ArticleNature communications2016
Label-free cell cycle analysis for high-throughput imaging flow cytometry.
Article in Nature communications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
109 citing papers in PubMed.
- Image cytometry and kinetic modelling reveal amendment-associated differences in microbial cell state and apparent PAH degradation potential.Archives of microbiology · 2026Article
- Article
- Single-pixel imaging flow cytometry for biomedical research.Inflammation and regeneration · 2025Review
- Three-dimensional forward-scattering imaging flow cytometry system for single-cell analysis.APL photonics · 2025Article
- Cellular elasticity drives mechano-adaptation against fluid shear stress.Journal of cell science · 2025Article
- Model-based inference of cell cycle dynamics captures alterations of the DNA replication programme.PLoS computational biology · 2025Article
- Label-Free Cancer Detection Methods Based on Biophysical Cell Phenotypes.Bioengineering (Basel, Switzerland) · 2025Review
- A dual-branch deep learning network for circulating tumor cells classification.Journal of translational medicine · 2025Article
- Imaging Flow Cytometry as a Molecular Biology Tool: From Cell Morphology to Molecular Mechanisms.International journal of molecular sciences · 2025Review
- Multi-contrast machine learning improves schistosomiasis diagnostic performance.PLoS neglected tropical diseases · 2025Article
- Predicting cell cycle stage from 3D single-cell nuclear-stained images.Life science alliance · 2025Article
- AI-driven 3D bioprinting for regenerative medicine: From bench to bedside.Bioactive materials · 2025Review
- Imaging flow cytometry with a real-time throughput beyond 1,000,000 events per second.Light, science & applications · 2025Article
- Imaging flow cytometry as a novel approach for the diagnosis of heparin-induced thrombocytopenia.British journal of haematology · 2025Article
- Neuromorphic-enabled video-activated cell sorting.Nature communications · 2024Article
- Review
- Systematic data analysis pipeline for quantitative morphological cell phenotyping.Computational and structural biotechnology journal · 2024Review
- Label-free spatiotemporal decoding of single-cell fate via acoustic driven 3D tomography.Materials today. Bio · 2024Article
- Single-cell laser emitting cytometry for label-free nucleolus fingerprinting.Nature communications · 2024Article
- Stain-Free Approach to Determine and Monitor Cell Heath Using Supervised and Unsupervised Image-Based Deep Learning.Journal of pharmaceutical sciences · 2024Article
49 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Imaging flow cytometry combines the high-throughput capabilities of conventional flow cytometry with single-cell imaging. Here we demonstrate label-free prediction of DNA content and quantification of the mitotic cell cycle phases by applying supervised machine learning to morphological features extracted from brightfield and the typically ignored darkfield images of cells from an imaging flow cytometer. This method facilitates non-destructive monitoring of cells avoiding potentially confounding effects of fluorescent stains while maximizing available fluorescence channels. The method is effective in cell cycle analysis for mammalian cells, both fixed and live, and accurately assesses the impact of a cell cycle mitotic phase blocking agent. As the same method is effective in predicting the DNA content of fission yeast, it is likely to have a broad application to other cell types.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.