CellSeT: Novel Software to Extract and Analyze Structured Networks of Plant Cells from Confocal Images
CellSeT: Novel Software to Extract and Analyze Structured Networks of Plant Cells from Confocal Images
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DOI：
10.1105/tpc.112.096289
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发表时间：
2012-04-01
期刊：
影响因子：
11.6
通讯作者：
Pridmore, Tony P.
中科院分区：
文献类型：
--
作者：
Pound, Michael P.;French, Andrew P.;Pridmore, Tony P.
在生命科学中，许多细胞尺度和组织尺度的测量都是通过共聚焦显微镜图像来量化的，这一点越来越重要。然而，大规模共聚焦图像数据集的提取和分析是研究人员面临的主要瓶颈。为了帮助这一过程，CellSeT软件已经开发出来，它利用组织尺度结构来帮助分割单个细胞。我们提供了CellSeT软件如何用于量化激素响应核报告的荧光，确定膜蛋白极性，提取细胞和组织几何形状以用于后期建模的例子，并使用可扩展的插件工具集采取许多额外的生物学相关措施。CellSeT的应用有望消除结果数据集的主观性，促进植物细胞研究的高通量、定量方法。
It is increasingly important in life sciences that many cell-scale and tissue-scale measurements are quantified from confocal microscope images. However, extracting and analyzing large-scale confocal image data sets represents a major bottleneck for researchers. To aid this process, CellSeT software has been developed, which utilizes tissue-scale structure to help segment individual cells. We provide examples of how the CellSeT software can be used to quantify fluorescence of hormone-responsive nuclear reporters, determine membrane protein polarity, extract cell and tissue geometry for use in later modeling, and take many additional biologically relevant measures using an extensible plug-in toolset. Application of CellSeT promises to remove subjectivity from the resulting data sets and facilitate higher-throughput, quantitative approaches to plant cell research.