The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Multidimensional Drug Profiling By Automated Microscopy
Abstract
We present a method for high-throughput cytological profiling by microscopy. Our system provides quantitative multidimensional measures of individual cell states over wide ranges of perturbations. We profile dose-dependent phenotypic effects of drugs in human cell culture with a titration-invariant similarity score (TISS). This method successfully categorized blinded drugs and suggested targets for drugs of uncertain mechanism. Multivariate single-cell analysis is a starting point for identifying relationships among drug effects at a systems level and a step toward phenotypic profiling at the single-cell level. Our methods will be useful for discovering the mechanism and predicting the toxicity of new drugs.
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“Most published HCS studies do not measure how cellular responses change as a function of compound dosage, nor do they treat cell count as an indicator of stress response14.”
From A statistical framework for high-content phenotypic profiling using cellular feature distributions (2022) · cites this paper as [14]
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CellProfiler: image analysis software for identifying and quantifying cell phenotypes
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Metadata
- Authors
- Perlman, Z. E., Slack, M. D., Feng, Y., Mitchison, T. J., Wu, L. F., & Altschuler, S. J.
- Affiliations
- Harvard University (US)
- Corresponding author
- Perlman, Zachary E.
- Slack, Michael D.
- Feng, Yan
- Wu, Lani F.
- Altschuler, Steven J.
- Venue
- Science
- Published
- 2004-11-12
- Volume
- 306
- Issue
- 5699
- Pages
- 1194-1198
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W1993669821
- Cited by
- 660
- References
- 29
- Citations by year
- 2026: 13 · 2025: 17 · 2024: 26 · 2023: 13 · 2022: 29 · 2021: 23 · 2020: 25 · 2019: 22 · 2018: 15 · 2017: 22 · 2016: 47 · 2015: 26 · 2014: 27 · 2013: 37 · 2012: 33
- FWCI
- 29.15
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (P01CA078048)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Keywords
- drug profiling, automated microscopy, phenotypic profiling, drug target identification, mechanism of action, drug toxicity prediction, single-cell analysis, human cell culture
- MeSH terms
- Automation, Cell Cycle, DNA, Dose-Response Relationship, Drug, Drug Evaluation, Preclinical, Fluorescent Dyes, HeLa Cells, Humans, Image Processing, Computer-Assisted, Microscopy, Fluorescence, Pharmacology, Phenotype, Statistics as Topic, Cluster Analysis, Toxicity Tests
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