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Background fluorescence and spreading error are major contributors of variability in high-dimensional flow cytometry data visualization by t-distributed stochastic neighboring embedding
Cytometry Part A
◽
10.1002/cyto.a.23566
◽
2018
◽
Vol 93
(8)
◽
pp. 785-792
◽
Cited By ~ 10
Author(s):
Emilia Maria Cristina Mazza
◽
Jolanda Brummelman
◽
Giorgia Alvisi
◽
Alessandra Roberto
◽
Federica De Paoli
◽
...
Keyword(s):
Flow Cytometry
◽
Data Visualization
◽
High Dimensional
◽
Flow Cytometry Data
◽
Background Fluorescence
◽
Dimensional Flow
Download Full-text
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References
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
Cytometry Part A
◽
10.1002/cyto.a.22622
◽
2015
◽
Vol 87
(7)
◽
pp. 616-623
◽
Cited By ~ 7
Author(s):
Dong Ling Tong
◽
Graham R. Ball
◽
A. Graham Pockley
Keyword(s):
Flow Cytometry
◽
Disease Progression
◽
High Dimensional
◽
Flow Cytometry Data
◽
Clinical Phenotypes
◽
Dimensional Flow
◽
Computational Strategy
Download Full-text
High dimensional flow cytometry for comprehensive leukocyte immunophenotyping (CLIP) in translational research
Journal of Immunological Methods
◽
10.1016/j.jim.2010.06.010
◽
2011
◽
Vol 363
(2)
◽
pp. 245-261
◽
Cited By ~ 26
Author(s):
Angélique Biancotto
◽
John C. Fuchs
◽
Ann Williams
◽
Pradeep K. Dagur
◽
J. Philip McCoy
Keyword(s):
Flow Cytometry
◽
Translational Research
◽
High Dimensional
◽
Dimensional Flow
Download Full-text
Training Novices in Generation and Analysis of High‐Dimensional Human Cell Phospho‐Flow Cytometry Data
Current Protocols in Cytometry
◽
10.1002/cpcy.71
◽
2020
◽
Vol 93
(1)
◽
Author(s):
Caroline E. Roe
◽
Madeline J. Hayes
◽
Sierra M. Barone
◽
Jonathan M. Irish
Keyword(s):
Flow Cytometry
◽
Human Cell
◽
High Dimensional
◽
Flow Cytometry Data
Download Full-text
High-dimensional flow cytometry uncovers cell heterogeneity in the placental villus core: changes across gestation and in Fetal Growth Restriction (FGR).
Placenta
◽
10.1016/j.placenta.2021.07.282
◽
2021
◽
Vol 112
◽
pp. e88
Author(s):
Anna Boss
◽
Anna Brooks
◽
Larry Chamley
◽
Jo James
Keyword(s):
Flow Cytometry
◽
Fetal Growth
◽
Fetal Growth Restriction
◽
Growth Restriction
◽
High Dimensional
◽
Cell Heterogeneity
◽
Placental Villus
◽
Dimensional Flow
Download Full-text
Impact of Density Gradient Separation and Cryopreservation on High Dimensional Flow Cytometry
Clinical Immunology
◽
10.1016/j.clim.2010.03.392
◽
2010
◽
Vol 135
◽
pp. S130
Author(s):
Angelique Biancotto
◽
Christopher Fuchs
◽
Dagur Pradeep
◽
J. McCoy
Keyword(s):
Flow Cytometry
◽
Density Gradient
◽
High Dimensional
◽
Dimensional Flow
◽
Gradient Separation
◽
Density Gradient Separation
Download Full-text
Analysis of clinical flow cytometric immunophenotyping data by clustering on statistical manifolds: Treating flow cytometry data as high-dimensional objects
Cytometry Part B Clinical Cytometry
◽
10.1002/cyto.b.20435
◽
2009
◽
Vol 76B
(1)
◽
pp. 1-7
◽
Cited By ~ 30
Author(s):
William G. Finn
◽
Kevin M. Carter
◽
Raviv Raich
◽
Lloyd M. Stoolman
◽
Alfred O. Hero
Keyword(s):
Flow Cytometry
◽
High Dimensional
◽
Flow Cytometric Immunophenotyping
◽
Flow Cytometry Data
◽
Statistical Manifolds
◽
Flow Cytometric
Download Full-text
Unfold High-Dimensional Clouds for Exhaustive Gating of Flow Cytometry Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics
◽
10.1109/tcbb.2014.2321403
◽
2014
◽
Vol 11
(6)
◽
pp. 1045-1051
◽
Cited By ~ 4
Author(s):
Peng Qiu
Keyword(s):
Flow Cytometry
◽
High Dimensional
◽
Flow Cytometry Data
Download Full-text
High-Dimensional Flow Cytometry Analysis of Regulatory Receptors on Human T Cells, NK Cells, and NKT Cells
Methods in Molecular Biology - Translational Bioinformatics for Therapeutic Development
◽
10.1007/978-1-0716-0849-4_14
◽
2020
◽
pp. 255-290
Author(s):
Ryosuke Nakagawa
◽
Jason Brayer
◽
Nicole Restrepo
◽
James J. Mulé
◽
Adam W. Mailloux
Keyword(s):
Flow Cytometry
◽
T Cells
◽
Nk Cells
◽
Nkt Cells
◽
High Dimensional
◽
Flow Cytometry Analysis
◽
Dimensional Flow
◽
Human T Cells
Download Full-text
SWIFT—scalable clustering for automated identification of rare cell populations in large, high‐dimensional flow cytometry datasets, Part 2: Biological evaluation
Cytometry Part A
◽
10.1002/cyto.a.22445
◽
2014
◽
Vol 85
(5)
◽
pp. 422-433
◽
Cited By ~ 44
Author(s):
Tim R. Mosmann
◽
Iftekhar Naim
◽
Jonathan Rebhahn
◽
Suprakash Datta
◽
James S. Cavenaugh
◽
...
Keyword(s):
Flow Cytometry
◽
Biological Evaluation
◽
High Dimensional
◽
Cell Populations
◽
Automated Identification
◽
Dimensional Flow
◽
Scalable Clustering
Download Full-text
High‐Dimensional Data Analysis Algorithms Yield Comparable Results for Mass Cytometry and Spectral Flow Cytometry Data
Cytometry Part A
◽
10.1002/cyto.a.24016
◽
2020
◽
Vol 97
(8)
◽
pp. 824-831
◽
Cited By ~ 1
Author(s):
Laura Ferrer‐Font
◽
Johannes U. Mayer
◽
Samuel Old
◽
Ian F. Hermans
◽
Jonathan Irish
◽
...
Keyword(s):
Flow Cytometry
◽
Data Analysis
◽
High Dimensional Data
◽
High Dimensional
◽
Spectral Flow
◽
Mass Cytometry
◽
Flow Cytometry Data
◽
High Dimensional Data Analysis
Download Full-text
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