ArticleMolecular biology of the cell2024
From pixels to phenotypes: Integrating image-based profiling with cell health data as BioMorph features improves interpretability.
Article in Molecular biology of the cell, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Cell Painting Identifies Phenotypic Clusters Associated with Anticancer Drug Responses in OVCAR-3 Ovarian Cancer Cells.International journal of molecular sciences · 2026Article
- CALIPERS: Cell cycle-aware live imaging for phenotyping experiments and regeneration studies.Nature communications · 2026Article
- Progress and new challenges in image-based profiling.Molecular systems biology · 2026Review
- Counting cells can accurately predict small-molecule bioactivity benchmarks.Nature communications · 2026Article
- Acquisition, quality control, and architecture of a large image dataset as a tool for in silico cell biological research.Materials today. Bio · 2025Article
- Computational prediction of mutagenicity through comprehensive cell painting analysis.Mutagenesis · 2025Article
- Prediction of cellular morphology changes under perturbations with a transcriptome-guided diffusion model.Nature communications · 2025Article
- Article
- Exploring NLRP3-related phenotypic fingerprints in human macrophages using Cell Painting assay.iScience · 2025Article
- Cell Painting: a decade of discovery and innovation in cellular imaging.Nature methods · 2025Review
- A Decade in a Systematic Review: The Evolution and Impact of Cell Painting.bioRxiv : the preprint server for biology · 2024Article
- Article
- Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA Drug-Induced Cardiotoxicity Rank.Journal of chemical information and modeling · 2024Article
- Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA DICTrank.bioRxiv : the preprint server for biology · 2023Article
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Authors and funding
6 authors.
Funding
Abstract
Cell Painting assays generate morphological profiles that are versatile descriptors of biological systems and have been used to predict in vitro and in vivo drug effects. However, Cell Painting features extracted from classical software such as CellProfiler are based on statistical calculations and often not readily biologically interpretable. In this study, we propose a new feature space, which we call BioMorph, that maps these Cell Painting features with readouts from comprehensive Cell Health assays. We validated that the resulting BioMorph space effectively connected compounds not only with the morphological features associated with their bioactivity but with deeper insights into phenotypic characteristics and cellular processes associated with the given bioactivity. The BioMorph space revealed the mechanism of action for individual compounds, including dual-acting compounds such as emetine, an inhibitor of both protein synthesis and DNA replication. Overall, BioMorph space offers a biologically relevant way to interpret the cell morphological features derived using software such as CellProfiler and to generate hypotheses for experimental validation.
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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.