Zhang Hongmei, Zhong Yang, Hao Bailin, Gu Xun
Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC 29208, USA.
Gene. 2009 Jul 15;441(1-2):163-8. doi: 10.1016/j.gene.2008.07.008. Epub 2008 Jul 17.
Many studies have been contributed to the inferences of phylogenies. Some studies are based on a single-gene (family), and some are based on entire genome data. In this paper, we propose a total loss genome distance approach based on gene content information to inferring phylogenies. Through various simulations, we demonstrate and evaluate the proposed approach. We compare it with some other approaches built upon gene content or extended gene content. Overall, the proposed approach performs equally well as the other methods do and is more efficient than some of the methods. We apply our approach to 34 microbial complete genomes from COG. The reconstructed tree agrees with the results from other approaches and the tree supports the concept of universal trees.
许多研究都致力于系统发育的推断。一些研究基于单基因（家族），而一些则基于全基因组数据。在本文中，我们提出了一种基于基因含量信息的全基因组距离方法来推断系统发育。通过各种模拟，我们对所提出的方法进行了演示和评估。我们将其与其他基于基因含量或扩展基因含量构建的方法进行了比较。总体而言，所提出的方法与其他方法表现相当，并且比其中一些方法更有效。我们将我们的方法应用于来自COG的34个微生物完整基因组。重建的树与其他方法的结果一致，并且该树支持通用树的概念。
