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The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.

A deep profiler's guide to cytometry

Open access
Bendall, Sean C., Nolan, Garry P., Roederer, Mario, Chattopadhyay, Pratip K.·2012·Trends in Immunology

Abstract

In recent years, advances in technology have provided us with tools to quantify the expression of multiple genes in individual cells. The ability to simultaneously measure multiple genes on the same cell is necessary to resolve the incredible diversity of cell subsets, as well as to define their function in the host. Fluorescence-based flow cytometry is the benchmark for this; with it, we can quantify 18 proteins per cell, at >10,000 cells per second. “Mass cytometry” is a new technology that promises to significantly extend these capabilities. Immunophenotyping by mass spectrometry provides the ability to measure more than three dozen proteins at a rate of 1,000 cells per second. We review these cytometric technologies, capable of high-content, high-throughput single-cell assays.

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Crossref · 10.1016/j.it.2012.02.010

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Metadata

Authors
Bendall, S. C., Nolan, G. P., Roederer, M., & Chattopadhyay, P. K.
Venue
Trends in Immunology
Publisher
Elsevier BV
Published
2012-07
Volume
33
Issue
7
Pages
323-332
ISSN
1471-4906 (ISSN-L)
OpenAlex
W2015671099
Cited by
656
References
47
FWCI
2.97
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A deep profiler's guide to cytometry. https://app.cochat.ai/papers/10.1016/j.it.2012.02.010
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Bendall, S. C., Nolan, G. P., Roederer, M., & Chattopadhyay, P. K. (2012). A deep profiler's guide to cytometry. Trends in Immunology. https://doi.org/10.1016/j.it.2012.02.010

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.