ArticleCommunications biology2023
Morphodynamical cell state description via live-cell imaging trajectory embedding.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Tracking cell fate through morphodynamics.Molecular systems biology · 2026Article
- Single-cell morphodynamics predict cell fate decisions during mucociliary epithelial differentiation.Molecular systems biology · 2026Article
- Single-cell morphodynamical trajectories enable prediction of gene expression accompanying cell state change.Cell systems · 2026Article
- Tumor-immune trajectory context connects static tissue architecture to clinical outcomes.bioRxiv : the preprint server for biology · 2026Article
- AI-Driven Innovations for Quality Control and Standardization: Future Strategies in Adipose-Derived Stem Cell Manufacturing.International journal of molecular sciences · 2026Review
- Trajectory Landscapes for Therapeutic Strategy Design in Agent-Based Tumor Microenvironment Models.IEEE control systems letters · 2026Article
- Quantifying the Single-Cell Morphological Landscape of Cellular Transdifferentiation through Force Field Reconstruction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- The Prolyl Isomerase PIN1 Affects Fibroblast Differentiation States and Cross-talk in Pancreatic Cancer.Cancer research · 2025Article
- Serial Imaging of Tumour and microEnvironment (SITE) platform for live-cellbioRxiv : the preprint server for biology · 2025Article
- Single-cell morphodynamics predict cell fate decisions during mucociliary epithelial differentiation.bioRxiv : the preprint server for biology · 2025Article
- Microenvironmental signals combine to induce non-additive molecular and phenotypic responses in mammary epithelial cells.iScience · 2025Article
- Development of label-free cell tracking for discrimination of the heterogeneous mesenchymal migration.PloS one · 2025Article
- Exploring heterogeneous cell population dynamics in different microenvironments by novel analytical strategy based on images.NPJ systems biology and applications · 2024Article
- Featurizing Koopman mode decomposition for robust forecasting.The Journal of chemical physics · 2024Article
- Perspective on quantitative phase imaging to improve precision cancer medicine.Journal of biomedical optics · 2024Article
- Machine learning inference of continuous single-cell state transitions during myoblast differentiation and fusion.Molecular systems biology · 2024Article
- Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, CaBiophysical reviews · 2024Review
- Mesenchymal cell migration on one-dimensional micropatterns.Frontiers in cell and developmental biology · 2024Review
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Authors and funding
5 authors.
Funding
Abstract
Time-lapse imaging is a powerful approach to gain insight into the dynamic responses of cells, but the quantitative analysis of morphological changes over time remains challenging. Here, we exploit the concept of "trajectory embedding" to analyze cellular behavior using morphological feature trajectory histories-that is, multiple time points simultaneously, rather than the more common practice of examining morphological feature time courses in single timepoint (snapshot) morphological features. We apply this approach to analyze live-cell images of MCF10A mammary epithelial cells after treatment with a panel of microenvironmental perturbagens that strongly modulate cell motility, morphology, and cell cycle behavior. Our morphodynamical trajectory embedding analysis constructs a shared cell state landscape revealing ligand-specific regulation of cell state transitions and enables quantitative and descriptive models of single-cell trajectories. Additionally, we show that incorporation of trajectories into single-cell morphological analysis enables (i) systematic characterization of cell state trajectories, (ii) better separation of phenotypes, and (iii) more descriptive models of ligand-induced differences as compared to snapshot-based analysis. This morphodynamical trajectory embedding is broadly applicable to the quantitative analysis of cell responses via live-cell imaging across many biological and biomedical applications.
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Registered trials
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