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 *

392 related articles for article (PubMed ID: 33294129)

  • 21. 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]  

  • 22. Supervised learning of gene-regulatory networks based on graph distance profiles of transcriptomics data.
    Razaghi-Moghadam Z; Nikoloski Z
    NPJ Syst Biol Appl; 2020 Jun; 6(1):21. PubMed ID: 32606380
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Enhancing Graph Neural Networks by a High-quality Aggregation of Beneficial Information.
    Liu C; Wu J; Liu W; Hu W
    Neural Netw; 2021 Oct; 142():20-33. PubMed ID: 33964476
    [TBL] [Abstract][Full Text] [Related]  

  • 24. MGLNN: Semi-supervised learning via Multiple Graph Cooperative Learning Neural Networks.
    Jiang B; Chen S; Wang B; Luo B
    Neural Netw; 2022 Sep; 153():204-214. PubMed ID: 35750007
    [TBL] [Abstract][Full Text] [Related]  

  • 25. CVGAE: A Self-Supervised Generative Method for Gene Regulatory Network Inference Using Single-Cell RNA Sequencing Data.
    Liu W; Teng Z; Li Z; Chen J
    Interdiscip Sci; 2024 May; ():. PubMed ID: 38778003
    [TBL] [Abstract][Full Text] [Related]  

  • 26. CI-GNN: A Granger causality-inspired graph neural network for interpretable brain network-based psychiatric diagnosis.
    Zheng K; Yu S; Chen B
    Neural Netw; 2024 Apr; 172():106147. PubMed ID: 38306785
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Semi-supervised heterogeneous graph contrastive learning for drug-target interaction prediction.
    Yao K; Wang X; Li W; Zhu H; Jiang Y; Li Y; Tian T; Yang Z; Liu Q; Liu Q
    Comput Biol Med; 2023 Sep; 163():107199. PubMed ID: 37421738
    [TBL] [Abstract][Full Text] [Related]  

  • 28. CNNGRN: A Convolutional Neural Network-Based Method for Gene Regulatory Network Inference From Bulk Time-Series Expression Data.
    Gao Z; Tang J; Xia J; Zheng CH; Wei PJ
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(5):2853-2861. PubMed ID: 37267145
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Exploration of chemical space with partial labeled noisy student self-training and self-supervised graph embedding.
    Liu Y; Lim H; Xie L
    BMC Bioinformatics; 2022 May; 23(Suppl 3):158. PubMed ID: 35501680
    [TBL] [Abstract][Full Text] [Related]  

  • 30. GRACE: Unveiling Gene Regulatory Networks With Causal Mechanistic Graph Neural Networks in Single-Cell RNA-Sequencing Data.
    Wang JC; Chen YJ; Zou Q
    IEEE Trans Neural Netw Learn Syst; 2024 Jun; PP():. PubMed ID: 38896510
    [TBL] [Abstract][Full Text] [Related]  

  • 31. A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis.
    Ni Y; Aghamirzaie D; Elmarakeby H; Collakova E; Li S; Grene R; Heath LS
    Front Plant Sci; 2016; 7():1936. PubMed ID: 28066488
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Inferring gene regulatory networks from single-cell transcriptomics based on graph embedding.
    Gan Y; Yu J; Xu G; Yan C; Zou G
    Bioinformatics; 2024 May; 40(5):. PubMed ID: 38810116
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Semi-Supervised Mixture Learning for Graph Neural Networks With Neighbor Dependence.
    Liu K; Liu H; Wang T; Hu G; Ward TE; Chen CLP
    IEEE Trans Neural Netw Learn Syst; 2023 Apr; PP():. PubMed ID: 37037240
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Visualizing Graph Neural Networks With CorGIE: Corresponding a Graph to Its Embedding.
    Liu Z; Wang Y; Bernard J; Munzner T
    IEEE Trans Vis Comput Graph; 2022 Jun; 28(6):2500-2516. PubMed ID: 35120005
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Efficient dynamic graph construction for inductive semi-supervised learning.
    Dornaika F; Dahbi R; Bosaghzadeh A; Ruichek Y
    Neural Netw; 2017 Oct; 94():192-203. PubMed ID: 28802162
    [TBL] [Abstract][Full Text] [Related]  

  • 36. scSGL: kernelized signed graph learning for single-cell gene regulatory network inference.
    Karaaslanli A; Saha S; Aviyente S; Maiti T
    Bioinformatics; 2022 May; 38(11):3011-3019. PubMed ID: 35451460
    [TBL] [Abstract][Full Text] [Related]  

  • 37. TRaCE+: Ensemble inference of gene regulatory networks from transcriptional expression profiles of gene knock-out experiments.
    Ud-Dean SM; Heise S; Klamt S; Gunawan R
    BMC Bioinformatics; 2016 Jun; 17():252. PubMed ID: 27342648
    [TBL] [Abstract][Full Text] [Related]  

  • 38. SCGRNs: Novel supervised inference of single-cell gene regulatory networks of complex diseases.
    Turki T; Taguchi YH
    Comput Biol Med; 2020 Mar; 118():103656. PubMed ID: 32174324
    [TBL] [Abstract][Full Text] [Related]  

  • 39. A gene regulatory network inference model based on pseudo-siamese network.
    Wang Q; Guo M; Chen J; Duan R
    BMC Bioinformatics; 2023 Apr; 24(1):163. PubMed ID: 37085776
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Supervised Learning of Gene Regulatory Networks.
    Razaghi-Moghadam Z; Nikoloski Z
    Curr Protoc Plant Biol; 2020 Jun; 5(2):e20106. PubMed ID: 32207875
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 20.