Critical assessment of automated flow cytometry data analysis techniques. (Q30587564)

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23 February 2020

title

Critical assessment of automated flow cytometry data analysis techniques (English)

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23 February 2020

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flow cytometry data analysis

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inferred from title

author

Richard H. Scheuermann

9

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23 February 2020

Holger H. Hoos

5

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23 February 2020

Ryan R Brinkman

7

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23 February 2020

1

Nima Aghaeepour

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23 February 2020

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Raphael Gottardo

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23 February 2020

Tiziana Sanavia

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Giovanna Ambrosini

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Raquel Norel

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George Luta

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author name string

Greg Finak

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23 February 2020

FlowCAP Consortium

3

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23 February 2020

DREAM Consortium

4

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23 February 2020

Tim R Mosmann

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23 February 2020

language of work or name

English

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publication date

10 February 2013

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23 February 2020

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23 February 2020

volume

10

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23 February 2020

issue

3

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23 February 2020

page(s)

228-238

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RchyOptimyx: cellular hierarchy optimization for flow cytometry

23 February 2020

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20 June 2018

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Matching phosphorylation response patterns of antigen-receptor-stimulated T cells via flow cytometry

20 June 2018

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Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays.

20 June 2018

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Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes

20 June 2018

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20 June 2018

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Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE

20 June 2018

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Verification of systems biology research in the age of collaborative competition

20 June 2018

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Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum

20 June 2018

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SPICE: exploration and analysis of post-cytometric complex multivariate datasets

20 June 2018

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Multiparameter flow cytometry in the diagnosis and management of acute leukemia

20 June 2018

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Rapid cell population identification in flow cytometry data

20 June 2018

1 reference

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Misty Mountain clustering: application to fast unsupervised flow cytometry gating

20 June 2018

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Understanding GPU Programming for Statistical Computation: Studies in Massively Parallel Massive Mixtures

20 June 2018

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Automated pattern-guided principal component analysis vs expert-based immunophenotypic classification of B-cell chronic lymphoproliferative disorders: a step forward in the standardization of clinical immunophenotyping

20 June 2018

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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

20 June 2018

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Data reduction for spectral clustering to analyze high throughput flow cytometry data

20 June 2018

1 reference

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Data analysis in flow cytometry: the future just started

20 June 2018

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Towards a rigorous assessment of systems biology models: the DREAM3 challenges

20 June 2018

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The curvHDR method for gating flow cytometry samples.

20 June 2018

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Merging mixture components for cell population identification in flow cytometry

20 June 2018

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Automated high-dimensional flow cytometric data analysis

20 June 2018

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MIFlowCyt: the minimum information about a Flow Cytometry Experiment

20 June 2018

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Automated gating of flow cytometry data via robust model-based clustering

20 June 2018

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20 June 2018

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20 June 2018

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20 June 2018

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20 June 2018

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20 June 2018

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12 December 2020

Statistical mixture modeling for cell subtype identification in flow cytometry

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Crossref

https://api.crossref.org/works/10.1038%2FNMETH.2365

7 January 2021

inferred from DOI database lookup

Identifiers

DOI

10.1038/NMETH.2365

1 reference

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Dimensions Publication ID

23 February 2020

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1 reference

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23 February 2020

PubMed publication ID

23396282

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