BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

277 related articles for article (PubMed ID: 37255323)

  • 1. MRGCN: cancer subtyping with multi-reconstruction graph convolutional network using full and partial multi-omics dataset.
    Yang B; Yang Y; Wang M; Su X
    Bioinformatics; 2023 Jun; 39(6):. PubMed ID: 37255323
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep structure integrative representation of multi-omics data for cancer subtyping.
    Yang B; Yang Y; Su X
    Bioinformatics; 2022 Jun; 38(13):3337-3342. PubMed ID: 35639657
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A network embedding based method for partial multi-omics integration in cancer subtyping.
    Xu H; Gao L; Huang M; Duan R
    Methods; 2021 Aug; 192():67-76. PubMed ID: 32805397
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Multi-omics clustering for cancer subtyping based on latent subspace learning.
    Ye X; Shang Y; Shi T; Zhang W; Sakurai T
    Comput Biol Med; 2023 Sep; 164():107223. PubMed ID: 37490833
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Integration of multi-omics data using adaptive graph learning and attention mechanism for patient classification and biomarker identification.
    Ouyang D; Liang Y; Li L; Ai N; Lu S; Yu M; Liu X; Xie S
    Comput Biol Med; 2023 Sep; 164():107303. PubMed ID: 37586201
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Autoencoder-assisted latent representation learning for survival prediction and multi-view clustering on multi-omics cancer subtyping.
    Zhu S; Wang W; Fang W; Cui M
    Math Biosci Eng; 2023 Nov; 20(12):21098-21119. PubMed ID: 38124589
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A semi-supervised approach for the integration of multi-omics data based on transformer multi-head self-attention mechanism and graph convolutional networks.
    Wang J; Liao N; Du X; Chen Q; Wei B
    BMC Genomics; 2024 Jan; 25(1):86. PubMed ID: 38254021
    [TBL] [Abstract][Full Text] [Related]  

  • 8. FGCNSurv: dually fused graph convolutional network for multi-omics survival prediction.
    Wen G; Li L
    Bioinformatics; 2023 Aug; 39(8):. PubMed ID: 37522887
    [TBL] [Abstract][Full Text] [Related]  

  • 9. HyperTMO: a trusted multi-omics integration framework based on hypergraph convolutional network for patient classification.
    Wang H; Lin K; Zhang Q; Shi J; Song X; Wu J; Zhao C; He K
    Bioinformatics; 2024 Mar; 40(4):. PubMed ID: 38530977
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Cancer subtype identification by consensus guided graph autoencoders.
    Liang C; Shang M; Luo J
    Bioinformatics; 2021 Dec; 37(24):4779-4786. PubMed ID: 34289034
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Capturing the latent space of an Autoencoder for multi-omics integration and cancer subtyping.
    Madhumita ; Paul S
    Comput Biol Med; 2022 Sep; 148():105832. PubMed ID: 35834966
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Molecular Subtyping of Cancer Based on Robust Graph Neural Network and Multi-Omics Data Integration.
    Yin C; Cao Y; Sun P; Zhang H; Li Z; Xu Y; Sun H
    Front Genet; 2022; 13():884028. PubMed ID: 35646077
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A multimodal graph neural network framework for cancer molecular subtype classification.
    Li B; Nabavi S
    BMC Bioinformatics; 2024 Jan; 25(1):27. PubMed ID: 38225583
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Multi-view spectral clustering with latent representation learning for applications on multi-omics cancer subtyping.
    Ge S; Liu J; Cheng Y; Meng X; Wang X
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36445207
    [TBL] [Abstract][Full Text] [Related]  

  • 15. GOAT: Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network for eosinophilic asthma subtype.
    Jeong D; Koo B; Oh M; Kim TB; Kim S
    Bioinformatics; 2023 Oct; 39(10):. PubMed ID: 37740295
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep Subspace Mutual Learning for cancer subtypes prediction.
    Yang B; Xin TT; Pang SM; Wang M; Wang YJ
    Bioinformatics; 2021 Nov; 37(21):3715-3722. PubMed ID: 34478501
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Manifold alignment for heterogeneous single-cell multi-omics data integration using Pamona.
    Cao K; Hong Y; Wan L
    Bioinformatics; 2021 Dec; 38(1):211-219. PubMed ID: 34398192
    [TBL] [Abstract][Full Text] [Related]  

  • 18. COmic: convolutional kernel networks for interpretable end-to-end learning on (multi-)omics data.
    Ditz JC; Reuter B; Pfeifer N
    Bioinformatics; 2023 Jun; 39(39 Suppl 1):i76-i85. PubMed ID: 37387152
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. A universal framework for single-cell multi-omics data integration with graph convolutional networks.
    Gao H; Zhang B; Liu L; Li S; Gao X; Yu B
    Brief Bioinform; 2023 May; 24(3):. PubMed ID: 36929841
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.