{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T06:16:58Z","timestamp":1772173018860,"version":"3.50.1"},"reference-count":68,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2022,6,13]],"date-time":"2022-06-13T00:00:00Z","timestamp":1655078400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1150645"],"award-info":[{"award-number":["1150645"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1533708"],"award-info":[{"award-number":["1533708"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1533708"],"award-info":[{"award-number":["1533708"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1553228"],"award-info":[{"award-number":["1553228"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004917","name":"CPRIT","doi-asserted-by":"crossref","award":["RR140073"],"award-info":[{"award-number":["RR140073"]}],"id":[{"id":"10.13039\/100004917","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["RO1DE026677"],"award-info":[{"award-number":["RO1DE026677"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["RO1DE031477"],"award-info":[{"award-number":["RO1DE031477"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"UT Rising STAR"},{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1250104"],"award-info":[{"award-number":["1250104"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>\n                    We introduce cytoNet, a cloud-based tool to characterize cell populations from microscopy images. cytoNet quantifies spatial topology and functional relationships in cell communities using principles of network science. Capturing multicellular dynamics through graph features, cytoNet also evaluates the effect of cell-cell interactions on individual cell phenotypes. We demonstrate cytoNet\u2019s capabilities in four case studies: 1) characterizing the temporal dynamics of neural progenitor cell communities during neural differentiation, 2) identifying communities of pain-sensing neurons\n                    <jats:italic>in vivo<\/jats:italic>\n                    , 3) capturing the effect of cell community on endothelial cell morphology, and 4) investigating the effect of laminin \u03b14 on perivascular niches in adipose tissue. The analytical framework introduced here can be used to study the dynamics of complex cell communities in a quantitative manner, leading to a deeper understanding of environmental effects on cellular behavior. The versatile, cloud-based format of cytoNet makes the image analysis framework accessible to researchers across domains.\n                  <\/jats:p>","DOI":"10.1371\/journal.pcbi.1009846","type":"journal-article","created":{"date-parts":[[2022,6,13]],"date-time":"2022-06-13T13:47:46Z","timestamp":1655128066000},"page":"e1009846","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":9,"title":["cytoNet: Spatiotemporal network analysis of cell communities"],"prefix":"10.1371","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7315-8261","authenticated-orcid":true,"given":"Arun S.","family":"Mahadevan","sequence":"first","affiliation":[]},{"given":"Byron L.","family":"Long","sequence":"additional","affiliation":[]},{"given":"Chenyue W.","family":"Hu","sequence":"additional","affiliation":[]},{"given":"David T.","family":"Ryan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1264-5290","authenticated-orcid":true,"given":"Nicolas E.","family":"Grandel","sequence":"additional","affiliation":[]},{"given":"George L.","family":"Britton","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8095-184X","authenticated-orcid":true,"given":"Marisol","family":"Bustos","sequence":"additional","affiliation":[]},{"given":"Maria A.","family":"Gonzalez Porras","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9105-0892","authenticated-orcid":true,"given":"Katerina","family":"Stojkova","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4777-2847","authenticated-orcid":true,"given":"Andrew","family":"Ligeralde","sequence":"additional","affiliation":[]},{"given":"Hyeonwi","family":"Son","sequence":"additional","affiliation":[]},{"given":"John","family":"Shannonhouse","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3509-3054","authenticated-orcid":true,"given":"Jacob T.","family":"Robinson","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5679-2268","authenticated-orcid":true,"given":"Aryeh","family":"Warmflash","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8766-7390","authenticated-orcid":true,"given":"Eric M.","family":"Brey","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6677-5656","authenticated-orcid":true,"given":"Yu Shin","family":"Kim","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1737-9208","authenticated-orcid":true,"given":"Amina A.","family":"Qutub","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2022,6,13]]},"reference":[{"key":"pcbi.1009846.ref001","article-title":"AI-driven