Cited by 662Cell Image Analysis TechniquesSingle-cell and spatial transcriptomicsComputational Drug Discovery Methods

Multidimensional Drug Profiling By Automated Microscopy

Perlman, Zachary E., Slack, Michael D., Feng, Yan, Mitchison, Timothy J., Wu, Lani F., Altschuler, Steven J.·2004·Science

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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Crossref · 10.1126/science.1100709

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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 response.

    “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.”

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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
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › 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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