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 *

173 related articles for article (PubMed ID: 39056705)

  • 21. scGCL: an imputation method for scRNA-seq data based on graph contrastive learning.
    Xiong Z; Luo J; Shi W; Liu Y; Xu Z; Wang B
    Bioinformatics; 2023 Mar; 39(3):. PubMed ID: 36825817
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Visualizing Single-Cell RNA-seq Data with Semisupervised Principal Component Analysis.
    Liu Z
    Int J Mol Sci; 2020 Aug; 21(16):. PubMed ID: 32806757
    [TBL] [Abstract][Full Text] [Related]  

  • 23. SCDRHA: A scRNA-Seq Data Dimensionality Reduction Algorithm Based on Hierarchical Autoencoder.
    Zhao J; Wang N; Wang H; Zheng C; Su Y
    Front Genet; 2021; 12():733906. PubMed ID: 34512734
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Dimensionality Reduction of Single-Cell RNA-Seq Data.
    Linderman GC
    Methods Mol Biol; 2021; 2284():331-342. PubMed ID: 33835451
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Single-cell RNA sequencing data analysis based on non-uniform ε-neighborhood network.
    Jia J; Chen L
    Bioinformatics; 2022 Apr; 38(9):2459-2465. PubMed ID: 35188181
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Dimensionality reduction by UMAP reinforces sample heterogeneity analysis in bulk transcriptomic data.
    Yang Y; Sun H; Zhang Y; Zhang T; Gong J; Wei Y; Duan YG; Shu M; Yang Y; Wu D; Yu D
    Cell Rep; 2021 Jul; 36(4):109442. PubMed ID: 34320340
    [TBL] [Abstract][Full Text] [Related]  

  • 27. A Comparison for Dimensionality Reduction Methods of Single-Cell RNA-seq Data.
    Xiang R; Wang W; Yang L; Wang S; Xu C; Chen X
    Front Genet; 2021; 12():646936. PubMed ID: 33833778
    [TBL] [Abstract][Full Text] [Related]  

  • 28. AE-TPGG: a novel autoencoder-based approach for single-cell RNA-seq data imputation and dimensionality reduction.
    Zhao S; Zhang L; Liu X
    Front Comput Sci; 2023; 17(3):173902. PubMed ID: 36320820
    [TBL] [Abstract][Full Text] [Related]  

  • 29. A robust nonlinear low-dimensional manifold for single cell RNA-seq data.
    Verma A; Engelhardt BE
    BMC Bioinformatics; 2020 Jul; 21(1):324. PubMed ID: 32693778
    [TBL] [Abstract][Full Text] [Related]  

  • 30. scGCC: Graph Contrastive Clustering With Neighborhood Augmentations for scRNA-Seq Data Analysis.
    Tian SW; Ni JC; Wang YT; Zheng CH; Ji CM
    IEEE J Biomed Health Inform; 2023 Dec; 27(12):6133-6143. PubMed ID: 37751336
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Clustering Single-Cell RNA Sequence Data Using Information Maximized and Noise-Invariant Representations.
    Mondal AK; Joshi I; Singh P; Ap P
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(3):1983-1994. PubMed ID: 37015582
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Clustering single-cell RNA sequencing data via iterative smoothing and self-supervised discriminative embedding.
    Xie J; Ruan S; Tu M; Yuan Z; Hu J; Li H; Li S
    Oncogene; 2024 Jul; 43(29):2279-2292. PubMed ID: 38834657
    [TBL] [Abstract][Full Text] [Related]  

  • 33. ScLRTC: imputation for single-cell RNA-seq data via low-rank tensor completion.
    Pan X; Li Z; Qin S; Yu M; Hu H
    BMC Genomics; 2021 Nov; 22(1):860. PubMed ID: 34844559
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Recovering Gene Interactions from Single-Cell Data Using Data Diffusion.
    van Dijk D; Sharma R; Nainys J; Yim K; Kathail P; Carr AJ; Burdziak C; Moon KR; Chaffer CL; Pattabiraman D; Bierie B; Mazutis L; Wolf G; Krishnaswamy S; Pe'er D
    Cell; 2018 Jul; 174(3):716-729.e27. PubMed ID: 29961576
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics.
    Hu Q; Greene CS
    Pac Symp Biocomput; 2019; 24():362-373. PubMed ID: 30963075
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Contrastive self-supervised clustering of scRNA-seq data.
    Ciortan M; Defrance M
    BMC Bioinformatics; 2021 May; 22(1):280. PubMed ID: 34044773
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Single-cell RNA sequencing data imputation using bi-level feature propagation.
    Lee J; Yun S; Kim Y; Chen T; Kellis M; Park C
    Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38706317
    [TBL] [Abstract][Full Text] [Related]  

  • 38. scBGEDA: deep single-cell clustering analysis via a dual denoising autoencoder with bipartite graph ensemble clustering.
    Wang Y; Yu Z; Li S; Bian C; Liang Y; Wong KC; Li X
    Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36734596
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Resolution of the curse of dimensionality in single-cell RNA sequencing data analysis.
    Imoto Y; Nakamura T; Escolar EG; Yoshiwaki M; Kojima Y; Yabuta Y; Katou Y; Yamamoto T; Hiraoka Y; Saitou M
    Life Sci Alliance; 2022 Aug; 5(12):. PubMed ID: 35944930
    [TBL] [Abstract][Full Text] [Related]  

  • 40. scNAME: neighborhood contrastive clustering with ancillary mask estimation for scRNA-seq data.
    Wan H; Chen L; Deng M
    Bioinformatics; 2022 Mar; 38(6):1575-1583. PubMed ID: 34999761
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.