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{"title":"Automated Tracking of Cell Migration with Rapid Data Analysis.","authors":"Brian J DuChez","doi":"10.1002/cpcb.28","DOIUrl":null,"url":null,"abstract":"<p><p>Cell migration is essential for many biological processes including development, wound healing, and metastasis. However, studying cell migration often requires the time-consuming and labor-intensive task of manually tracking cells. To accelerate the task of obtaining coordinate positions of migrating cells, we have developed a graphical user interface (GUI) capable of automating the tracking of fluorescently labeled nuclei. This GUI provides an intuitive user interface that makes automated tracking accessible to researchers with no image-processing experience or familiarity with particle-tracking approaches. Using this GUI, users can interactively determine a minimum of four parameters to identify fluorescently labeled cells and automate acquisition of cell trajectories. Additional features allow for batch processing of numerous time-lapse images, curation of unwanted tracks, and subsequent statistical analysis of tracked cells. Statistical outputs allow users to evaluate migratory phenotypes, including cell speed, distance, displacement, and persistence, as well as measures of directional movement, such as forward migration index (FMI) and angular displacement. © 2017 by John Wiley & Sons, Inc.</p>","PeriodicalId":40051,"journal":{"name":"Current Protocols in Cell Biology","volume":"76 ","pages":"12.12.1-12.12.16"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cpcb.28","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Protocols in Cell Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/cpcb.28","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 14
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Abstract
Cell migration is essential for many biological processes including development, wound healing, and metastasis. However, studying cell migration often requires the time-consuming and labor-intensive task of manually tracking cells. To accelerate the task of obtaining coordinate positions of migrating cells, we have developed a graphical user interface (GUI) capable of automating the tracking of fluorescently labeled nuclei. This GUI provides an intuitive user interface that makes automated tracking accessible to researchers with no image-processing experience or familiarity with particle-tracking approaches. Using this GUI, users can interactively determine a minimum of four parameters to identify fluorescently labeled cells and automate acquisition of cell trajectories. Additional features allow for batch processing of numerous time-lapse images, curation of unwanted tracks, and subsequent statistical analysis of tracked cells. Statistical outputs allow users to evaluate migratory phenotypes, including cell speed, distance, displacement, and persistence, as well as measures of directional movement, such as forward migration index (FMI) and angular displacement. © 2017 by John Wiley & Sons, Inc.
快速数据分析的细胞迁移自动跟踪。
细胞迁移对许多生物过程至关重要,包括发育、伤口愈合和转移。然而,研究细胞迁移通常需要人工跟踪细胞的耗时和劳动密集型任务。为了加快获得迁移细胞坐标位置的任务,我们开发了一个图形用户界面(GUI),能够自动跟踪荧光标记的细胞核。这个GUI提供了一个直观的用户界面,使自动跟踪访问没有图像处理经验或熟悉粒子跟踪方法的研究人员。使用此GUI,用户可以交互式地确定至少四个参数,以识别荧光标记的细胞和自动获取细胞轨迹。其他功能允许批量处理大量延时图像,管理不需要的轨道,以及跟踪细胞的后续统计分析。统计输出允许用户评估迁移表型,包括细胞速度,距离,位移和持久性,以及定向运动的措施,如前向迁移指数(FMI)和角位移。©2017 by John Wiley & Sons, Inc。
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