ArticleThe FEBS journal2026
Cellular Morphometric Analysis (CellMorph)-a comprehensive imaging-based tool for quantifying cellular phenotype heterogeneity and dynamics across biological processes.
Article in The FEBS journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Understanding eukaryotic cell morphometry is fundamental to cell biology, as cells exhibit a broad range of sizes and shapes during processes such as senescence, cell death, mitosis, and migration. Dynamic changes in subcellular compartments and protein distribution also occur, impacting cytoplasmic and nuclear characteristics. Traditional measurement methods are often limited, highlighting the need for alternatives that comprehensively integrate data from both the cytosol and nuclei while tracking individual live cells over time. To address these limitations, we developed Cellular Morphometric Analysis (CellMorph), a novel tool designed to objectively assess multiple features of individual eukaryotic cells, including cell size, shape, cytosolic staining, and morphometry. CellMorph can analyze bright-field and fluorescent images, accommodating both nonstained cells and those expressing fluorescent reporters or chromogenic labels. We validated the tool using various cellular models and specific staining protocols that target fundamental processes such as apoptosis, autophagy, and senescence. CellMorph captures the intricate heterogeneity within cell populations by providing a multidimensional perspective on individual cellular features and their differential responses to various stresses. This capability to track phenotypic changes over time makes CellMorph particularly valuable for studying dynamic cellular responses. Detailed morphometric data are essential for investigating cellular behavior in pathogenic processes and responses to stressors, including therapies or environmental changes. By integrating multiple parameters, CellMorph represents a significant advancement in cell biology, offering researchers a powerful tool to explore the complexities of cellular morphometry effectively.
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Registered trials
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