Evidence map›Paper›PMID 39639168›Full record

ReviewNature methods2025

Cell Painting: a decade of discovery and innovation in cellular imaging.

Srijit Seal, Maria-Anna Trapotsi, Ola Spjuth, Shantanu Singh, Jordi Carreras-Puigvert, Nigel Greene, Andreas Bender, Anne E Carpenter

Erratum issuedAbstract readReview
In one paragraph

Review in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing 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

53 citing papers in PubMed.

  1. Review
  2. Algebraic Representation of Mitochondrial Dynamics.Bulletin of mathematical biology · 2026
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  3. Review
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  7. Review
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  12. Review
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  17. JACS Au · 2026
    Article
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  19. Article
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Srijit Seal *Broad Institute of MIT and Harvard, Cambridge, MA, USA. seal@broadinstitute.org.ORCID http://orcid.org/0000-0003-2790-8679
Maria-Anna Trapotsi *Imaging and Data Analytics, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, UK. marianna.trapotsi1@astrazeneca.com.ORCID http://orcid.org/0000-0002-9177-4241
Ola SpjuthDepartment of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.ORCID http://orcid.org/0000-0002-8083-2864
Shantanu SinghBroad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID http://orcid.org/0000-0003-3150-3025
Jordi Carreras-PuigvertDepartment of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Nigel GreeneImaging and Data Analytics, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Waltham, MA, USA.
Andreas BenderYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-6683-7546
Anne E CarpenterBroad Institute of MIT and Harvard, Cambridge, MA, USA. anne@broadinstitute.org.ORCID http://orcid.org/0000-0003-1555-8261

Funding

Extracting rich information from biological imagesR35GM122547 · NIGMS · BROAD INSTITUTE, INC. · PI Anne E. Carpenter · 2017 to 2026
$6.2M
NIGMS NIH HHS R35 GM122547
6 · The paper itself

Abstract

Modern quantitative image analysis techniques have enabled high-throughput, high-content imaging experiments. Image-based profiling leverages the rich information in images to identify similarities or differences among biological samples, rather than measuring a few features, as in high-content screening. Here, we review a decade of advancements and applications of Cell Painting, a microscopy-based cell-labeling assay aiming to capture a cell's state, introduced in 2013 to optimize and standardize image-based profiling. Cell Painting's ability to capture cellular responses to various perturbations has expanded owing to improvements in the protocol, adaptations for different perturbations, and enhanced methodologies for feature extraction, quality control, and batch-effect correction. Cell Painting is a versatile tool that has been used in various applications, alone or with other -omics data, to decipher the mechanism of action of a compound, its toxicity profile, and other biological effects. Future advances will likely involve computational and experimental techniques, new publicly available datasets, and integration with other high-content data types.

Indexed as

Image Processing, Computer-AssistedAnimalsHigh-Throughput Screening AssaysHumans

Identifiers

PMID39639168
PMCPMC11810604

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

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 Socratic graph.