Evidence map›Paper›PMID 41479048›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Cell Painting Protocol to Characterize Morphological Profiles of Large Compound Collections Using the EU-OPENSCREEN Library.

Christopher Wolff, Martin Neuenschwander, Michelle Müller, Astrid Mühl, Jens Peter von Kries, Christopher Schmied, Edgar Specker

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Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Christopher WolffLeibniz-Forschungsinstitut für Molekulare Pharmakologie im Forschungsverbund Berlin e.V. (FMP), Campus Berlin-Buch, Berlin, Germany. wolff@fmp-berlin.de.
Martin NeuenschwanderLeibniz-Forschungsinstitut für Molekulare Pharmakologie im Forschungsverbund Berlin e.V. (FMP), Campus Berlin-Buch, Berlin, Germany.
Michelle MüllerLeibniz-Forschungsinstitut für Molekulare Pharmakologie im Forschungsverbund Berlin e.V. (FMP), Campus Berlin-Buch, Berlin, Germany.
Astrid MühlLeibniz-Forschungsinstitut für Molekulare Pharmakologie im Forschungsverbund Berlin e.V. (FMP), Campus Berlin-Buch, Berlin, Germany.
Jens Peter von KriesLeibniz-Forschungsinstitut für Molekulare Pharmakologie im Forschungsverbund Berlin e.V. (FMP), Campus Berlin-Buch, Berlin, Germany.
Christopher SchmiedEU-OPENSCREEN ERIC, Campus Berlin-Buch, Berlin, Germany. christopher.schmied@eu-openscreen.eu.
Edgar SpeckerLeibniz-Forschungsinstitut für Molekulare Pharmakologie im Forschungsverbund Berlin e.V. (FMP), Campus Berlin-Buch, Berlin, Germany. specker@fmp-berlin.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Morphological profiling with the Cell Painting assay started a new era in phenotypic screening approaches by harnessing comprehensive morphological profiles of cellular perturbations. This enables an unbiased characterization of the effects of small chemical compounds. We established and extensively validated a Cell Painting protocol to screen the compound libraries of the European initiative EU-OPENSCREEN ( www.eu-openscreen.eu ) in order to find robust and reproducible links between the known target or the pathway mechanism of each compound to the phenotypic profile. In this chapter, we describe the Cell Painting procedure, image analysis, and the downstream data processing procedures.

Indexed as

Drug DiscoveryHigh-Throughput Screening AssaysSmall Molecule LibrariesDrug Evaluation, PreclinicalHumansImage Processing, Computer-AssistedSmall Molecule LibrariesCell PaintingEU-OPENSCREEN libraryFluorescent dyesMorphological profiling

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Registered trials

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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.