Deep Visual Proteomics defines cell identity and heterogeneity","author":"A Mund","year":"2021","journal-title":"bioRxiv"},{"issue":"5","key":"pcbi.1009846.ref002","doi-asserted-by":"crossref","DOI":"10.1016\/j.cell.2020.07.005","article-title":"Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front","volume":"182","author":"CM Sch\u00fcrch","year":"2020","journal-title":"Cell"},{"issue":"10","key":"pcbi.1009846.ref003","doi-asserted-by":"crossref","first-page":"987","DOI":"10.1038\/s41592-019-0548-y","article-title":"High-definition spatial transcriptomics for in situ tissue profiling","volume":"16","author":"S Vickovic","year":"2019","journal-title":"Nature Methods"},{"issue":"6401","key":"pcbi.1009846.ref004","article-title":"Multiplexed protein maps link subcellular organization to cellular states","volume":"361","author":"G Gut","year":"2018","journal-title":"Science"},{"issue":"7751","key":"pcbi.1009846.ref005","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1038\/s41586-019-1049-y","article-title":"Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+","volume":"568","author":"CHL Eng","year":"2019","journal-title":"Nature"},{"issue":"6340","key":"pcbi.1009846.ref006","article-title":"A subcellular map of the human proteome","volume":"356","author":"PJ Thul","year":"2017","journal-title":"Science"},{"issue":"3","key":"pcbi.1009846.ref007","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1038\/nn.4502","article-title":"Network neuroscience","volume":"20","author":"DS Bassett","year":"2017","journal-title":"Nature Neuroscience"},{"issue":"9","key":"pcbi.1009846.ref008","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1038\/s41583-018-0038-8","article-title":"On the nature and use of models in network neuroscience","volume":"19","author":"DS Bassett","year":"2018","journal-title":"Nature Reviews Neuroscience"},{"issue":"1","key":"pcbi.1009846.ref009","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1145\/2960404","article-title":"Cell-graphs","volume":"60","author":"B Yener","year":"2016","journal-title":"Communications of the ACM"},{"key":"pcbi.1009846.ref010","author":"AA Qutub","year":"2013","journal-title":"inventorsAutomated method for measuring, classifying, and matching the dynamics and information passing of single objects within one or more images"},{"key":"pcbi.1009846.ref011","first-page":"254","volume-title":"Computational Bioengineering","author":"CRC Press","year":"2015"},{"key":"pcbi.1009846.ref012","article-title":"Living Neural Networks: Dynamic Network Analysis of Developing Neural Progenitor Cells","author":"AS Mahadevan","year":"2018","journal-title":"bioRxiv"},{"key":"pcbi.1009846.ref013","article-title":"histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data","author":"D Schapiro","year":"2017","journal-title":"Nature Methods"},{"issue":"7263","key":"pcbi.1009846.ref014","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1038\/nature08282","article-title":"Population context determines cell-to-cell variability in endocytosis and virus infection","volume":"461","author":"B Snijder","year":"2009","journal-title":"Nature"},{"key":"pcbi.1009846.ref015","first-page":"8","article-title":"Single-cell analysis of population context advances RNAi screening at multiple levels","author":"B Snijder","year":"2012","journal-title":"Molecular Systems Biology"},{"issue":"4","key":"pcbi.1009846.ref016","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1016\/j.cels.2018.09.001","article-title":"Multivariate Control of Transcript to Protein Variability in Single Mammalian Cells","volume":"7","author":"D Popovic","year":"2018","journal-title":"Cell Systems"},{"key":"pcbi.1009846.ref017","article-title":"The Tumor Profiler Study: integrated, multi-omic, functional tumor profiling for clinical decision support","author":"A Irmisch","year":"2021","journal-title":"Cancer Cell"},{"key":"pcbi.1009846.ref018","author":"F Rose","year":"2019","journal-title":"PySpacell: A Python Package for Spatial Analysis of Cell Images. Cytometry Part A"},{"issue":"5","key":"pcbi.1009846.ref019","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1038\/nmeth.4636","article-title":"SpatialDE: Identification of spatially variable genes","volume":"15","author":"V Svensson","year":"2018","journal-title":"Nature Methods"},{"issue":"5","key":"pcbi.1009846.ref020","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1038\/nmeth.4634","article-title":"Identification of spatial expression trends in single-cell gene expression data","volume":"15","author":"D Edsg\u00e4rd","year":"2018","journal-title":"Nature Methods"},{"issue":"3","key":"pcbi.1009846.ref021","doi-asserted-by":"crossref","DOI":"10.1016\/j.celrep.2020.107523","article-title":"CytoMAP: