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Beyond the more conventional single-cell segmentation and tracking, single-cell cycle dynamics is gaining a growing interest in the field of cell biology. Thanks to sophisticated systems, such as the fluorescent ubiquitination-based cell cycle indicator (FUCCI), it is now possible to study cell proliferation, migration, changes in nuclear morphology and single cell cycle dynamics, quantitatively and in real time. In this work, we introduce FUCCItrack, an all-in-one, semi-automated software to segment, track and visualize FUCCI modified cell lines. A user-friendly complete graphical user interface is presented to record and quantitatively analyze both collective cell proliferation as well as single cell information, including migration and changes in nuclear or cell morphology as a function of cell cycle. To enable full control over the analysis, FUCCItrack also contains features for identification of errors and manual corrections.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9258891 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0268297 | PLOS |
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New York University Grossman School of Medicine, Microbiology Department, New York, NY, USA.
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Institute for Regenerative Medicine, Medical Innovation Center and State Key Laboratory of Cardiovascular Diseases, Shanghai East Hospital, National Stem Cell Translational Resource Center & Ministry of Education Stem Cell Resource Center, Frontier Science Center for Stem Cell Research, School of Li
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Institute for Stem Cell Science and Regenerative Medicine (inStem), GKVK post, Bellary Road, Bangalore, Karnataka, 560065, India.
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Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
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Department of Endocrinology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510080, China.
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