Li-qian Zhou, Zuguo Yu, Guo-Sheng Han, Guang-ming Zhou, De-Sheng Wang
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引用次数: 2
Abstract
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.
人们对使用全基因组数据进行系统发育分析的无比对方法越来越感兴趣。其中,利用CVTree方法、特征频率谱方法和动态语言方法对大型dsDNA病毒的全蛋白质组系统发育进行了研究。利用高和齐(BMC Evol.)的大型dsDNA病毒数据集。Yu et al. (BMC evolution . 2007)对基于CVTree方法和动态语言方法的系统发育结果进行了比较。医学杂志。2010)。在本文中,我们首先将动态语言方法应用于Wu等人(Proc. Natl)的大型dsDNA病毒数据集。学会科学。(美国,2009),并将我们的系统发育结果与基于特征频率谱方法的结果进行比较。然后结合以上两个数据集构建更大数据集的全蛋白质组系统发育。根据国际病毒分类委员会(International Committee on the Taxonomy of Viruses, ICTV)的报告,我们的分析树与大型dsDNA病毒的最新分类非常一致。