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 *

304 related articles for article (PubMed ID: 26274018)

  • 1. Mapping cell populations in flow cytometry data for cross-sample comparison using the Friedman-Rafsky test statistic as a distance measure.
    Hsiao C; Liu M; Stanton R; McGee M; Qian Y; Scheuermann RH
    Cytometry A; 2016 Jan; 89(1):71-88. PubMed ID: 26274018
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Modeling of inter-sample variation in flow cytometric data with the joint clustering and matching procedure.
    Lee SX; McLachlan GJ; Pyne S
    Cytometry A; 2016 Jan; 89(1):30-43. PubMed ID: 26492316
    [TBL] [Abstract][Full Text] [Related]  

  • 3. flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population identification.
    Malek M; Taghiyar MJ; Chong L; Finak G; Gottardo R; Brinkman RR
    Bioinformatics; 2015 Feb; 31(4):606-7. PubMed ID: 25378466
    [TBL] [Abstract][Full Text] [Related]  

  • 4. FR-Match: robust matching of cell type clusters from single cell RNA sequencing data using the Friedman-Rafsky non-parametric test.
    Zhang Y; Aevermann BD; Bakken TE; Miller JA; Hodge RD; Lein ES; Scheuermann RH
    Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33249453
    [TBL] [Abstract][Full Text] [Related]  

  • 5. NetFCM: a semi-automated web-based method for flow cytometry data analysis.
    Frederiksen J; Buggert M; Karlsson AC; Lund O
    Cytometry A; 2014 Nov; 85(11):969-77. PubMed ID: 25044796
    [TBL] [Abstract][Full Text] [Related]  

  • 6. immunoClust--An automated analysis pipeline for the identification of immunophenotypic signatures in high-dimensional cytometric datasets.
    Sörensen T; Baumgart S; Durek P; Grützkau A; Häupl T
    Cytometry A; 2015 Jul; 87(7):603-15. PubMed ID: 25850678
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Critical assessment of automated flow cytometry data analysis techniques.
    Aghaeepour N; Finak G; ; ; Hoos H; Mosmann TR; Brinkman R; Gottardo R; Scheuermann RH
    Nat Methods; 2013 Mar; 10(3):228-38. PubMed ID: 23396282
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparison of clustering methods for high-dimensional single-cell flow and mass cytometry data.
    Weber LM; Robinson MD
    Cytometry A; 2016 Dec; 89(12):1084-1096. PubMed ID: 27992111
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Quadratic form: a robust metric for quantitative comparison of flow cytometric histograms.
    Bernas T; Asem EK; Robinson JP; Rajwa B
    Cytometry A; 2008 Aug; 73(8):715-26. PubMed ID: 18561196
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Identifying Cell Populations in Flow Cytometry Data Using Phenotypic Signatures.
    Pouyan MB; Nourani M
    IEEE/ACM Trans Comput Biol Bioinform; 2017; 14(4):880-891. PubMed ID: 27076456
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes.
    Aghaeepour N; Chattopadhyay P; Chikina M; Dhaene T; Van Gassen S; Kursa M; Lambrecht BN; Malek M; McLachlan GJ; Qian Y; Qiu P; Saeys Y; Stanton R; Tong D; Vens C; Walkowiak S; Wang K; Finak G; Gottardo R; Mosmann T; Nolan GP; Scheuermann RH; Brinkman RR
    Cytometry A; 2016 Jan; 89(1):16-21. PubMed ID: 26447924
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Elucidation of seventeen human peripheral blood B-cell subsets and quantification of the tetanus response using a density-based method for the automated identification of cell populations in multidimensional flow cytometry data.
    Qian Y; Wei C; Eun-Hyung Lee F; Campbell J; Halliley J; Lee JA; Cai J; Kong YM; Sadat E; Thomson E; Dunn P; Seegmiller AC; Karandikar NJ; Tipton CM; Mosmann T; Sanz I; Scheuermann RH
    Cytometry B Clin Cytom; 2010; 78 Suppl 1(Suppl 1):S69-82. PubMed ID: 20839340
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A computational approach for phenotypic comparisons of cell populations in high-dimensional cytometry data.
    Platon L; Pejoski D; Gautreau G; Targat B; Le Grand R; Beignon AS; Tchitchek N
    Methods; 2018 Jan; 132():66-75. PubMed ID: 28917725
    [TBL] [Abstract][Full Text] [Related]  

  • 14. DAFi: A directed recursive data filtering and clustering approach for improving and interpreting data clustering identification of cell populations from polychromatic flow cytometry data.
    Lee AJ; Chang I; Burel JG; Lindestam Arlehamn CS; Mandava A; Weiskopf D; Peters B; Sette A; Scheuermann RH; Qian Y
    Cytometry A; 2018 Jun; 93(6):597-610. PubMed ID: 29665244
    [TBL] [Abstract][Full Text] [Related]  

  • 15. cytometree: A binary tree algorithm for automatic gating in cytometry analysis.
    Commenges D; Alkhassim C; Gottardo R; Hejblum B; Thiébaut R
    Cytometry A; 2018 Nov; 93(11):1132-1140. PubMed ID: 30277649
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Analysis of clinical flow cytometric immunophenotyping data by clustering on statistical manifolds: treating flow cytometry data as high-dimensional objects.
    Finn WG; Carter KM; Raich R; Stoolman LM; Hero AO
    Cytometry B Clin Cytom; 2009 Jan; 76(1):1-7. PubMed ID: 18642311
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Unfold High-Dimensional Clouds for Exhaustive Gating of Flow Cytometry Data.
    Qiu P
    IEEE/ACM Trans Comput Biol Bioinform; 2014; 11(6):1045-51. PubMed ID: 26357042
    [TBL] [Abstract][Full Text] [Related]  

  • 18. gEM/GANN: A multivariate computational strategy for auto-characterizing relationships between cellular and clinical phenotypes and predicting disease progression time using high-dimensional flow cytometry data.
    Tong DL; Ball GR; Pockley AG
    Cytometry A; 2015 Jul; 87(7):616-23. PubMed ID: 25572884
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Computational prediction of manually gated rare cells in flow cytometry data.
    Qiu P
    Cytometry A; 2015 Jul; 87(7):594-602. PubMed ID: 25755118
    [TBL] [Abstract][Full Text] [Related]  

  • 20. What is a "unimodal" cell population? Using statistical tests as criteria for unimodality in automated gating and quality control.
    Johnsson K; Linderoth M; Fontes M
    Cytometry A; 2017 Sep; 91(9):908-916. PubMed ID: 28759711
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.