ArticleNature communications2023
The CellPhe toolkit for cell phenotyping using time-lapse imaging and pattern recognition.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- CALIPERS: Cell cycle-aware live imaging for phenotyping experiments and regeneration studies.Nature communications · 2026Article
- Celldetective, an AI-enhanced image analysis tool for unraveling dynamic cell interactions.eLife · 2026Article
- Single-cell morphodynamics predict cell fate decisions during mucociliary epithelial differentiation.Molecular systems biology · 2026Article
- Uncertainty-aware quantitative analysis of high-throughput live cell migration data.PLoS computational biology · 2026Article
- A Microwell Platform for Characterizing the Dynamic Response of Corneal Keratocytes to Biochemical and Biophysical Cues.Micromachines · 2026Article
- Kinemomics: spatiotemporal morphodynamic mapping of ventricular kinematic subpopulations in organotypic fetal heart slices.bioRxiv : the preprint server for biology · 2026Article
- Multidimensional data analysis and classification using SMIAL.Communications biology · 2026Article
- A modular platform for automated organoid culture and longitudinal imaging.Scientific reports · 2026Article
- Fast label-free live imaging with FlowVision reveals key principles of cancer cell arrest on endothelial monolayers.The EMBO journal · 2026Article
- Cardiac EndMT and EpiMT as a developmental continuum: integration of mechanical, metabolic, and epigenetic regulation.Frontiers in cell and developmental biology · 2026Review
- Methods to analyze cell migration data: fundamentals and practical guidelines.Nature methods · 2026Review
- From cells to pixels: A decision tree for designing bioimage analysis pipelines.Journal of microscopy · 2025Article
- Single-cell morphodynamics predict cell fate decisions during mucociliary epithelial differentiation.bioRxiv : the preprint server for biology · 2025Article
- Quantitative analysis of human umbilical vein endothelial cell morphology and tubulogenesis.Journal of microscopy · 2025Article
- CellPhePy: A python implementation of the CellPhe toolkit for automated cell phenotyping from microscopy time-lapse videos.Journal of microscopy · 2025Article
- Ptychographic analysis of human bone marrow-derived mesenchymal stem cell morphology: The impact of cell senescence.Journal of microscopy · 2025Article
- ESPRESSO: spatiotemporal omics based on organelle phenotyping.Nature methods · 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
- Exploring the Impact of Variability in Cell Segmentation and Tracking Approaches.Microscopy research and technique · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
With phenotypic heterogeneity in whole cell populations widely recognised, the demand for quantitative and temporal analysis approaches to characterise single cell morphology and dynamics has increased. We present CellPhe, a pattern recognition toolkit for the unbiased characterisation of cellular phenotypes within time-lapse videos. CellPhe imports tracking information from multiple segmentation and tracking algorithms to provide automated cell phenotyping from different imaging modalities, including fluorescence. To maximise data quality for downstream analysis, our toolkit includes automated recognition and removal of erroneous cell boundaries induced by inaccurate tracking and segmentation. We provide an extensive list of features extracted from individual cell time series, with custom feature selection to identify variables that provide greatest discrimination for the analysis in question. Using ensemble classification for accurate prediction of cellular phenotype and clustering algorithms for the characterisation of heterogeneous subsets, we validate and prove adaptability using different cell types and experimental conditions.
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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.