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Some comparison on whole-proteome phylogeny of large dsDNA viruses based on dynamical language approach and feature frequency profiles method

机译:基于动力学语言方法的大型DSDNA病毒全蛋白质组文源的一些比较和特征频率分布方法

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There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among them, CVTree method, feature frequency profiles method and dynamical language approach were used to investigate the whole-proteome phylogeny of large dsDNA viruses. Using the data set of large dsDNA viruses from Gao and Qi (BMC Evol. Biol. 2007), the phylogenetic results based on the CVTree method and the dynamical language approach were compared in Yu et al. (BMC Evol. Biol. 2010). In this paper, we first apply dynamical language approach to the data set of large dsDNA viruses from Wu et al. (Proc. Natl. Acad. Sci. USA 2009) and compare our phylogenetic results with those based on the feature frequency profiles method. Then we construct the whole-proteome phylogeny of the larger dataset combining the above two data sets. According to the report of The International Committee on the Taxonomy of Viruses (ICTV), the trees from our analyses are in good agreement to the latest classification of large dsDNA viruses.
机译:使用完整的基因组数据,对系统发育分析的对齐方法产生了越来越令人兴趣。其中,使用特征频率分布方法和动态语言方法来研究大型DSDNA病毒的全蛋白质组系统。使用来自GAO和QI(BMC EVOL的大DSDNA病毒数据集。在Yu等人的情况下,比较了基于CVTree方法的系统发育结果和动力学语言方法。 (BMC EVOL。BIOL。2010)。在本文中,我们首先将动态语言方法应用于Wu等人的大DSDNA病毒数据集。 (Proc。Natl。Acad。SCI。美国2009)并将这些系统发育结果与基于特征频率分布方法的系统进行比较。然后我们构建组合上述两个数据集的较大数据集的全蛋白质组文发。据“病毒分类委员会(ICTV)的报告称,我们分析中的树木与大型DSDNA病毒的最新分类有关。

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