ArticleScience advances2020
Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data.
Article in Science advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 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.
The trial behind it
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
66 citing papers in PubMed.
- Joint inference of paired dynamical gene regulatory networks reveals distinct cell-state landscapes of neutrophil reprogramming.bioRxiv : the preprint server for biology · 2026Article
- Role of epithelial-mesenchymal transition (EMT) in malignancies: current status and future prospects.Signal transduction and targeted therapy · 2026Review
- Proteomic Stability and Ex Vivo Compatibility of a Processed Phospholipoproteic Secretome-Derived Formulation.Pharmaceutics · 2026Article
- Cellular Morphometric Analysis (CellMorph)-a comprehensive imaging-based tool for quantifying cellular phenotype heterogeneity and dynamics across biological processes.The FEBS journal · 2026Article
- Single-cell morphodynamical trajectories enable prediction of gene expression accompanying cell state change.Cell systems · 2026Article
- Progress and new challenges in image-based profiling.Molecular systems biology · 2026Review
- Partial EMT Drives Persistent Collective Migration via Collision Guidance in Heterogeneous Populations.bioRxiv : the preprint server for biology · 2026Article
- Single cell snapshot analyses under proper representation reveal that epithelial-mesenchymal transition couples at G1 and G2/M.Communications biology · 2026Article
- Quantifying the Single-Cell Morphological Landscape of Cellular Transdifferentiation through Force Field Reconstruction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Building dynamical models of multi-step state transitions from single cell gene expression trajectories.bioRxiv : the preprint server for biology · 2025Article
- Generalizable morphological profiling of cells by interpretable unsupervised learning.Nature communications · 2025Article
- A morphology-based machine learning model for scoring epithelial-mesenchymal plasticity using organelle dynamics.Communications biology · 2025Article
- Label-Free Longitudinal Imaging of Single Cell Drug Response with a 3D-Printed Cell Culture Platform.Analytical chemistry · 2025Article
- Image-Based Profiling in Live Cells Using Live Cell Painting.Bio-protocol · 2025Article
- Single extracellular vesicle imaging via rolling circle amplification-expansion microscopy.Nature communications · 2025Article
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- Live-cell painting: Image-based profiling in live cells using acridine orange.Molecular biology of the cell · 2025Article
- Temporal and spatial omics technologies for 4D profiling.Nature methods · 2025Review
- Deep learning identifies heterogeneous subpopulations in breast cancer cell lines.npj biomedical innovations · 2025Article
6 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
10 authors.
Funding
Abstract
Recent advances in single-cell techniques catalyze an emerging field of studying how cells convert from one phenotype to another, in a step-by-step process. Two grand technical challenges, however, impede further development of the field. Fixed cell-based approaches can provide snapshots of high-dimensional expression profiles but have fundamental limits on revealing temporal information, and fluorescence-based live-cell imaging approaches provide temporal information but are technically challenging for multiplex long-term imaging. We first developed a live-cell imaging platform that tracks cellular status change through combining endogenous fluorescent labeling that minimizes perturbation to cell physiology and/or live-cell imaging of high-dimensional cell morphological and texture features. With our platform and an A549 VIM-RFP epithelial-to-mesenchymal transition (EMT) reporter cell line, live-cell trajectories reveal parallel paths of EMT missing from snapshot data due to cell-cell dynamic heterogeneity. Our results emphasize the necessity of extracting dynamical information of phenotypic transitions from multiplex live-cell imaging.
Identifiers
What Socratic holds
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.