BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

140 related articles for article (PubMed ID: 36993544)

  • 1. 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]  

  • 2. 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]  

  • 3. 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]  

  • 4. scBSP: A fast and accurate tool for identifying spatially variable genes from spatial transcriptomic data.
    Li J; Wang Y; Raina MA; Xu C; Su L; Guo Q; Ma Q; Wang J; Xu D
    bioRxiv; 2024 May; ():. PubMed ID: 38765956
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. Recent advances in spatially variable gene detection in spatial transcriptomics.
    Das Adhikari S; Yang J; Wang J; Cui Y
    Comput Struct Biotechnol J; 2024 Dec; 23():883-891. PubMed ID: 38370977
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. A SELECTIVE REVIEW OF RECENT DEVELOPMENTS IN SPATIALLY VARIABLE GENE DETECTION FOR SPATIAL TRANSCRIPTOMICS.
    Adhikari SD; Yang J; Wang J; Cui Y
    ArXiv; 2023 Nov; ():. PubMed ID: 38045476
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. 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]  

  • 11. 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]  

  • 12. The spatiotemporal dynamics of spatially variable genes in developing mouse brain revealed by a novel computational scheme.
    Hong Y; Song K; Zhang Z; Deng Y; Zhang X; Zhao J; Jiang J; Zhang Q; Guo C; Peng C
    Cell Death Discov; 2023 Jul; 9(1):264. PubMed ID: 37500639
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomic data with nonuniform cellular densities.
    Miller BF; Bambah-Mukku D; Dulac C; Zhuang X; Fan J
    Genome Res; 2021 Oct; 31(10):1843-1855. PubMed ID: 34035045
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 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. DESpace: spatially variable gene detection via differential expression testing of spatial clusters.
    Cai P; Robinson MD; Tiberi S
    Bioinformatics; 2024 Feb; 40(2):. PubMed ID: 38243704
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Categorization of 31 computational methods to detect spatially variable genes from spatially resolved transcriptomics data.
    Yan G; Hua SH; Li JJ
    ArXiv; 2024 May; ():. PubMed ID: 38855546
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. SpaceX: gene co-expression network estimation for spatial transcriptomics.
    Acharyya S; Zhou X; Baladandayuthapani V
    Bioinformatics; 2022 Nov; 38(22):5033-5041. PubMed ID: 36179087
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.