 May; 21(3):216-229. PubMed ID: 35368060
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization.
    Yu H; Mao KT; Shi JY; Huang H; Chen Z; Dong K; Yiu SM
    BMC Syst Biol; 2018 Apr; 12(Suppl 1):14. PubMed ID: 29671393
    [TBL] [Abstract][Full Text] [Related]  

  • 15. CNN-DDI: a learning-based method for predicting drug-drug interactions using convolution neural networks.
    Zhang C; Lu Y; Zang T
    BMC Bioinformatics; 2022 Mar; 23(Suppl 1):88. PubMed ID: 35255808
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Attention-based cross domain graph neural network for prediction of drug-drug interactions.
    Yu H; Li K; Dong W; Song S; Gao C; Shi J
    Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37195815
    [TBL] [Abstract][Full Text] [Related]  

  • 17. DMFDDI: deep multimodal fusion for drug-drug interaction prediction.
    Gan Y; Liu W; Xu G; Yan C; Zou G
    Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37930025
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A dual graph neural network for drug-drug interactions prediction based on molecular structure and interactions.
    Ma M; Lei X
    PLoS Comput Biol; 2023 Jan; 19(1):e1010812. PubMed ID: 36701288
    [TBL] [Abstract][Full Text] [Related]  

  • 19. DDIGIP: predicting drug-drug interactions based on Gaussian interaction profile kernels.
    Yan C; Duan G; Pan Y; Wu FX; Wang J
    BMC Bioinformatics; 2019 Dec; 20(Suppl 15):538. PubMed ID: 31874609
    [TBL] [Abstract][Full Text] [Related]  

  • 20. GCNGAT: Drug-disease association prediction based on graph convolution neural network and graph attention network.
    Yang R; Fu Y; Zhang Q; Zhang L
    Artif Intell Med; 2024 Apr; 150():102805. PubMed ID: 38553169
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.