BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

218 related articles for article (PubMed ID: 26447924)

  • 1. 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]  

  • 2. FloReMi: Flow density survival regression using minimal feature redundancy.
    Van Gassen S; Vens C; Dhaene T; Lambrecht BN; Saeys Y
    Cytometry A; 2016 Jan; 89(1):22-9. PubMed ID: 26243673
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. RchyOptimyx: cellular hierarchy optimization for flow cytometry.
    Aghaeepour N; Jalali A; O'Neill K; Chattopadhyay PK; Roederer M; Hoos HH; Brinkman RR
    Cytometry A; 2012 Dec; 81(12):1022-30. PubMed ID: 23044634
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. 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]  

  • 7. 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]  

  • 8. 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]  

  • 9. Identification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data.
    Lin L; Frelinger J; Jiang W; Finak G; Seshadri C; Bart PA; Pantaleo G; McElrath J; DeRosa S; Gottardo R
    Cytometry A; 2015 Jul; 87(7):675-82. PubMed ID: 25908275
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automated identification of stratifying signatures in cellular subpopulations.
    Bruggner RV; Bodenmiller B; Dill DL; Tibshirani RJ; Nolan GP
    Proc Natl Acad Sci U S A; 2014 Jul; 111(26):E2770-7. PubMed ID: 24979804
    [TBL] [Abstract][Full Text] [Related]  

  • 11. CytoML for cross-platform cytometry data sharing.
    Finak G; Jiang W; Gottardo R
    Cytometry A; 2018 Dec; 93(12):1189-1196. PubMed ID: 30551257
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. SWIFT-scalable clustering for automated identification of rare cell populations in large, high-dimensional flow cytometry datasets, part 2: biological evaluation.
    Mosmann TR; Naim I; Rebhahn J; Datta S; Cavenaugh JS; Weaver JM; Sharma G
    Cytometry A; 2014 May; 85(5):422-33. PubMed ID: 24532172
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Data-Driven Flow Cytometry Analysis.
    Wang S; Brinkman RR
    Methods Mol Biol; 2019; 1989():245-265. PubMed ID: 31077110
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Computational analysis optimizes the flow cytometric evaluation for lymphoma.
    Craig FE; Brinkman RR; Ten Eyck S; Aghaeepour N
    Cytometry B Clin Cytom; 2014 Jan; 86(1):18-24. PubMed ID: 24002786
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays.
    Aghaeepour N; Chattopadhyay PK; Ganesan A; O'Neill K; Zare H; Jalali A; Hoos HH; Roederer M; Brinkman RR
    Bioinformatics; 2012 Apr; 28(7):1009-16. PubMed ID: 22383736
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. 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]  

  • 20. Comparative exploration of multidimensional flow cytometry software: a model approach evaluating T cell polyfunctional behavior.
    Spear TT; Nishimura MI; Simms PE
    J Leukoc Biol; 2017 Aug; 102(2):551-561. PubMed ID: 28550117
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.