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 *

191 related articles for article (PubMed ID: 38940132)

  • 1. SPRITE: improving spatial gene expression imputation with gene and cell networks.
    Sun ED; Ma R; Zou J
    Bioinformatics; 2024 Jun; 40(Suppl 1):i521-i528. PubMed ID: 38940132
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. scMAGS: Marker gene selection from scRNA-seq data for spatial transcriptomics studies.
    Baran Y; Doğan B
    Comput Biol Med; 2023 Mar; 155():106634. PubMed ID: 36774895
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A point cloud segmentation framework for image-based spatial transcriptomics.
    Defard T; Laporte H; Ayan M; Soulier J; Curras-Alonso S; Weber C; Massip F; Londoño-Vallejo JA; Fouillade C; Mueller F; Walter T
    Commun Biol; 2024 Jul; 7(1):823. PubMed ID: 38971915
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Imputing spatial transcriptomics through gene network constructed from protein language model.
    Zeng Y; Song Y; Zhang C; Li H; Zhao Y; Yu W; Zhang S; Zhang H; Dai Z; Yang Y
    Commun Biol; 2024 Oct; 7(1):1271. PubMed ID: 39369061
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Hidden Markov random field models for cell-type assignment of spatially resolved transcriptomics.
    Zhong C; Tian T; Wei Z
    Bioinformatics; 2023 Nov; 39(11):. PubMed ID: 37944045
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. 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]  

  • 10. SFINN: inferring gene regulatory network from single-cell and spatial transcriptomic data with shared factor neighborhood and integrated neural network.
    Wang Y; Zhou F; Guan J
    Bioinformatics; 2024 Jul; 40(7):. PubMed ID: 38950180
    [TBL] [Abstract][Full Text] [Related]  

  • 11. BANMF-S: a blockwise accelerated non-negative matrix factorization framework with structural network constraints for single cell imputation.
    Zhao J; Ching WK; Wong CW; Cheng X
    Brief Bioinform; 2024 Jul; 25(5):. PubMed ID: 39242194
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Joint Bayesian estimation of cell dependence and gene associations in spatially resolved transcriptomic data.
    Chakrabarti A; Ni Y; Mallick BK
    Sci Rep; 2024 Apr; 14(1):9516. PubMed ID: 38664448
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. 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]  

  • 15. 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]  

  • 16. 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]  

  • 17. Clustering spatial transcriptomics data.
    Teng H; Yuan Y; Bar-Joseph Z
    Bioinformatics; 2022 Jan; 38(4):997-1004. PubMed ID: 34623423
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Computer vision for image-based transcriptomics.
    Stoeger T; Battich N; Herrmann MD; Yakimovich Y; Pelkmans L
    Methods; 2015 Sep; 85():44-53. PubMed ID: 26014038
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Benchmarking cell-type clustering methods for spatially resolved transcriptomics data.
    Cheng A; Hu G; Li WV
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36410733
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 10.