ArticleCell systems2017
Systematic Quantification of Population Cell Death Kinetics in Mammalian Cells.
Article in Cell systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.
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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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Who cites it
73 citing papers in PubMed.
- Article
- A peptide-based screen for cell death inhibitors identifies the cytoprotective compound CDL36.bioRxiv : the preprint server for biology · 2026Article
- Cell size modulates ferroptosis susceptibility.eLife · 2026Article
- A systematic study of parameter sharing strategies in multi-task learning for drug synergy and sensitivity prediction.Journal of computer-aided molecular design · 2026Article
- A harmless-to-harmful switchable and spatiotemporally activated nano-CRISPR hierarchically amplifies ferroptosis in melanoma.Cell reports. Medicine · 2026Article
- A scalable multimodal graph neural network for drug combination response prediction.Molecular diversity · 2026Article
- Dissecting Complex Interactions Between Ferroptosis and the Proteasome.bioRxiv : the preprint server for biology · 2026Article
- Cell size modulates ferroptosis susceptibility.bioRxiv : the preprint server for biology · 2026Article
- UniSyn: a multi-modal framework with knowledge transfer for anti-cancer drug synergy prediction.Genome biology · 2026Article
- PAIRWISE: Deep Learning-based Prediction of Effective Personalized Drug Combinations in Cancer.Research square · 2026Article
- Cell Population Dynamics Informed by Cell-Cycle Regulation: A Deterministic Modeling Toolkit.Computational and structural biotechnology journal · 2026Review
- Remodeling the tumor immune microenvironment: mechanisms of crosstalk between regulated cell death macrophages.Frontiers in immunology · 2026Review
- A review of deep learning approaches for drug synergy prediction in cancer.npj drug discovery · 2025Review
- Defining the Antitumor Mechanism of Action of a Clinical-stage Compound as a Selective Degrader of the Nuclear Pore Complex.Cancer discovery · 2025Article
- Tegavivint triggers TECR-dependent nonapoptotic cancer cell death.Nature chemical biology · 2025Article
- Article
- HIG-Syn: a hypergraph and interaction-aware multigranularity network for predicting synergistic drug combinations.Bioinformatics (Oxford, England) · 2025Article
- Comprehensive Analysis of Drug Response using the FLICK Assay.Journal of visualized experiments : JoVE · 2025Article
- Deep learning-based image classification reveals heterogeneous execution of cell death fates during viral infection.Molecular biology of the cell · 2025Article
- MEDUSA for Identifying Death Regulatory Genes in Chemo-genetic Profiling Data.Journal of visualized experiments : JoVE · 2025Article
13 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors.
Funding
Abstract
Cytotoxic compounds are important drugs and research tools. Here, we introduce a method, scalable time-lapse analysis of cell death kinetics (STACK), to quantify the kinetics of compound-induced cell death in mammalian cells at the population level. STACK uses live and dead cell markers, high-throughput time-lapse imaging, and mathematical modeling to determine the kinetics of population cell death over time. We used STACK to profile the effects of over 1,800 bioactive compounds on cell death in two human cancer cell lines, resulting in a large and freely available dataset. 79 potent lethal compounds common to both cell lines caused cell death with widely divergent kinetics. 13 compounds triggered cell death within hours, including the metallophore zinc pyrithione. Mechanistic studies demonstrated that this rapid onset lethal phenotype was caused in human cancer cells by metabolic disruption and ATP depletion. These results provide the first comprehensive survey of cell death kinetics and analysis of rapid-onset lethal compounds.
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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 Socratic graph.