Nature Communications (Jan 2016)

Label-free cell cycle analysis for high-throughput imaging flow cytometry

  • Thomas Blasi,
  • Holger Hennig,
  • Huw D. Summers,
  • Fabian J. Theis,
  • Joana Cerveira,
  • James O. Patterson,
  • Derek Davies,
  • Andrew Filby,
  • Anne E. Carpenter,
  • Paul Rees

DOI
https://doi.org/10.1038/ncomms10256
Journal volume & issue
Vol. 7, no. 1
pp. 1 – 9

Abstract

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Imaging flow cytometry enables high-throughput acquisition of fluorescence, brightfield and darkfield images of biological cells. Here, Blasi et al.demonstrate that applying machine learning algorithms on brightfield and darkfield images can detect cellular phenotypes without the need for fluorescent stains, enabling label-free assays.