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The end of gating? An introduction to automated analysis of high dimensional cytometry data
The end of gating? An introduction to automated analysis of high dimensional cytometry data
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The end of gating? An introduction to automated analysis of high dimensional cytometry data

Mair, Florian ; Hartmann, Felix J. ; Mrdjen, Dunja ; Tosevski, Vinko ; Krieg, Carsten ; Becher, Burkhard

European journal of immunology, 2016-01, Vol.46 (1), p.34-43 [Periódico revisado por pares]

Germany: Wiley Subscription Services, Inc

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A Beginner's Guide to Analyzing and Visualizing Mass Cytometry Data
A Beginner's Guide to Analyzing and Visualizing Mass Cytometry Data
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A Beginner's Guide to Analyzing and Visualizing Mass Cytometry Data

Kimball, Abigail K ; Oko, Lauren M ; Bullock, Bonnie L ; Nemenoff, Raphael A ; van Dyk, Linda F ; Clambey, Eric T

The Journal of immunology (1950), 2018-01, Vol.200 (1), p.3-22 [Periódico revisado por pares]

United States: American Association of Immunologists

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3
Analyzing high-dimensional cytometry data using FlowSOM
Analyzing high-dimensional cytometry data using FlowSOM
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Analyzing high-dimensional cytometry data using FlowSOM

Quintelier, Katrien ; Couckuyt, Artuur ; Emmaneel, Annelies ; Aerts, Joachim ; Saeys, Yvan ; Van Gassen, Sofie

Nature protocols, 2021-08, Vol.16 (8), p.3775-3801 [Periódico revisado por pares]

England: Nature Publishing Group

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4
Quantifying cell densities and biovolumes of phytoplankton communities and functional groups using scanning flow cytometry, machine learning and unsupervised clustering
Quantifying cell densities and biovolumes of phytoplankton communities and functional groups using scanning flow cytometry, machine learning and unsupervised clustering
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Quantifying cell densities and biovolumes of phytoplankton communities and functional groups using scanning flow cytometry, machine learning and unsupervised clustering

Thomas, Mridul K ; Fontana, Simone ; Reyes, Marta ; Pomati, Francesco Lovejoy, Connie

PloS one, 2018-05, Vol.13 (5), p.e0196225-e0196225 [Periódico revisado por pares]

United States: Public Library of Science

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5
Thinking Outside the Gate: Single-Cell Assessments in Multiple Dimensions
Thinking Outside the Gate: Single-Cell Assessments in Multiple Dimensions
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Thinking Outside the Gate: Single-Cell Assessments in Multiple Dimensions

Kvistborg, Pia ; Gouttefangeas, Cécile ; Aghaeepour, Nima ; Cazaly, Angelica ; Chattopadhyay, Pratip K. ; Chan, Cliburn ; Eckl, Judith ; Finak, Greg ; Hadrup, Sine Reker ; Maecker, Holden T. ; Maurer, Dominik ; Mosmann, Tim ; Qiu, Peng ; Scheuermann, Richard H. ; Welters, Marij J.P. ; Ferrari, Guido ; Brinkman, Ryan R. ; Britten, Cedrik M.

Immunity (Cambridge, Mass.), 2015-04, Vol.42 (4), p.591-592 [Periódico revisado por pares]

United States: Elsevier Inc

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6
Establishment of normative ranges of the healthy human immune system with comprehensive polychromatic flow cytometry profiling
Establishment of normative ranges of the healthy human immune system with comprehensive polychromatic flow cytometry profiling
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Establishment of normative ranges of the healthy human immune system with comprehensive polychromatic flow cytometry profiling

Yi, John S ; Rosa-Bray, Marilyn ; Staats, Janet ; Zakroysky, Pearl ; Chan, Cliburn ; Russo, Melissa A ; Dumbauld, Chelsae ; White, Scott ; Gierman, Todd ; Weinhold, Kent J ; Guptill, Jeffrey T Unutmaz, Derya

PloS one, 2019-12, Vol.14 (12), p.e0225512-e0225512 [Periódico revisado por pares]

United States: Public Library of Science

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7
Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE)
Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE)
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Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE)

Shekhar, Karthik ; Brodin, Petter ; Davis, Mark M. ; Chakraborty, Arup K.

Proceedings of the National Academy of Sciences - PNAS, 2014-01, Vol.111 (1), p.202-207 [Periódico revisado por pares]

United States: National Academy of Sciences

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8
PeacoQC: Peak‐based selection of high quality cytometry data
PeacoQC: Peak‐based selection of high quality cytometry data
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PeacoQC: Peak‐based selection of high quality cytometry data

Emmaneel, Annelies ; Quintelier, Katrien ; Sichien, Dorine ; Rybakowska, Paulina ; Marañón, Concepción ; Alarcón‐Riquelme, Marta E. ; Van Isterdael, Gert ; Van Gassen, Sofie ; Saeys, Yvan

Cytometry. Part A, 2022-04, Vol.101 (4), p.325-338 [Periódico revisado por pares]

Hoboken, USA: John Wiley & Sons, Inc

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9
cyCombine allows for robust integration of single-cell cytometry datasets within and across technologies
cyCombine allows for robust integration of single-cell cytometry datasets within and across technologies
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cyCombine allows for robust integration of single-cell cytometry datasets within and across technologies

Pedersen, Christina Bligaard ; Dam, Søren Helweg ; Barnkob, Mike Bogetofte ; Leipold, Michael D ; Purroy, Noelia ; Rassenti, Laura Z ; Kipps, Thomas J ; Nguyen, Jennifer ; Lederer, James Arthur ; Gohil, Satyen Harish ; Wu, Catherine J ; Olsen, Lars Rønn

Nature communications, 2022-03, Vol.13 (1), p.1698-1698, Article 1698 [Periódico revisado por pares]

England: Nature Publishing Group

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10
Automated biophysical classification of apoptotic pancreatic cancer cell subpopulations by using machine learning approaches with impedance cytometry
Automated biophysical classification of apoptotic pancreatic cancer cell subpopulations by using machine learning approaches with impedance cytometry
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Automated biophysical classification of apoptotic pancreatic cancer cell subpopulations by using machine learning approaches with impedance cytometry

Honrado, Carlos ; Salahi, Armita ; Adair, Sara J ; Moore, John H ; Bauer, Todd W ; Swami, Nathan S

Lab on a chip, 2022-09, Vol.22 (19), p.378-372 [Periódico revisado por pares]

England: Royal Society of Chemistry

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