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 *

154 related articles for article (PubMed ID: 33014009)

  • 1. Pseudo2GO: A Graph-Based Deep Learning Method for Pseudogene Function Prediction by Borrowing Information From Coding Genes.
    Fan K; Zhang Y
    Front Genet; 2020; 11():807. PubMed ID: 33014009
    [TBL] [Abstract][Full Text] [Related]  

  • 2. PseudoFuN: Deriving functional potentials of pseudogenes from integrative relationships with genes and microRNAs across 32 cancers.
    Johnson TS; Li S; Franz E; Huang Z; Dan Li S; Campbell MJ; Huang K; Zhang Y
    Gigascience; 2019 May; 8(5):. PubMed ID: 31029062
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Predicting Pseudogene-miRNA Associations Based on Feature Fusion and Graph Auto-Encoder.
    Zhou S; Sun W; Zhang P; Li L
    Front Genet; 2021; 12():781277. PubMed ID: 34966413
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A novel candidate disease gene prioritization method using deep graph convolutional networks and semi-supervised learning.
    Azadifar S; Ahmadi A
    BMC Bioinformatics; 2022 Oct; 23(1):422. PubMed ID: 36241966
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Network analysis of pseudogene-gene relationships: from pseudogene evolution to their functional potentials.
    Johnson TS; Li S; Kho JR; Huang K; Zhang Y
    Pac Symp Biocomput; 2018; 23():536-547. PubMed ID: 29218912
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Inferring pseudogene-MiRNA associations based on an ensemble learning framework with similarity kernel fusion.
    Fan C; Ding M
    Sci Rep; 2023 May; 13(1):8833. PubMed ID: 37258695
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Predicting functions of maize proteins using graph convolutional network.
    Zhou G; Wang J; Zhang X; Guo M; Yu G
    BMC Bioinformatics; 2020 Dec; 21(Suppl 16):420. PubMed ID: 33323113
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Graph generative and adversarial strategy-enhanced node feature learning and self-calibrated pairwise attribute encoding for prediction of drug-related side effects.
    Xuan P; Xu K; Cui H; Nakaguchi T; Zhang T
    Front Pharmacol; 2023; 14():1257842. PubMed ID: 37731739
    [No Abstract]   [Full Text] [Related]  

  • 9. 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]  

  • 10. MAMF-GCN: Multi-scale adaptive multi-channel fusion deep graph convolutional network for predicting mental disorder.
    Pan J; Lin H; Dong Y; Wang Y; Ji Y
    Comput Biol Med; 2022 Sep; 148():105823. PubMed ID: 35872410
    [TBL] [Abstract][Full Text] [Related]  

  • 11. GENCODE pseudogenes.
    Frankish A; Harrow J
    Methods Mol Biol; 2014; 1167():129-55. PubMed ID: 24823776
    [TBL] [Abstract][Full Text] [Related]  

  • 12. SeBioGraph: Semi-supervised Deep Learning for the Graph via Sustainable Knowledge Transfer.
    Ma Y; Li Q; Hu N; Li L
    Front Neurorobot; 2021; 15():665055. PubMed ID: 33867966
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A unified deep semi-supervised graph learning scheme based on nodes re-weighting and manifold regularization.
    Dornaika F; Bi J; Zhang C
    Neural Netw; 2023 Jan; 158():188-196. PubMed ID: 36462365
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Deep Learning Framework for Predicting Protein Functions With Co-Occurrence of GO Terms.
    Li M; Shi W; Zhang F; Zeng M; Li Y
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(2):833-842. PubMed ID: 35476573
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Comparative Analysis of Unsupervised Protein Similarity Prediction Based on Graph Embedding.
    Zhang Y; Wang Z; Wang S; Shang J
    Front Genet; 2021; 12():744334. PubMed ID: 34630534
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Application of Machine Learning in Developing a Novelty Five-Pseudogene Signature to Predict Prognosis of Head and Neck Squamous Cell Carcinoma: A New Aspect of "Junk Genes" in Biomedical Practice.
    Xing L; Zhang X; Guo M; Zhang X; Liu F
    DNA Cell Biol; 2020 Apr; 39(4):709-723. PubMed ID: 32045271
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep semi-supervised learning via dynamic anchor graph embedding in latent space.
    Tu E; Wang Z; Yang J; Kasabov N
    Neural Netw; 2022 Feb; 146():350-360. PubMed ID: 34929418
    [TBL] [Abstract][Full Text] [Related]  

  • 18. HPODNets: deep graph convolutional networks for predicting human protein-phenotype associations.
    Liu L; Mamitsuka H; Zhu S
    Bioinformatics; 2022 Jan; 38(3):799-808. PubMed ID: 34672333
    [TBL] [Abstract][Full Text] [Related]  

  • 19. GOGCN: Graph Convolutional Network on Gene Ontology for Functional Similarity Analysis of Genes.
    Tian Z; Fang H; Teng Z; Ye Y
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(2):1053-1064. PubMed ID: 35687647
    [TBL] [Abstract][Full Text] [Related]  

  • 20. MDA-GCNFTG: identifying miRNA-disease associations based on graph convolutional networks via graph sampling through the feature and topology graph.
    Chu Y; Wang X; Dai Q; Wang Y; Wang Q; Peng S; Wei X; Qiu J; Salahub DR; Xiong Y; Wei DQ
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34009265
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.