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Mass Cytometry

Overview of attention for book
Cover of 'Mass Cytometry'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Introduction
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    Chapter 1 Setting Up Mass Cytometry in a Shared Resource Lab Environment
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    Chapter 2 Citizenship and Money: Historical Snapshots
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    Chapter 2 Acquisition, Processing, and Quality Control of Mass Cytometry Data
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    Chapter 3 To Sell or Not to Sell: The Ethics of ius pecuniae
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    Chapter 3 Visualization of Mass Cytometry Signal Background to Enable Optimal Core Panel Customization and Signal Threshold Gating
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    Chapter 4 Method for Tagging Antibodies with Metals for Mass Cytometry Experiments
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    Chapter 4 A Classification of Investment-Based Citizenship Programmes
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    Chapter 5 ‘Long-Distance Citizens’: Strategies and Interests of States, Companies and Individuals in the Global Race for Wealth
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    Chapter 5 Scalable Conjugation and Characterization of Immunoglobulins with Stable Mass Isotope Reporters for Single-Cell Mass Cytometry Analysis
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    Chapter 6 Ius pecuniae in a Multilevel System: The European Experience
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    Chapter 6 Titration of Mass Cytometry Reagents
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    Chapter 7 Surface Barcoding of Live PBMC for Multiplexed Mass Cytometry
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    Chapter 8 Automated Cell Processing for Mass Cytometry Experiments
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    Chapter 9 Live Cell Barcoding for Efficient Analysis of Small Samples by Mass Cytometry
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    Chapter 10 Staining of Phosphorylated Signalling Markers Protocol for Mass Cytometry
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    Chapter 11 Multiplex MHC Class I Tetramer Combined with Intranuclear Staining by Mass Cytometry
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    Chapter 12 Analysis of the Murine Bone Marrow Hematopoietic System Using Mass and Flow Cytometry
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    Chapter 13 Mass Cytometric Cell Cycle Analysis
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    Chapter 14 Picturing Polarized Myeloid Phagocytes and Regulatory Cells by Mass Cytometry
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    Chapter 15 Quantitative Measurement of Cell-Nanoparticle Interactions Using Mass Cytometry
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    Chapter 16 Data-Driven Flow Cytometry Analysis
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    Chapter 17 Analysis of Mass Cytometry Data
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    Chapter 18 Analysis of High-Dimensional Phenotype Data Generated by Mass Cytometry or High-Dimensional Flow Cytometry
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    Chapter 19 Computational Analysis of High-Dimensional Mass Cytometry Data from Clinical Tissue Samples
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    Chapter 20 Supervised Machine Learning with CITRUS for Single Cell Biomarker Discovery
Attention for Chapter 12: Analysis of the Murine Bone Marrow Hematopoietic System Using Mass and Flow Cytometry
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  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

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Chapter title
Analysis of the Murine Bone Marrow Hematopoietic System Using Mass and Flow Cytometry
Chapter number 12
Book title
Mass Cytometry
Published in
Methods in molecular biology, May 2019
DOI 10.1007/978-1-4939-9454-0_12
Pubmed ID
Book ISBNs
978-1-4939-9453-3, 978-1-4939-9454-0
Authors

Thomas M. Ashhurst, Darren A. Cox, Adrian L. Smith, Nicholas J. C. King, Ashhurst, Thomas M., Cox, Darren A., Smith, Adrian L., King, Nicholas J. C.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Professor 3 21%
Student > Ph. D. Student 3 21%
Student > Master 2 14%
Researcher 2 14%
Other 1 7%
Other 2 14%
Unknown 1 7%
Readers by discipline Count As %
Immunology and Microbiology 4 29%
Chemistry 2 14%
Agricultural and Biological Sciences 2 14%
Unspecified 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Other 2 14%
Unknown 2 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 June 2020.
All research outputs
#14,449,295
of 23,146,350 outputs
Outputs from Methods in molecular biology
#4,259
of 13,275 outputs
Outputs of similar age
#193,546
of 350,843 outputs
Outputs of similar age from Methods in molecular biology
#18
of 43 outputs
Altmetric has tracked 23,146,350 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,275 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 64% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 350,843 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.