ArticlePloS one2019
TISMorph: A tool to quantify texture, irregularity and spreading of single cells.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- Development of a universal imaging "phenome" using shape, appearance and motion (SAM) features and the SAM Phenotype Observation Tool (SPOT).Nature communications · 2026Article
- Deep learning-supported image quantification of epithelial cell shapes and its application to polycystic kidney disease.PLoS computational biology · 2026Article
- Single-cell morphodynamical trajectories enable prediction of gene expression accompanying cell state change.Cell systems · 2026Article
- Fast and interpretable quantification of biological shape heterogeneity via stratified Wasserstein kernel.PLoS computational biology · 2026Article
- Epistasis regulates genetic control of cardiac hypertrophy.Nature cardiovascular research · 2025Article
- Deciphering epistatic genetic regulation of cardiac hypertrophy.medRxiv : the preprint server for health sciences · 2025Article
- Morphometric analysis of actin networks.Molecular biology of the cell · 2024Article
- Quantification of bacterial shape using moment invariants enables distinguishing populations during cellular plasmolysis.MethodsX · 2024Article
- Epistasis regulates genetic control of cardiac hypertrophy.Research square · 2023Article
- Morphodynamical cell state description via live-cell imaging trajectory embedding.Communications biology · 2023Article
- Orthogonal outlier detection and dimension estimation for improved MDS embedding of biological datasets.Frontiers in bioinformatics · 2023Article
- Coordinated regulation of Cdc42ep1, actin, and septin filaments during neural crest cell migration.Frontiers in cell and developmental biology · 2023Article
- Article
- Insight into Mechanobiology: How Stem Cells Feel Mechanical Forces and Orchestrate Biological Functions.International journal of molecular sciences · 2019Review
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5 authors.
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Abstract
A number of recent studies have shown that cell shape and cytoskeletal texture can be used as sensitive readouts of the physiological state of the cell. However, utilization of this information requires the development of quantitative measures that can describe relevant aspects of cell shape. In this paper we develop a toolbox, TISMorph, that calculates a set of quantitative measures to address this need. Some of the measures introduced here have been used previously, while others are new and have desirable properties for shape and texture quantification of cells. These measures, broadly classifiable into the categories of textural, irregularity and spreading measures, are tested by using them to discriminate between osteosarcoma cell lines treated with different cytoskeletal drugs. We find that even though specific classification tasks often rely on a few measures, these are not the same between all classification tasks, thus requiring the use of the entire suite of measures for classification and discrimination. We provide detailed descriptions of the measures, as well as the TISMorph package to implement them. Quantitative morphological measures that capture different aspects of cell morphology will help enhance large-scale image-based quantitative analysis, which is emerging as a new field of biological data.
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