BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

203 related articles for article (PubMed ID: 30528274)

  • 1. Visualizing and Interpreting Single-Cell Gene Expression Datasets with Similarity Weighted Nonnegative Embedding.
    Wu Y; Tamayo P; Zhang K
    Cell Syst; 2018 Dec; 7(6):656-666.e4. PubMed ID: 30528274
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Generalizable and Scalable Visualization of Single-Cell Data Using Neural Networks.
    Cho H; Berger B; Peng J
    Cell Syst; 2018 Aug; 7(2):185-191.e4. PubMed ID: 29936184
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Visualization of Single Cell RNA-Seq Data Using t-SNE in R.
    Zhou B; Jin W
    Methods Mol Biol; 2020; 2117():159-167. PubMed ID: 31960377
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Fast interpolation-based t-SNE for improved visualization of single-cell RNA-seq data.
    Linderman GC; Rachh M; Hoskins JG; Steinerberger S; Kluger Y
    Nat Methods; 2019 Mar; 16(3):243-245. PubMed ID: 30742040
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Visualizing Cluster-specific Genes from Single-cell Transcriptomics Data Using Association Plots.
    Gralinska E; Kohl C; Sokhandan Fadakar B; Vingron M
    J Mol Biol; 2022 Jun; 434(11):167525. PubMed ID: 35271868
    [TBL] [Abstract][Full Text] [Related]  

  • 6. XCVATR: detection and characterization of variant impact on the Embeddings of single -cell and bulk RNA-sequencing samples.
    Harmanci A; Harmanci AS; Klisch TJ; Patel AJ
    BMC Genomics; 2022 Dec; 23(1):841. PubMed ID: 36539717
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Statistical method scDEED for detecting dubious 2D single-cell embeddings and optimizing t-SNE and UMAP hyperparameters.
    Xia L; Lee C; Li JJ
    Nat Commun; 2024 Feb; 15(1):1753. PubMed ID: 38409103
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Jointly defining cell types from multiple single-cell datasets using LIGER.
    Liu J; Gao C; Sodicoff J; Kozareva V; Macosko EZ; Welch JD
    Nat Protoc; 2020 Nov; 15(11):3632-3662. PubMed ID: 33046898
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Assessing single-cell transcriptomic variability through density-preserving data visualization.
    Narayan A; Berger B; Cho H
    Nat Biotechnol; 2021 Jun; 39(6):765-774. PubMed ID: 33462509
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Supervised capacity preserving mapping: a clustering guided visualization method for scRNA-seq data.
    Zhai Z; Lei YL; Wang R; Xie Y
    Bioinformatics; 2022 Apr; 38(9):2496-2503. PubMed ID: 35253834
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Network-Based Structural Learning Nonnegative Matrix Factorization Algorithm for Clustering of scRNA-Seq Data.
    Wu W; Ma X
    IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(1):566-575. PubMed ID: 35316190
    [TBL] [Abstract][Full Text] [Related]  

  • 12. WEDGE: imputation of gene expression values from single-cell RNA-seq datasets using biased matrix decomposition.
    Hu Y; Li B; Zhang W; Liu N; Cai P; Chen F; Qu K
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33834202
    [TBL] [Abstract][Full Text] [Related]  

  • 13. UINMF performs mosaic integration of single-cell multi-omic datasets using nonnegative matrix factorization.
    Kriebel AR; Welch JD
    Nat Commun; 2022 Feb; 13(1):780. PubMed ID: 35140223
    [TBL] [Abstract][Full Text] [Related]  

  • 14. scSTEM: clustering pseudotime ordered single-cell data.
    Song Q; Wang J; Bar-Joseph Z
    Genome Biol; 2022 Jul; 23(1):150. PubMed ID: 35799304
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Robust classification of single-cell transcriptome data by nonnegative matrix factorization.
    Shao C; Höfer T
    Bioinformatics; 2017 Jan; 33(2):235-242. PubMed ID: 27663498
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Single Cell Self-Paced Clustering with Transcriptome Sequencing Data.
    Zhao P; Xu Z; Chen J; Ren Y; King I
    Int J Mol Sci; 2022 Mar; 23(7):. PubMed ID: 35409258
    [TBL] [Abstract][Full Text] [Related]  

  • 18. SMURF: embedding single-cell RNA-seq data with matrix factorization preserving self-consistency.
    Pu J; Wang B; Liu X; Chen L; Li SC
    Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36715274
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. GE-Impute: graph embedding-based imputation for single-cell RNA-seq data.
    Wu X; Zhou Y
    Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35901457
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.