Evidence map›Paper›PMID 34139168›Full record

ReviewCell systems2021

Single-cell image analysis to explore cell-to-cell heterogeneity in isogenic populations.

Mojca Mattiazzi Usaj, Clarence Hue Lok Yeung, Helena Friesen, Charles Boone, Brenda J Andrews

Abstract readReview
In one paragraph

Review in Cell systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

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  9. Isolation Techniques of Micro/Nano-Scaled Species for Biomedical Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mojca Mattiazzi UsajDepartment of Chemistry and Biology, Ryerson University, Toronto, ON M5B 2K3, Canada.
Clarence Hue Lok YeungThe Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada.
Helena FriesenThe Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada.
Charles BooneThe Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada; RIKEN Centre for Sustainable Resource Science, Wako, Saitama 351-0198, Japan.
Brenda J AndrewsThe Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada. Electronic address: brenda.andrews@utoronto.ca.

Funding

Mapping the reference genetic network of a eukaryotic cellR01HG005853 · NHGRI · UNIVERSITY OF TORONTO · PI ANDREWS, BRENDA JEAN, BOONE, CHARLES · 2010 to 2025
$7.6M
CIHR FDN-143264CIHR FDN-143265NHGRI NIH HHS R01 HG005853
6 · The paper itself

Abstract

Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from microbial cultures to individual cells in multicellular organisms. This phenotypic variability must be explained at a mechanistic level if biologists are to fully understand cellular function and address the genotype-to-phenotype relationship. Variability in single-cell phenotypes is obscured by bulk readouts or averaging of phenotypes from individual cells in a sample; thus, single-cell image analysis enables a higher resolution view of cellular function. Here, we consider examples of both small- and large-scale studies carried out with isogenic cell populations assessed by fluorescence microscopy, and we illustrate the advantages, challenges, and the promise of quantitative single-cell image analysis.

Indexed as

Biological Variation, PopulationSingle-Cell AnalysisMicroscopy, FluorescencePhenotypefluorescence microscopyhigh-content screeningphenotypic diversityphenotypic heterogeneitysingle-cell image analysis

Identifiers

PMID34139168
PMCPMC9112900

What OpenQuestion holds

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Registered trials

None linked

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.