QUT ePrints

Whole-proteome phylogeny of large dsDNA viruses and parvoviruses through a composition vector method related to dynamical language model

Yu, Zuguo, Chu, Ka-Hou, Li, Chi Pang, Anh, Vo, Zhou, Li-Qian, & Wang, Roger (2010) Whole-proteome phylogeny of large dsDNA viruses and parvoviruses through a composition vector method related to dynamical language model. BMC Evolutionary Biology, 10(192), pp. 1-11.

View at publisher (open access)

Abstract

Background

The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes. Results

In this paper, the DL method is used to analyze the whole-proteome phylogeny of 124 large dsDNA viruses and 30 parvoviruses, two data sets with large difference in genome size. The trees from our analyses are in good agreement to the latest classification of large dsDNA viruses and parvoviruses by the International Committee on Taxonomy of Viruses (ICTV). Conclusions

The present method provides a new way for recovering the phylogeny of large dsDNA viruses and parvoviruses, and also some insights on the affiliation of a number of unclassified viruses. In comparison, some alignment-free methods such as the CV Tree method can be used for recovering the phylogeny of large dsDNA viruses, but they are not suitable for resolving the phylogeny of parvoviruses with a much smaller genome size.

Impact and interest:

13 citations in Scopus
Search Google Scholar™
10 citations in Web of Science®

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 42959
Item Type: Journal Article
DOI: 10.1186/1471-2148-10-192
ISSN: 1471-2148
Subjects: Australian and New Zealand Standard Research Classification > BIOLOGICAL SCIENCES (060000) > BIOCHEMISTRY AND CELL BIOLOGY (060100) > Bioinformatics (060102)
Australian and New Zealand Standard Research Classification > BIOLOGICAL SCIENCES (060000) > EVOLUTIONARY BIOLOGY (060300)
Australian and New Zealand Standard Research Classification > BIOLOGICAL SCIENCES (060000) > GENETICS (060400)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > Mathematical Sciences
Deposited On: 13 Jul 2011 23:08
Last Modified: 03 Dec 2012 12:07

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page