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Computational Methods for Estimation of Cell Cycle Phase Distributions of Yeast Cells

机译:估算酵母细胞周期周期分布的计算方法

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摘要

Two computational methods for estimating the cell cycle phase distribution of a budding yeast (Saccharomyces cerevisiae) cell population are presented. The first one is a nonparametric method that is based on the analysis of DNA content in the individual cells of the population. The DNA content is measured with a fluorescence-activated cell sorter (FACS). The second method is based on budding index analysis. An automated image analysis method is presented for the task of detecting the cells and buds. The proposed methods can be used to obtain quantitative information on the cell cycle phase distribution of a budding yeast S. cerevisiae population. They therefore provide a solid basis for obtaining the complementary information needed in deconvolution of gene expression data. As a case study, both methods are tested with data that were obtained in a time series experiment with S. cerevisiae. The details of the time series experiment as well as the image and FACS data obtained in the experiment can be found in the online additional material at .
机译:提出了两种计算方法来估算出芽酵母(酿酒酵母)细胞群体的细胞周期阶段分布。第一种是非参数方法,该方法基于对种群单个细胞中DNA含量的分析。用荧光激活细胞分选仪(FACS)测量DNA含量。第二种方法基于萌芽指数分析。提出了一种自动图像分析方法,用于检测细胞和芽。所提出的方法可用于获得关于芽生啤酒酵母种群的细胞周期阶段分布的定量信息。因此,它们为获得基因表达数据反卷积所需的补充信息提供了坚实的基础。作为案例研究,将两种方法都用在酿酒酵母的时序实验中获得的数据进行测试。时间序列实验的详细信息以及实验中获得的图像和FACS数据可在上的在线其他资料中找到。

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