A Spatial Analysis Toolbox Reveals Features of Myeloid Cell Organization in Lymphoid Tissues","volume":"31","author":"CR Stoltzfus","year":"2020","journal-title":"Cell Reports"},{"key":"pcbi.1009846.ref022","article-title":"Mapping cell structure across scales by fusing protein images and interactions","author":"Y Qin","year":"2020","journal-title":"bioRxiv"},{"issue":"1","key":"pcbi.1009846.ref023","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1038\/nrn2759","article-title":"Mechanisms underlying spontaneous patterned activity in developing neural circuits","volume":"11","author":"AG Blankenship","year":"2010","journal-title":"Nature reviews Neuroscience"},{"key":"pcbi.1009846.ref024","first-page":"E1524","article-title":"Neural progenitors organize in small-world networks to promote cell proliferation","volume":"110","author":"S Malmersj\u00f6","year":"2013","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"},{"key":"pcbi.1009846.ref025","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.neuron.2008.02.014","article-title":"Oscillations in Notch Signaling Regulate Maintenance of Neural Progenitors","volume":"58","author":"H Shimojo","year":"2008","journal-title":"Neuron"},{"issue":"4","key":"pcbi.1009846.ref026","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1016\/j.stem.2016.03.003","article-title":"2D and 3D Stem Cell Models of Primate Cortical Development Identify Species-Specific Differences in Progenitor Behavior Contributing to Brain Size","volume":"18","author":"T Otani","year":"2016","journal-title":"Cell Stem Cell"},{"key":"pcbi.1009846.ref027","author":"C Li","year":"2016","journal-title":"Zika Virus Disrupts Neural Progenitor Development and Leads to Microcephaly in Mice"},{"issue":"6","key":"pcbi.1009846.ref028","doi-asserted-by":"crossref","first-page":"2088","DOI":"10.1523\/JNEUROSCI.17-06-02088.1997","article-title":"Synchrony of clonal cell proliferation and contiguity of clonally related cells: production of mosaicism in the ventricular zone of developing mouse neocortex","volume":"17","author":"L Cai","year":"1997","journal-title":"The Journal of neuroscience: the official journal of the Society for Neuroscience"},{"issue":"3","key":"pcbi.1009846.ref029","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1002\/cne.903600313","article-title":"Variability and partial synchrony of the cell cycle in the germinal zone of the early embryonic cerebral cortex","volume":"360","author":"K Reznikov","year":"1995","journal-title":"The Journal of comparative neurology"},{"issue":"3","key":"pcbi.1009846.ref030","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1016\/j.cell.2007.12.033","article-title":"Visualizing Spatiotemporal Dynamics of Multicellular Cell-Cycle Progression","volume":"132","author":"A Sakaue-Sawano","year":"2008","journal-title":"Cell"},{"issue":"6","key":"pcbi.1009846.ref031","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1005526","article-title":"An integrated calcium imaging processing toolbox for the analysis of neuronal population dynamics","volume":"13","author":"SA Romano","year":"2017","journal-title":"PLOS Computational Biology"},{"key":"pcbi.1009846.ref032","first-page":"8","article-title":"CaImAn an open source tool for scalable calcium imaging data analysis","author":"A Giovannucci","year":"2019","journal-title":"eLife"},{"key":"pcbi.1009846.ref033","article-title":"EZcalcium: Open Source Toolbox for Analysis of Calcium Imaging Data","author":"DA Cantu","year":"2020","journal-title":"bioRxiv"},{"issue":"3","key":"pcbi.1009846.ref034","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1006054","article-title":"An open source tool for automatic spatiotemporal assessment of calcium transients and local \u2018signal-close-to-noise\u2019 activity in calcium imaging data","volume":"14","author":"J Prada","year":"2018","journal-title":"PLOS Computational Biology"},{"key":"pcbi.1009846.ref035","doi-asserted-by":"crossref","first-page":"958","DOI":"10.3389\/fnins.2018.00958","article-title":"CAVE: An Open-Source Tool for Combined Analysis of Head-Mounted Calcium Imaging and Behavior in MATLAB","volume":"12","author":"J Tegtmeier","year":"2018","journal-title":"Frontiers in Neuroscience"},{"issue":"17","key":"pcbi.1009846.ref036","doi-asserted-by":"crossref","first-page":"3052","DOI":"10.1093\/bioinformatics\/bty281","article-title":"CaSiAn: a Calcium Signaling Analyzer tool","volume":"34","author":"M Moein","year":"2018","journal-title":"Bioinformatics"},{"key":"pcbi.1009846.ref037","first-page":"8","article-title":"SIMA: Python software for analysis of dynamic fluorescence imaging data","author":"P Kaifosh","year":"2014","journal-title":"Frontiers in