Literature DB >> 18675889

A simple method for phylogenomic inference using the information of gene content of genomes.

Hongmei Zhang1, Yang Zhong, Bailin Hao, Xun Gu.   

Abstract

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.

Mesh:

Year:  2008        PMID: 18675889     DOI: 10.1016/j.gene.2008.07.008

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  5 in total

Review 1.  Insect phylogenomics.

Authors:  S K Behura
Journal:  Insect Mol Biol       Date:  2015-05-12       Impact factor: 3.585

2.  Phylogenetic analysis of protein sequences based on distribution of length about common sub-string.

Authors:  Guisong Chang; Tianming Wang
Journal:  Protein J       Date:  2011-03       Impact factor: 2.371

3.  Maximum likelihood phylogenetic reconstruction from high-resolution whole-genome data and a tree of 68 eukaryotes.

Authors:  Yu Lin; Fei Hu; Jijun Tang; Bernard M E Moret
Journal:  Pac Symp Biocomput       Date:  2013

4.  Tracing lifestyle adaptation in prokaryotic genomes.

Authors:  Eric Altermann
Journal:  Front Microbiol       Date:  2012-02-21       Impact factor: 5.640

5.  Using the taxon-specific genes for the taxonomic classification of bacterial genomes.

Authors:  Ankit Gupta; Vineet K Sharma
Journal:  BMC Genomics       Date:  2015-05-20       Impact factor: 3.969

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.