{"publication_status":"published","type":"journal_article","author":[{"last_name":"Bleile","id":"920a7385-7995-11ef-9bfd-8c434cd8f3c2","first_name":"Yossi","orcid":"0000-0002-4861-9174","full_name":"Bleile, Yossi"},{"first_name":"Pooja","full_name":"Yadav, Pooja","last_name":"Yadav"},{"full_name":"Koehl, Patrice","first_name":"Patrice","last_name":"Koehl"},{"first_name":"Florian","full_name":"Rehfeldt, Florian","last_name":"Rehfeldt"}],"file":[{"date_created":"2026-02-10T07:13:06Z","checksum":"3899d929ee9be0453c95524e49992d72","file_name":"2026_PloSCompBio_Bleile.pdf","relation":"main_file","file_id":"21204","date_updated":"2026-02-10T07:13:06Z","success":1,"access_level":"open_access","file_size":8908746,"content_type":"application/pdf","creator":"dernst"}],"language":[{"iso":"eng"}],"OA_place":"publisher","doi":"10.1371/journal.pcbi.1013890","corr_author":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Public Library of Science","intvolume":" 22","year":"2026","related_material":{"link":[{"url":"https://github.com/yossibokorbleile/correa","relation":"software"}]},"day":"28","date_published":"2026-01-28T00:00:00Z","oa_version":"Published Version","DOAJ_listed":"1","PlanS_conform":"1","publication_identifier":{"issn":["1553-7358"]},"pmid":1,"title":"Persistence diagrams as morphological signatures of cells: A method to measure and compare cells within a population","article_processing_charge":"Yes","tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png"},"department":[{"_id":"HeEd"}],"_id":"21115","publication":"PLoS Computational Biology","oa":1,"volume":22,"ddc":["000"],"date_created":"2026-01-30T10:36:32Z","status":"public","quality_controlled":"1","abstract":[{"lang":"eng","text":"Quantifying cell morphology is central to understanding cellular regulation, fate, and heterogeneity, yet conventional image-based analyses often struggle with diverse or irregular shapes. We present a computational framework that uses topological data analysis to characterise and compare single-cell morphologies from fluorescence microscopy. Each cell is represented by its contour together with the position of its nucleus, from which we construct a filtration based on a radial distance function and derive a persistence diagram encoding the shape’s topological evolution. The similarity between two cells is quantified using the 2-Wasserstein distance between their diagrams, yielding a shape distance we call the PH distance. We apply this method to two representative experimental systems—primary human mesenchymal stem cells (hMSCs) and HeLa cells—and show that PH distances enable the detection of outliers in those systems, the identification of sub-populations, and the quantification of shape heterogeneity. We benchmark PH against three established contour-based distances (aspect ratio, Fourier descriptors, and elastic shape analysis) and show that PH offers better separation between cell types and greater robustness when clustering heterogeneous populations. Together, these results demonstrate that persistent-homology-based signatures provide a principled and sensitive approach for analysing cell morphology in settings where traditional geometric or image-based descriptors are insufficient."}],"has_accepted_license":"1","month":"01","external_id":{"pmid":["41604421"]},"article_type":"original","acknowledgement":"We thank Stephan Huckemann, Katharine Turner, Benjamin Eltzner, Stephan Tillmann, Fariza Rashid, Vanessa Robins, and Lamiae Azizi for many useful discussions at various stages of this project. FR and PY gratefully acknowledge Matthias Weiss (Experimental Physics I, University of Bayreuth, Germany) for granting access to cell culture and laboratories, as well as funding consumables and the fruitful discussion that contributed to this work. For open access purposes, the author has applied a CC BY public copyright license to any author-accepted manuscript version arising from this submission.","OA_type":"gold","scopus_import":"1","file_date_updated":"2026-02-10T07:13:06Z","article_number":"e1013890","citation":{"mla":"Bleile, Yossi, et al. “Persistence Diagrams as Morphological Signatures of Cells: A Method to Measure and Compare Cells within a Population.” PLoS Computational Biology, vol. 22, e1013890, Public Library of Science, 2026, doi:10.1371/journal.pcbi.1013890.","short":"Y. Bleile, P. Yadav, P. Koehl, F. Rehfeldt, PLoS Computational Biology 22 (2026).","ama":"Bleile Y, Yadav P, Koehl P, Rehfeldt F. Persistence diagrams as morphological signatures of cells: A method to measure and compare cells within a population. PLoS Computational Biology. 2026;22. doi:10.1371/journal.pcbi.1013890","apa":"Bleile, Y., Yadav, P., Koehl, P., & Rehfeldt, F. (2026). Persistence diagrams as morphological signatures of cells: A method to measure and compare cells within a population. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1013890","ieee":"Y. Bleile, P. Yadav, P. Koehl, and F. Rehfeldt, “Persistence diagrams as morphological signatures of cells: A method to measure and compare cells within a population,” PLoS Computational Biology, vol. 22. Public Library of Science, 2026.","chicago":"Bleile, Yossi, Pooja Yadav, Patrice Koehl, and Florian Rehfeldt. “Persistence Diagrams as Morphological Signatures of Cells: A Method to Measure and Compare Cells within a Population.” PLoS Computational Biology. Public Library of Science, 2026. https://doi.org/10.1371/journal.pcbi.1013890.","ista":"Bleile Y, Yadav P, Koehl P, Rehfeldt F. 2026. Persistence diagrams as morphological signatures of cells: A method to measure and compare cells within a population. PLoS Computational Biology. 22, e1013890."},"date_updated":"2026-02-12T14:23:54Z"}