Neuroinformatics"},{"key":"pcbi.1009846.ref038","first-page":"061507","article-title":"Suite2p: beyond 10,000 neurons with standard two-photon microscopy","author":"M Pachitariu","year":"2016","journal-title":"bioRxiv"},{"key":"pcbi.1009846.ref039","first-page":"7","article-title":"Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data","author":"P Zhou","year":"2018","journal-title":"eLife"},{"key":"pcbi.1009846.ref040","first-page":"190348","article-title":"ABLE: an Activity-Based Level Set Segmentation Algorithm for Two-Photon Calcium Imaging Data","author":"S Reynolds","year":"2017","journal-title":"bioRxiv"},{"issue":"4","key":"pcbi.1009846.ref041","doi-asserted-by":"crossref","first-page":"2430","DOI":"10.1214\/18-AOAS1159","article-title":"Scalpel: Extracting neurons from calcium imaging data","volume":"12","author":"A Petersen","year":"2018","journal-title":"Annals of Applied Statistics"},{"issue":"12","key":"pcbi.1009846.ref042","doi-asserted-by":"crossref","first-page":"3673","DOI":"10.1016\/j.celrep.2018.05.062","article-title":"MIN1PIPE: A Miniscope 1-Photon-Based Calcium Imaging Signal Extraction Pipeline","volume":"23","author":"J Lu","year":"2018","journal-title":"Cell Reports"},{"key":"pcbi.1009846.ref043","first-page":"11","article-title":"SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales","author":"M Rueckl","year":"2017","journal-title":"Frontiers in Neuroinformatics"},{"issue":"February","key":"pcbi.1009846.ref044","first-page":"110","volume":"2","author":"V Colizza","year":"2006","journal-title":"Detecting rich-club ordering in complex networks"},{"issue":"20","key":"pcbi.1009846.ref045","doi-asserted-by":"crossref","first-page":"208701","DOI":"10.1103\/PhysRevLett.89.208701","article-title":"Assortative Mixing in Networks","volume":"89","author":"M. Newman","year":"2002","journal-title":"Physical Review Letters"},{"issue":"35","key":"pcbi.1009846.ref046","doi-asserted-by":"crossref","first-page":"6829","DOI":"10.1523\/JNEUROSCI.2663-18.2019","article-title":"Differences between Dorsal Root and Trigeminal Ganglion Nociceptors in Mice Revealed by Translational Profiling","volume":"39","author":"S Megat","year":"2019","journal-title":"J Neurosci"},{"issue":"5","key":"pcbi.1009846.ref047","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1016\/j.neuron.2016.07.044","article-title":"Coupled Activation of Primary Sensory Neurons Contributes to Chronic Pain","volume":"91","author":"YS Kim","year":"2016","journal-title":"Neuron"},{"issue":"4","key":"pcbi.1009846.ref048","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1016\/j.neuron.2013.12.011","article-title":"Central terminal sensitization of TRPV1 by descending serotonergic facilitation modulates chronic pain","volume":"81","author":"YS Kim","year":"2014","journal-title":"Neuron"},{"issue":"2","key":"pcbi.1009846.ref049","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1016\/j.jstrokecerebrovasdis.2016.10.004","article-title":"Reported Prestroke Physical Activity Is Associated with Vascular Endothelial Growth Factor Expression and Good Outcomes after Stroke","volume":"26","author":"E L\u00f3pez-Cancio","year":"2017","journal-title":"Journal of Stroke and Cerebrovascular Diseases"},{"key":"pcbi.1009846.ref050","article-title":"Neuroprotective and regenerative roles of intranasal Wnt-3a Administration after focal ischemic stroke in mice","author":"ZZ Wei","year":"2017","journal-title":"Journal of Cerebral Blood Flow & Metabolism"},{"issue":"2","key":"pcbi.1009846.ref051","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.mvr.2007.05.006","article-title":"In vitro assays of angiogenesis for assessment of angiogenic and anti-angiogenic agents","volume":"74","author":"AM Goodwin","year":"2007","journal-title":"Microvascular Research"},{"issue":"12","key":"pcbi.1009846.ref052","doi-asserted-by":"crossref","first-page":"1292","DOI":"10.1038\/ncb3443","article-title":"Asymmetric division coordinates collective cell migration in angiogenesis","volume":"18","author":"G Costa","year":"2016","journal-title":"Nature Cell Biology"},{"issue":"6","key":"pcbi.1009846.ref053","doi-asserted-by":"crossref","first-page":"6128","DOI":"10.1021\/acsnano.5b01366","article-title":"Recapitulation and Modulation of the Cellular Architecture of a User-Chosen Cell of Interest Using Cell-Derived, Biomimetic Patterning","volume":"9","author":"JH Slater","year":"2015","journal-title":"ACS Nano"},{"issue":"10","key":"pcbi.1009846.ref054","doi-asserted-by":"crossref","first-page":"951","DOI":"10.1038\/nmeth.3545","article-title":"Trajectories of cell-cycle progression from fixed cell populations","volume":"12","author":"G Gut","year":"2015","journal-title":"Nature methods"},{"issue":"10","key":"pcbi.1009846.ref055","doi-asserted-by":"crossref","first-page":"e109854","DOI":"10.1371\/journal.pone.0109854","article-title":"Laminin