BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

188 related articles for article (PubMed ID: 37699885)

  • 1. SiGra: single-cell spatial elucidation through an image-augmented graph transformer.
    Tang Z; Li Z; Hou T; Zhang T; Yang B; Su J; Song Q
    Nat Commun; 2023 Sep; 14(1):5618. PubMed ID: 37699885
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Innovative super-resolution in spatial transcriptomics: a transformer model exploiting histology images and spatial gene expression.
    Zhao C; Xu Z; Wang X; Tao S; MacDonald WA; He K; Poholek AC; Chen K; Huang H; Chen W
    Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38436557
    [TBL] [Abstract][Full Text] [Related]  

  • 3. SCS: cell segmentation for high-resolution spatial transcriptomics.
    Chen H; Li D; Bar-Joseph Z
    Nat Methods; 2023 Aug; 20(8):1237-1243. PubMed ID: 37429992
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Inferring spatial transcriptomics markers from whole slide images to characterize metastasis-related spatial heterogeneity of colorectal tumors: A pilot study.
    Fatemi M; Feng E; Sharma C; Azher Z; Goel T; Ramwala O; Palisoul SM; Barney RE; Perreard L; Kolling FW; Salas LA; Christensen BC; Tsongalis GJ; Vaickus LJ; Levy JJ
    J Pathol Inform; 2023; 14():100308. PubMed ID: 37114077
    [TBL] [Abstract][Full Text] [Related]  

  • 5. SpaRx: elucidate single-cell spatial heterogeneity of drug responses for personalized treatment.
    Tang Z; Liu X; Li Z; Zhang T; Yang B; Su J; Song Q
    Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37798249
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Spatial transcriptomics prediction from histology jointly through Transformer and graph neural networks.
    Zeng Y; Wei Z; Yu W; Yin R; Yuan Y; Li B; Tang Z; Lu Y; Yang Y
    Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35849101
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Graph deep learning enabled spatial domains identification for spatial transcriptomics.
    Liu T; Fang ZY; Li X; Zhang LN; Cao DS; Yin MZ
    Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37080761
    [TBL] [Abstract][Full Text] [Related]  

  • 9. SCAN-IT: Domain segmentation of spatial transcriptomics images by graph neural network.
    Cang Z; Ning X; Nie A; Xu M; Zhang J
    BMVC; 2021 Nov; 32():. PubMed ID: 36227018
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Breast cancer histopathology image-based gene expression prediction using spatial transcriptomics data and deep learning.
    Rahaman MM; Millar EKA; Meijering E
    Sci Rep; 2023 Aug; 13(1):13604. PubMed ID: 37604916
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Computational solutions for spatial transcriptomics.
    Kleino I; Frolovaitė P; Suomi T; Elo LL
    Comput Struct Biotechnol J; 2022; 20():4870-4884. PubMed ID: 36147664
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Recent advances in high-throughput single-cell transcriptomics and spatial transcriptomics.
    Shen X; Zhao Y; Wang Z; Shi Q
    Lab Chip; 2022 Dec; 22(24):4774-4791. PubMed ID: 36254761
    [TBL] [Abstract][Full Text] [Related]  

  • 13. xSiGra: Explainable model for single-cell spatial data elucidation.
    Budhkar A; Tang Z; Liu X; Zhang X; Su J; Song Q
    bioRxiv; 2024 Apr; ():. PubMed ID: 38746321
    [TBL] [Abstract][Full Text] [Related]  

  • 14. spaCI: deciphering spatial cellular communications through adaptive graph model.
    Tang Z; Zhang T; Yang B; Su J; Song Q
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36545790
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Imputation of spatially-resolved transcriptomes by graph-regularized tensor completion.
    Li Z; Song T; Yong J; Kuang R
    PLoS Comput Biol; 2021 Apr; 17(4):e1008218. PubMed ID: 33826608
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Single-cell level deconvolution, convolution, and clustering in spatial transcriptomics by aligning spot level transcriptome to nuclear morphology.
    Zhu S; Kubota N; Wang S; Wang T; Xiao G; Hoshida Y
    bioRxiv; 2023 Dec; ():. PubMed ID: 38187541
    [TBL] [Abstract][Full Text] [Related]  

  • 18. DSTG: deconvoluting spatial transcriptomics data through graph-based artificial intelligence.
    Song Q; Su J
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33480403
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Advances in spatial transcriptomics and related data analysis strategies.
    Du J; Yang YC; An ZJ; Zhang MH; Fu XH; Huang ZF; Yuan Y; Hou J
    J Transl Med; 2023 May; 21(1):330. PubMed ID: 37202762
    [TBL] [Abstract][Full Text] [Related]  

  • 20. SpatialcoGCN: deconvolution and spatial information-aware simulation of spatial transcriptomics data via deep graph co-embedding.
    Yin W; Wan Y; Zhou Y
    Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38557675
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.