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 *

575 related articles for article (PubMed ID: 35487922)

  • 1. Reference-free cell type deconvolution of multi-cellular pixel-resolution spatially resolved transcriptomics data.
    Miller BF; Huang F; Atta L; Sahoo A; Fan J
    Nat Commun; 2022 Apr; 13(1):2339. PubMed ID: 35487922
    [TBL] [Abstract][Full Text] [Related]  

  • 2. SpatialCTD: A Large-Scale Tumor Microenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology.
    Ding J; Li L; Lu Q; Venegas J; Wang Y; Wu L; Jin W; Wen H; Liu R; Tang W; Dai X; Li Z; Zuo W; Chang Y; Lei YL; Shang L; Danaher P; Xie Y; Tang J
    J Comput Biol; 2024 Sep; 31(9):871-885. PubMed ID: 39117342
    [TBL] [Abstract][Full Text] [Related]  

  • 3. ScType enables fast and accurate cell type identification from spatial transcriptomics data.
    Nader K; Tasci M; Ianevski A; Erickson A; Verschuren EW; Aittokallio T; Miihkinen M
    Bioinformatics; 2024 Jul; 40(7):. PubMed ID: 38936341
    [TBL] [Abstract][Full Text] [Related]  

  • 4. RETROFIT: Reference-free deconvolution of cell-type mixtures in spatial transcriptomics.
    Singh R; He X; Park AK; Hardison RC; Zhu X; Li Q
    bioRxiv; 2023 Jun; ():. PubMed ID: 37333291
    [TBL] [Abstract][Full Text] [Related]  

  • 5. SD2: spatially resolved transcriptomics deconvolution through integration of dropout and spatial information.
    Li H; Li H; Zhou J; Gao X
    Bioinformatics; 2022 Oct; 38(21):4878-4884. PubMed ID: 36063455
    [TBL] [Abstract][Full Text] [Related]  

  • 6. stVAE deconvolves cell-type composition in large-scale cellular resolution spatial transcriptomics.
    Li C; Chan TF; Yang C; Lin Z
    Bioinformatics; 2023 Oct; 39(10):. PubMed ID: 37862237
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Uncover spatially informed variations for single-cell spatial transcriptomics with STew.
    Guo N; Vargas J; Reynoso S; Fritz D; Krishna R; Wang C; Zhang F
    Bioinform Adv; 2024; 4(1):vbae064. PubMed ID: 38827413
    [TBL] [Abstract][Full Text] [Related]  

  • 9. stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics.
    Shengquan C; Boheng Z; Xiaoyang C; Xuegong Z; Rui J
    Bioinformatics; 2021 Jul; 37(Suppl_1):i299-i307. PubMed ID: 34252941
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. 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]  

  • 12. EnDecon: cell type deconvolution of spatially resolved transcriptomics data via ensemble learning.
    Tu JJ; Li HS; Yan H; Zhang XF
    Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36610709
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Robust decomposition of cell type mixtures in spatial transcriptomics.
    Cable DM; Murray E; Zou LS; Goeva A; Macosko EZ; Chen F; Irizarry RA
    Nat Biotechnol; 2022 Apr; 40(4):517-526. PubMed ID: 33603203
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Probabilistic cell/domain-type assignment of spatial transcriptomics data with SpatialAnno.
    Shi X; Yang Y; Ma X; Zhou Y; Guo Z; Wang C; Liu J
    Nucleic Acids Res; 2023 Dec; 51(22):e115. PubMed ID: 37941153
    [TBL] [Abstract][Full Text] [Related]  

  • 15. STdGCN: spatial transcriptomic cell-type deconvolution using graph convolutional networks.
    Li Y; Luo Y
    Genome Biol; 2024 Aug; 25(1):206. PubMed ID: 39103939
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Simulating multiple variability in spatially resolved transcriptomics with scCube.
    Qian J; Bao H; Shao X; Fang Y; Liao J; Chen Z; Li C; Guo W; Hu Y; Li A; Yao Y; Fan X; Cheng Y
    Nat Commun; 2024 Jun; 15(1):5021. PubMed ID: 38866768
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. SpatialDeX is a Reference-Free Method for Cell Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors.
    Liu X; Tang G; Chen Y; Li Y; Li H; Wang X
    Cancer Res; 2024 Oct; ():. PubMed ID: 39387817
    [TBL] [Abstract][Full Text] [Related]  

  • 19. SpatialPrompt: spatially aware scalable and accurate tool for spot deconvolution and domain identification in spatial transcriptomics.
    Swain AK; Pandit V; Sharma J; Yadav P
    Commun Biol; 2024 May; 7(1):639. PubMed ID: 38796505
    [TBL] [Abstract][Full Text] [Related]  

  • 20. STtools: A Comprehensive Software Pipeline for Ultra-high Resolution Spatial Transcriptomics Data.
    Xi J; Lee JH; Kang HM; Jun G
    Bioinform Adv; 2022; 2(1):. PubMed ID: 36284674
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 29.