Per-channel basis normalization methods for flow cytometry data.
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Flow cytometry bioinformaticsStudying Cellular Signal Transduction with OMIC TechnologiesReceptor occupancy assessment by flow cytometry as a pharmacodynamic biomarker in biopharmaceutical developmentComparability and reproducibility of biomedical dataGenePattern flow cytometry suiteQUAliFiER: an automated pipeline for quality assessment of gated flow cytometry data.Normalization of mass cytometry data with bead standards.High-throughput flow cytometry data normalization for clinical trials.Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric dataOptimizing transformations for automated, high throughput analysis of flow cytometry data.Rapid cell population identification in flow cytometry dataA non-parametric Bayesian model for joint cell clustering and cluster matching: identification of anomalous sample phenotypes with random effects.BayesFlow: latent modeling of flow cytometry cell populationsA framework for analytical characterization of monoclonal antibodies based on reactivity profiles in different tissuesflowVS: channel-specific variance stabilization in flow cytometryFlow Cytometric Single-Cell Identification of Populations in Synthetic Bacterial Communities.A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes.CD4+ T cells with an activated and exhausted phenotype distinguish immunodeficiency during aviremic HIV-2 infection.Luciferase Expression Allows Bioluminescence Imaging But Imposes Limitations on the Orthotopic Mouse (4T1) Model of Breast Cancer.Removal of batch effects using distribution-matching residual networks.SWIFT-scalable clustering for automated identification of rare cell populations in large, high-dimensional flow cytometry datasets, part 2: biological evaluation.Single Cell and Population Level Analysis of HCA Data.flowLearn: Fast and precise identification and quality checking of cell populations in flow cytometry.DAFi: A directed recursive data filtering and clustering approach for improving and interpreting data clustering identification of cell populations from polychromatic flow cytometry data.Codon optimization and improved delivery/immunization regimen enhance the immune response against wild-type and drug-resistant HIV-1 reverse transcriptase, preserving its Th2-polarity.DNA immunization site determines the level of gene expression and the magnitude, but not the type of the induced immune response.
P2860
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P2860
Per-channel basis normalization methods for flow cytometry data.
description
2010 nî lūn-bûn
@nan
2010 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Per-channel basis normalization methods for flow cytometry data.
@ast
Per-channel basis normalization methods for flow cytometry data.
@en
Per-channel basis normalization methods for flow cytometry data.
@nl
type
label
Per-channel basis normalization methods for flow cytometry data.
@ast
Per-channel basis normalization methods for flow cytometry data.
@en
Per-channel basis normalization methods for flow cytometry data.
@nl
prefLabel
Per-channel basis normalization methods for flow cytometry data.
@ast
Per-channel basis normalization methods for flow cytometry data.
@en
Per-channel basis normalization methods for flow cytometry data.
@nl
P2093
P2860
P356
P1433
P1476
Per-channel basis normalization methods for flow cytometry data.
@en
P2093
Adam Asare
Ali Bashashati
Alireza Hadj Khodabakhshi
Andrew P Weng
Chao-Jen Wong
Florian Hahne
Katarzyna Bourcier
Ryan R Brinkman
Thomas Lumley
Vicky Seyfert-Margolis
P2860
P304
P356
10.1002/CYTO.A.20823
P577
2010-02-01T00:00:00Z