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 *

193 related articles for article (PubMed ID: 37862362)

  • 1. SMASH: Scalable Method for Analyzing Spatial Heterogeneity of genes in spatial transcriptomics data.
    Seal S; Bitler BG; Ghosh D
    PLoS Genet; 2023 Oct; 19(10):e1010983. PubMed ID: 37862362
    [TBL] [Abstract][Full Text] [Related]  

  • 2. SMASH: Scalable Method for Analyzing Spatial Heterogeneity of genes in spatial transcriptomics data.
    Seal S; Bitler BG; Ghosh D
    bioRxiv; 2023 Mar; ():. PubMed ID: 36993287
    [TBL] [Abstract][Full Text] [Related]  

  • 3. SMaSH: a scalable, general marker gene identification framework for single-cell RNA-sequencing.
    Nelson ME; Riva SG; Cvejic A
    BMC Bioinformatics; 2022 Aug; 23(1):328. PubMed ID: 35941549
    [TBL] [Abstract][Full Text] [Related]  

  • 4. SINFONIA: Scalable Identification of Spatially Variable Genes for Deciphering Spatial Domains.
    Jiang R; Li Z; Jia Y; Li S; Chen S
    Cells; 2023 Feb; 12(4):. PubMed ID: 36831270
    [TBL] [Abstract][Full Text] [Related]  

  • 5. HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics.
    Yuan X; Ma Y; Gao R; Cui S; Wang Y; Fa B; Ma S; Wei T; Ma S; Yu Z
    Nat Commun; 2024 Jul; 15(1):5700. PubMed ID: 38972896
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Evaluating spatially variable gene detection methods for spatial transcriptomics data.
    Chen C; Kim HJ; Yang P
    Genome Biol; 2024 Jan; 25(1):18. PubMed ID: 38225676
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Dimension-agnostic and granularity-based spatially variable gene identification using BSP.
    Wang J; Li J; Kramer ST; Su L; Chang Y; Xu C; Eadon MT; Kiryluk K; Ma Q; Xu D
    Nat Commun; 2023 Nov; 14(1):7367. PubMed ID: 37963892
    [TBL] [Abstract][Full Text] [Related]  

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

  • 9. 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]  

  • 10. PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics.
    Liang Y; Shi G; Cai R; Yuan Y; Xie Z; Yu L; Huang Y; Shi Q; Wang L; Li J; Tang Z
    Nat Commun; 2024 Jan; 15(1):600. PubMed ID: 38238417
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Dimension-agnostic and granularity-based spatially variable gene identification.
    Wang J; Li J; Kramer ST; Su L; Chang Y; Xu C; Ma Q; Xu D
    bioRxiv; 2023 Mar; ():. PubMed ID: 36993544
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Dimension-agnostic and granularity-based spatially variable gene identification.
    Wang J; Li J; Kramer S; Su L; Chang Y; Xu C; Ma Q; Xu D
    Res Sq; 2023 Mar; ():. PubMed ID: 36993309
    [TBL] [Abstract][Full Text] [Related]  

  • 13. SPIN-AI: A Deep Learning Model That Identifies Spatially Predictive Genes.
    Meng-Lin K; Ung CY; Zhang C; Weiskittel TM; Wisniewski P; Zhang Z; Tan SH; Yeo KS; Zhu S; Correia C; Li H
    Biomolecules; 2023 May; 13(6):. PubMed ID: 37371475
    [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. CROST: a comprehensive repository of spatial transcriptomics.
    Wang G; Wu S; Xiong Z; Qu H; Fang X; Bao Y
    Nucleic Acids Res; 2024 Jan; 52(D1):D882-D890. PubMed ID: 37791883
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST.
    Liu W; Liao X; Luo Z; Yang Y; Lau MC; Jiao Y; Shi X; Zhai W; Ji H; Yeong J; Liu J
    Nat Commun; 2023 Jan; 14(1):296. PubMed ID: 36653349
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Disparities in spatially variable gene calling highlight the need for benchmarking spatial transcriptomics methods.
    Charitakis N; Salim A; Piers AT; Watt KI; Porrello ER; Elliott DA; Ramialison M
    Genome Biol; 2023 Sep; 24(1):209. PubMed ID: 37723583
    [TBL] [Abstract][Full Text] [Related]  

  • 18. STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning.
    Zhang C; Dong K; Aihara K; Chen L; Zhang S
    Nucleic Acids Res; 2023 Nov; 51(20):e103. PubMed ID: 37811885
    [TBL] [Abstract][Full Text] [Related]  

  • 19. SGCAST: symmetric graph convolutional auto-encoder for scalable and accurate study of spatial transcriptomics.
    Li J; Wang J; Lin Z
    Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38171928
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A Bayesian multivariate mixture model for high throughput spatial transcriptomics.
    Allen C; Chang Y; Neelon B; Chang W; Kim HJ; Li Z; Ma Q; Chung D
    Biometrics; 2023 Sep; 79(3):1775-1787. PubMed ID: 35895854
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.