BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

552 related articles for article (PubMed ID: 30758819)

  • 1. Identification of Cell Types from Single-Cell Transcriptomic Data.
    Shekhar K; Menon V
    Methods Mol Biol; 2019; 1935():45-77. PubMed ID: 30758819
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Data Analysis in Single-Cell Transcriptome Sequencing.
    Gao S
    Methods Mol Biol; 2018; 1754():311-326. PubMed ID: 29536451
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A multitask clustering approach for single-cell RNA-seq analysis in Recessive Dystrophic Epidermolysis Bullosa.
    Zhang H; Lee CAA; Li Z; Garbe JR; Eide CR; Petegrosso R; Kuang R; Tolar J
    PLoS Comput Biol; 2018 Apr; 14(4):e1006053. PubMed ID: 29630593
    [TBL] [Abstract][Full Text] [Related]  

  • 4. An accessible, interactive GenePattern Notebook for analysis and exploration of single-cell transcriptomic data.
    Mah CK; Wenzel AT; Juarez EF; Tabor T; Reich MM; Mesirov JP
    F1000Res; 2018; 7():1306. PubMed ID: 31316748
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Single-Cell RNA Sequencing Analysis: A Step-by-Step Overview.
    Slovin S; Carissimo A; Panariello F; Grimaldi A; Bouché V; Gambardella G; Cacchiarelli D
    Methods Mol Biol; 2021; 2284():343-365. PubMed ID: 33835452
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Bayesian mixture model for clustering droplet-based single-cell transcriptomic data from population studies.
    Sun Z; Chen L; Xin H; Jiang Y; Huang Q; Cillo AR; Tabib T; Kolls JK; Bruno TC; Lafyatis R; Vignali DAA; Chen K; Ding Y; Hu M; Chen W
    Nat Commun; 2019 Apr; 10(1):1649. PubMed ID: 30967541
    [TBL] [Abstract][Full Text] [Related]  

  • 7. SINCERA: A Pipeline for Single-Cell RNA-Seq Profiling Analysis.
    Guo M; Wang H; Potter SS; Whitsett JA; Xu Y
    PLoS Comput Biol; 2015 Nov; 11(11):e1004575. PubMed ID: 26600239
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Rare Cell Type Detection.
    Jiang L
    Methods Mol Biol; 2019; 1935():79-89. PubMed ID: 30758820
    [TBL] [Abstract][Full Text] [Related]  

  • 9. The promise of single-cell RNA sequencing for kidney disease investigation.
    Wu H; Humphreys BD
    Kidney Int; 2017 Dec; 92(6):1334-1342. PubMed ID: 28893418
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Analysis of Technical and Biological Variability in Single-Cell RNA Sequencing.
    Kim B; Lee E; Kim JK
    Methods Mol Biol; 2019; 1935():25-43. PubMed ID: 30758818
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A hybrid deep clustering approach for robust cell type profiling using single-cell RNA-seq data.
    Srinivasan S; Leshchyk A; Johnson NT; Korkin D
    RNA; 2020 Oct; 26(10):1303-1319. PubMed ID: 32532794
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A Bioinformatic Toolkit for Single-Cell mRNA Analysis.
    Baßler K; Günther P; Schulte-Schrepping J; Becker M; Biernat P
    Methods Mol Biol; 2019; 1979():433-455. PubMed ID: 31028653
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Computational approaches for interpreting scRNA-seq data.
    Rostom R; Svensson V; Teichmann SA; Kar G
    FEBS Lett; 2017 Aug; 591(15):2213-2225. PubMed ID: 28524227
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Single-Cell Transcriptomics of Immune Cells: Cell Isolation and cDNA Library Generation for scRNA-Seq.
    Arsenio J
    Methods Mol Biol; 2020; 2184():1-18. PubMed ID: 32808214
    [TBL] [Abstract][Full Text] [Related]  

  • 15. VPAC: Variational projection for accurate clustering of single-cell transcriptomic data.
    Chen S; Hua K; Cui H; Jiang R
    BMC Bioinformatics; 2019 May; 20(Suppl 7):0. PubMed ID: 31074382
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Machine learning and statistical methods for clustering single-cell RNA-sequencing data.
    Petegrosso R; Li Z; Kuang R
    Brief Bioinform; 2020 Jul; 21(4):1209-1223. PubMed ID: 31243426
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Single-Cell Transcriptome Analysis Using SINCERA Pipeline.
    Guo M; Xu Y
    Methods Mol Biol; 2018; 1751():209-222. PubMed ID: 29508300
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Random forest based similarity learning for single cell RNA sequencing data.
    Pouyan MB; Kostka D
    Bioinformatics; 2018 Jul; 34(13):i79-i88. PubMed ID: 29950006
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A Gene Rank Based Approach for Single Cell Similarity Assessment and Clustering.
    Xu Y; Li HD; Pan Y; Luo F; Wu FX; Wang J
    IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(2):431-442. PubMed ID: 31369384
    [TBL] [Abstract][Full Text] [Related]  

  • 20. DIMM-SC: a Dirichlet mixture model for clustering droplet-based single cell transcriptomic data.
    Sun Z; Wang T; Deng K; Wang XF; Lafyatis R; Ding Y; Hu M; Chen W
    Bioinformatics; 2018 Jan; 34(1):139-146. PubMed ID: 29036318
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 28.