BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

183 related articles for article (PubMed ID: 38801701)

  • 1. A multi-view graph contrastive learning framework for deciphering spatially resolved transcriptomics data.
    Zhang L; Liang S; Wan L
    Brief Bioinform; 2024 May; 25(4):. PubMed ID: 38801701
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Spatially contrastive variational autoencoder for deciphering tissue heterogeneity from spatially resolved transcriptomics.
    Hu Y; Xiao K; Yang H; Liu X; Zhang C; Shi Q
    Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38324623
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Identifying spatial domains of spatially resolved transcriptomics via multi-view graph convolutional networks.
    Shi X; Zhu J; Long Y; Liang C
    Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37544658
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics.
    Wang L; Hu Y; Xiao K; Zhang C; Shi Q; Chen L
    Brief Bioinform; 2024 May; 25(4):. PubMed ID: 38819253
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A contrastive learning approach to integrate spatial transcriptomics and histological images.
    Lin Y; Liang Y; Wang D; Chang Y; Ma Q; Wang Y; He F; Xu D
    Comput Struct Biotechnol J; 2024 Dec; 23():1786-1795. PubMed ID: 38707535
    [TBL] [Abstract][Full Text] [Related]  

  • 6. STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering.
    Peng L; He X; Peng X; Li Z; Zhang L
    Comput Biol Med; 2023 Nov; 166():107440. PubMed ID: 37738898
    [TBL] [Abstract][Full Text] [Related]  

  • 7. ConSpaS: a contrastive learning framework for identifying spatial domains by integrating local and global similarities.
    Wu S; Qiu Y; Cheng X
    Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37965808
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Integrating multi-modal information to detect spatial domains of spatial transcriptomics by graph attention network.
    Huo Y; Guo Y; Wang J; Xue H; Feng Y; Chen W; Li X
    J Genet Genomics; 2023 Sep; 50(9):720-733. PubMed ID: 37356752
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Complete spatially resolved gene expression is not necessary for identifying spatial domains.
    Lin S; Cui Y; Zhao F; Yang Z; Song J; Yao J; Zhao Y; Qian BZ; Zhao Y; Yuan Z
    Cell Genom; 2024 Jun; 4(6):100565. PubMed ID: 38781966
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Accurate Identification of Spatial Domain by Incorporating Global Spatial Proximity and Local Expression Proximity.
    Yu Y; He Y; Xie Z
    Biomolecules; 2024 Jun; 14(6):. PubMed ID: 38927077
    [TBL] [Abstract][Full Text] [Related]  

  • 11. scBOL: a universal cell type identification framework for single-cell and spatial transcriptomics data.
    Zhai Y; Chen L; Deng M
    Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38678389
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Deciphering tissue heterogeneity from spatially resolved transcriptomics by the autoencoder-assisted graph convolutional neural network.
    Li X; Huang W; Xu X; Zhang HY; Shi Q
    Front Genet; 2023; 14():1202409. PubMed ID: 37303949
    [TBL] [Abstract][Full Text] [Related]  

  • 13. stAA: adversarial graph autoencoder for spatial clustering task of spatially resolved transcriptomics.
    Fang Z; Liu T; Zheng R; A J; Yin M; Li M
    Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38189544
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Impeller: a path-based heterogeneous graph learning method for spatial transcriptomic data imputation.
    Duan Z; Riffle D; Li R; Liu J; Min MR; Zhang J
    Bioinformatics; 2024 Jun; 40(6):. PubMed ID: 38806165
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder.
    Dong K; Zhang S
    Nat Commun; 2022 Apr; 13(1):1739. PubMed ID: 35365632
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Identifying spatial domain by adapting transcriptomics with histology through contrastive learning.
    Zeng Y; Yin R; Luo M; Chen J; Pan Z; Lu Y; Yu W; Yang Y
    Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36781228
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning.
    Chang Y; He F; Wang J; Chen S; Li J; Liu J; Yu Y; Su L; Ma A; Allen C; Lin Y; Sun S; Liu B; Javier Otero J; Chung D; Fu H; Li Z; Xu D; Ma Q
    Comput Struct Biotechnol J; 2022; 20():4600-4617. PubMed ID: 36090815
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Spatial domain detection using contrastive self-supervised learning for spatial multi-omics technologies.
    Yao J; Yu J; Caffo B; Page SC; Martinowich K; Hicks SC
    bioRxiv; 2024 Feb; ():. PubMed ID: 38352580
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification.
    Zhang C; Li X; Huang W; Wang L; Shi Q
    Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37253698
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding.
    Shen R; Liu L; Wu Z; Zhang Y; Yuan Z; Guo J; Yang F; Zhang C; Chen B; Feng W; Liu C; Guo J; Fan G; Zhang Y; Li Y; Xu X; Yao J
    Nat Commun; 2022 Dec; 13(1):7640. PubMed ID: 36496406
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.