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Cited by 396

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Microfluidics for flow cytometric analysis of cells and particles

Open access
Huh, Dongeun, Gu, Wei, Kamotani, Yoko, Grotberg, James B, Takayama, Shuichi·2005·Physiological Measurement

Abstract

This review describes recent developments in microfabricated flow cytometers and related microfluidic devices that can detect, analyze, and sort cells or particles. The high-speed analytical capabilities of flow cytometry depend on the cooperative use of microfluidics, optics and electronics. Along with the improvement of other components, replacement of conventional glass capillary-based fluidics with microfluidic sample handling systems operating in microfabricated structures enables volume- and power-efficient, inexpensive and flexible analysis of particulate samples. In this review, we present various efforts that take advantage of novel microscale flow phenomena and microfabrication techniques to build microfluidic cell analysis systems.

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Registry

Crossref · 10.1088/0967-3334/26/3/r02

Cites

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Metadata

Authors
Huh, D., Gu, W., Kamotani, Y., Grotberg, J. B., & Takayama, S.
Venue
Physiological Measurement
Published
2005-02-02
Volume
26
Issue
3
Pages
R73-R98
ISSN
  • 0967-3334 (ISSN-L)
  • 1361-6579
OpenAlex
W2098625432
Cited by
396
References
48
FWCI
19.03
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Microfluidics for flow cytometric analysis of cells and particles. https://app.cochat.ai/papers/10.1088/0967-3334/26/3/r02
The paper
Huh, D., Gu, W., Kamotani, Y., Grotberg, J. B., & Takayama, S. (2005). Microfluidics for flow cytometric analysis of cells and particles. Physiological Measurement. https://doi.org/10.1088/0967-3334/26/3/r02

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.