ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024
Profiling Dynamic Patterns of Single-Cell Motility.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Neutrophil migration in the lung is altered by alveolar collapse and stretch.bioRxiv : the preprint server for biology · 2026Article
- Cell-nanoplastics association impacts cell proliferation and motility.bioRxiv : the preprint server for biology · 2026Article
- Monocytes are biological sensors of aging and frailty in humans.bioRxiv : the preprint server for biology · 2026Article
- Acute priming using elevated fluid viscosity recovers 'bioRxiv : the preprint server for biology · 2026Article
- Methods to analyze cell migration data: fundamentals and practical guidelines.Nature methods · 2026Review
- Topographic cues regulate collective cell dynamics in curved nano/microgrooved tubular microchannels.Lab on a chip · 2025Article
- Deriving the A/B Cells Policy as a Robust Multi-Object Cell Pipeline for Time-Lapse Microscopy.International journal of molecular sciences · 2025Article
- Article
- Profiling Dynamic Patterns of Single-Cell Motility.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Quantitative morphological analysis ofApplied and environmental microbiology · 2024Article
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Cell motility plays an essential role in many biological processes as cells move and interact within their local microenvironments. Current methods for quantifying cell motility typically involve tracking individual cells over time, but the results are often presented as averaged values across cell populations. While informative, these ensemble approaches have limitations in assessing cellular heterogeneity and identifying generalizable patterns of single-cell behaviors, at baseline and in response to perturbations. In this study, CaMI is introduced, a computational framework designed to leverage the single-cell nature of motility data. CaMI identifies and classifies distinct spatio-temporal behaviors of individual cells, enabling robust classification of single-cell motility patterns in a large dataset (n = 74 253 cells). This framework allows quantification of spatial and temporal heterogeneities, determination of single-cell motility behaviors across various biological conditions and provides a visualization scheme for direct interpretation of dynamic cell behaviors. Importantly, CaMI reveals insights that conventional cell motility analyses may overlook, showcasing its utility in uncovering robust biological insights. Together, a multivariate framework is presented to classify emergent patterns of single-cell motility, emphasizing the critical role of cellular heterogeneity in shaping cell behaviors across populations.
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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 OpenQuestion graph.