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 *

131 related articles for article (PubMed ID: 37155405)

  • 1. Predicting Protein-Protein Interactions Using Sequence and Network Information via Variational Graph Autoencoder.
    Luo X; Wang L; Hu P; Hu L
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(5):3182-3194. PubMed ID: 37155405
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Graph-based prediction of Protein-protein interactions with attributed signed graph embedding.
    Yang F; Fan K; Song D; Lin H
    BMC Bioinformatics; 2020 Jul; 21(1):323. PubMed ID: 32693790
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Graph embedding-based novel protein interaction prediction via higher-order graph convolutional network.
    Xiao Z; Deng Y
    PLoS One; 2020; 15(9):e0238915. PubMed ID: 32970681
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DSSGNN-PPI: A Protein-Protein Interactions prediction model based on Double Structure and Sequence graph neural networks.
    Zhang F; Chang S; Wang B; Zhang X
    Comput Biol Med; 2024 Jul; 177():108669. PubMed ID: 38833802
    [TBL] [Abstract][Full Text] [Related]  

  • 5. GNNGL-PPI: multi-category prediction of protein-protein interactions using graph neural networks based on global graphs and local subgraphs.
    Zeng X; Meng FF; Wen ML; Li SJ; Li Y
    BMC Genomics; 2024 May; 25(1):406. PubMed ID: 38724906
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Predicting protein-protein interactions from protein sequences by a stacked sparse autoencoder deep neural network.
    Wang YB; You ZH; Li X; Jiang TH; Chen X; Zhou X; Wang L
    Mol Biosyst; 2017 Jun; 13(7):1336-1344. PubMed ID: 28604872
    [TBL] [Abstract][Full Text] [Related]  

  • 8. AE-LGBM: Sequence-based novel approach to detect interacting protein pairs via ensemble of autoencoder and LightGBM.
    Sharma A; Singh B
    Comput Biol Med; 2020 Oct; 125():103964. PubMed ID: 32911276
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Completing sparse and disconnected protein-protein network by deep learning.
    Huang L; Liao L; Wu CH
    BMC Bioinformatics; 2018 Mar; 19(1):103. PubMed ID: 29566671
    [TBL] [Abstract][Full Text] [Related]  

  • 10. PPISB: A Novel Network-Based Algorithm of Predicting Protein-Protein Interactions With Mixed Membership Stochastic Blockmodel.
    Wang X; Yang W; Yang Y; He Y; Zhang J; Wang L; Hu L
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(2):1606-1612. PubMed ID: 35939453
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Variational graph auto-encoders for miRNA-disease association prediction.
    Ding Y; Tian LP; Lei X; Liao B; Wu FX
    Methods; 2021 Aug; 192():25-34. PubMed ID: 32798654
    [TBL] [Abstract][Full Text] [Related]  

  • 12. MEG-PPIS: a fast protein-protein interaction site prediction method based on multi-scale graph information and equivariant graph neural network.
    Ding H; Li X; Han P; Tian X; Jing F; Wang S; Song T; Fu H; Kang N
    Bioinformatics; 2024 Jan; 40(5):. PubMed ID: 38640481
    [TBL] [Abstract][Full Text] [Related]  

  • 13. GVDTI: graph convolutional and variational autoencoders with attribute-level attention for drug-protein interaction prediction.
    Xuan P; Fan M; Cui H; Zhang T; Nakaguchi T
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34718408
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Long-distance dependency combined multi-hop graph neural networks for protein-protein interactions prediction.
    Zhong W; He C; Xiao C; Liu Y; Qin X; Yu Z
    BMC Bioinformatics; 2022 Dec; 23(1):521. PubMed ID: 36471248
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Local augmented graph neural network for multi-omics cancer prognosis prediction and analysis.
    Zhang Y; Xiong S; Wang Z; Liu Y; Luo H; Li B; Zou Q
    Methods; 2023 May; 213():1-9. PubMed ID: 36933628
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Amalgamation of 3D structure and sequence information for protein-protein interaction prediction.
    Jha K; Saha S
    Sci Rep; 2020 Nov; 10(1):19171. PubMed ID: 33154416
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Graph embeddings on gene ontology annotations for protein-protein interaction prediction.
    Zhong X; Rajapakse JC
    BMC Bioinformatics; 2020 Dec; 21(Suppl 16):560. PubMed ID: 33323115
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Protein-Protein Interaction Prediction via Structure-Based Deep Learning.
    Liu Y; Liu Y; Li Z
    Proteins; 2024 Nov; 92(11):1287-1296. PubMed ID: 38923590
    [TBL] [Abstract][Full Text] [Related]  

  • 19. LePrimAlign: local entropy-based alignment of PPI networks to predict conserved modules.
    Maskey S; Cho YR
    BMC Genomics; 2019 Dec; 20(Suppl 9):964. PubMed ID: 31874635
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Protein-Protein Interaction Prediction Based on Spectral Radius and General Regression Neural Network.
    Xu H; Xu D; Zhang N; Zhang Y; Gao R
    J Proteome Res; 2021 Mar; 20(3):1657-1665. PubMed ID: 33555893
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.