ArticleGigaScience2017
A dataset of images and morphological profiles of 30 000 small-molecule treatments using the Cell Painting assay.
Article in GigaScience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 96 papers.
What it found
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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.
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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
96 citing papers in PubMed.
- Empowering chemical structures with biological insights for scalable phenotypic virtual screening.Bioinformatics (Oxford, England) · 2026Article
- Review
- A generative framework for predicting cellular morphological and transcriptomic perturbation responses.Cell reports methods · 2026Article
- Identifying and targeting abnormal mitochondrial localization associated with psychosis.bioRxiv : the preprint server for biology · 2026Article
- Transitive prediction of small-molecule function through alignment of high-content screening resources.Nature biotechnology · 2026Article
- Progress and new challenges in image-based profiling.Molecular systems biology · 2026Review
- Predicting DNA damage response using synthetic cell painting profiles and experimental analysis.iScience · 2026Article
- PhenoModel: A multimodal phenotypic drug design foundation model for discovering novel potential inhibitors of multiple cancer cells.Acta pharmaceutica Sinica. B · 2026Article
- Advancing Label-Free Imaging Through CARS Microscopy: From Signal Formation to Biological Interpretation.International journal of molecular sciences · 2026Review
- Counting cells can accurately predict small-molecule bioactivity benchmarks.Nature communications · 2026Article
- Large scale compound selection guided by cell painting reveals activity cliffs and functional relationships.Communications biology · 2026Article
- Cell Painting Protocol to Characterize Morphological Profiles of Large Compound Collections Using the EU-OPENSCREEN Library.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Systematic analysis of immune cell motility leveraging the open intravital microscopy database Immunemap.The EMBO journal · 2026Article
- PhenoProfiler: advancing phenotypic learning for image-based drug discovery.Nature communications · 2025Article
- Cell-DINO: Self-supervised image-based embeddings for cell fluorescent microscopy.PLoS computational biology · 2025Article
- Prediction of cellular morphology changes under perturbations with a transcriptome-guided diffusion model.Nature communications · 2025Article
- Article
- MGMG: Cell Morphology-Guided Molecule Generation for Drug Discovery.bioRxiv : the preprint server for biology · 2025Article
- Morphological profiling data resource enables prediction of chemical compound properties.iScience · 2025Article
- Representation of high-dimensional cell morphology and morphodynamics in 2D latent space.Physical biology · 2025Article
36 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors.
Funding
Abstract
Background: Large-scale image sets acquired by automated microscopy of perturbed samples enable a detailed comparison of cell states induced by each perturbation, such as a small molecule from a diverse library. Highly multiplexed measurements of cellular morphology can be extracted from each image and subsequently mined for a number of applications. Findings: This microscopy dataset includes 919 265 five-channel fields of view, representing 30 616 tested compounds, available at "The Cell Image Library" (CIL) repository. It also includes data files containing morphological features derived from each cell in each image, both at the single-cell level and population-averaged (i.e., per-well) level; the image analysis workflows that generated the morphological features are also provided. Quality-control metrics are provided as metadata, indicating fields of view that are out-of-focus or containing highly fluorescent material or debris. Lastly, chemical annotations are supplied for the compound treatments applied. Conclusions: Because computational algorithms and methods for handling single-cell morphological measurements are not yet routine, the dataset serves as a useful resource for the wider scientific community applying morphological (image-based) profiling. The dataset can be mined for many purposes, including small-molecule library enrichment and chemical mechanism-of-action studies, such as target identification. Integration with genetically perturbed datasets could enable identification of small-molecule mimetics of particular disease- or gene-related phenotypes that could be useful as probes or potential starting points for development of future therapeutics.
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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.