alpha4 deficient mice exhibit decreased capacity for adipose tissue expansion and weight gain","volume":"9","author":"MK Vaicik","year":"2014","journal-title":"PLoS One"},{"issue":"1","key":"pcbi.1009846.ref056","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1210\/en.2017-00186","article-title":"The Absence of Laminin \u03b14 in Male Mice Results in Enhanced Energy Expenditure and Increased Beige Subcutaneous Adipose Tissue","volume":"159","author":"MK Vaicik","year":"2018","journal-title":"Endocrinology"},{"issue":"40","key":"pcbi.1009846.ref057","doi-asserted-by":"crossref","first-page":"7903","DOI":"10.1039\/C5TB00952A","article-title":"Hydrogel-Based Engineering of Beige Adipose Tissue","volume":"3","author":"MK Vaicik","year":"2015","journal-title":"J Mater Chem B"},{"issue":"3","key":"pcbi.1009846.ref058","article-title":"Optimization of Co-Culture Conditions for a Human Vascularized Adipose Tissue Model","volume":"7","author":"F Yang","year":"2020","journal-title":"Bioengineering (Basel)"},{"key":"pcbi.1009846.ref059","article-title":"Integrins and extracellular matrix proteins module adipocyte thermogenic capacity","author":"M Gonzalez-Porras","year":"2021","journal-title":"Scientific Reports"},{"issue":"12","key":"pcbi.1009846.ref060","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1038\/s41592-019-0582-9","article-title":"ilastik: interactive machine learning for (bio)image analysis","volume":"16","author":"S Berg","year":"2019","journal-title":"Nature Methods"},{"issue":"5","key":"pcbi.1009846.ref061","doi-asserted-by":"crossref","DOI":"10.1016\/j.cels.2020.04.003","article-title":"nucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer","volume":"10","author":"R Hollandi","year":"2020","journal-title":"Cell Systems"},{"key":"pcbi.1009846.ref062","first-page":"803205","article-title":"Accurate cell tracking and lineage construction in live-cell imaging experiments with deep learning","author":"E Moen","year":"2019","journal-title":"bioRxiv"},{"issue":"10","key":"pcbi.1009846.ref063","doi-asserted-by":"crossref","DOI":"10.1186\/gb-2006-7-10-r100","article-title":"CellProfiler: image analysis software for identifying and quantifying cell phenotypes","volume":"7","author":"AE Carpenter","year":"2006","journal-title":"Genome Biology"},{"key":"pcbi.1009846.ref064","doi-asserted-by":"crossref","first-page":"111","DOI":"10.3389\/fncir.2014.00111","article-title":"Network analysis of time-lapse microscopy recordings","volume":"8","author":"E Smedler","year":"2014","journal-title":"Front Neural Circuits"},{"key":"pcbi.1009846.ref065","first-page":"85","article-title":"Overview of metrics and their correlation patterns for multiple-metric topology analysis on heterogeneous graph ensembles","author":"G Bounova","year":"2012","journal-title":"Physical Review E\u2014Statistical, Nonlinear, and Soft Matter Physics"},{"issue":"3","key":"pcbi.1009846.ref066","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.stem.2009.07.011","article-title":"An Efficient and Reversible Transposable System for Gene Delivery and Lineage-Specific Differentiation in Human Embryonic Stem Cells","volume":"5","author":"A Lacoste","year":"2009","journal-title":"Cell Stem Cell"},{"key":"pcbi.1009846.ref067","author":"DT Ryan","year":"2013","journal-title":"Predicting endothelial cell phenotypes in angiogenesis"},{"issue":"1","key":"pcbi.1009846.ref068","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1186\/s12859-018-2022-8","article-title":"Shrinkage Clustering: a fast and size-constrained clustering algorithm for biomedical applications","volume":"19","author":"CW Hu","year":"2018","journal-title":"BMC Bioinformatics"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1013176","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2025,6,10]],"date-time":"2025-06-10T00:00:00Z","timestamp":1749513600000}},{"DOI":"10.1371\/journal.pcbi.1010644","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2022,11,8]],"date-time":"2022-11-08T00:00:00Z","timestamp":1667865600000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1009846","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,13]],"date-time":"2022-06-13T13:48:55Z","timestamp":1655128135000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1009846"}},"subtitle":[],"editor":[{"given":"Melissa L.","family":"Kemp","sequence":"first","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2022,6,13]]},"references-count":68,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2022,6,13]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1009846","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/180273","asserted-by":"object"}]},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,13]]}}}