Skip Navigation


Bioinformatics Advance Access originally published online on December 16, 2007
Bioinformatics 2008 24(3):383-388; doi:10.1093/bioinformatics/btm621
This Article
Right arrow Full Text
Right arrow Full Text (Print PDF)
Right arrow Supplementary Data
Right arrow All Versions of this Article:
24/3/383    most recent
btm621v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Vale, F.F.
Right arrow Articles by Vítor, J. M. B.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Vale, F.F.
Right arrow Articles by Vítor, J. M. B.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A new algorithm for cluster analysis of genomic methylation: the Helicobacter pylori case

F.F. Vale 1,*, P. Encarnação 1 and J. M. B. Vítor 2

1Engineering Faculty, Portuguese Catholic University, Estrada Octávio Pato, 2635-631 Rio de Mouro, Portugal and 2CECF (iMed.UL), Faculty of Pharmacy, University of Lisbon, Av. Forças Armadas, 1649-003 Lisboa, Portugal

*To whom correspondence should be addressed.


  Abstract

Motivation: The genomic methylation analysis is useful to type bacteria that have a high number of expressed type II methyltransferases. Methyltransferases are usually committed to Restriction and Modification (R-M) systems, in which the restriction endonuclease imposes high pressure on the expression of the cognate methyltransferase that hinder R-M system loss. Conventional cluster methods do not reflect this tendency. An algorithm was developed for dendrogram construction reflecting the propensity for conservation of R-M Type II systems.

Results: The new algorithm was applied to 52 Helicobacter pylori strains from different geographical regions and compared with conventional clustering methods. The algorithm works by first grouping strains that share a common minimum set of R-M systems and gradually adds strains according to the number of the R-M systems acquired. Dendrograms revealed a cluster of African strains, which suggest that R-M systems are present in H.pylori genome since its human host migrates from Africa.

Availability: The software files are available at http://www.ff.ul.pt/paginas/jvitor/Bioinformatics/MCRM_algorithm.zip

Contact: filipavale{at}fe.ucp.pt

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Martin Bishop

Received on October 19, 2007; revised on December 13, 2007; accepted on December 13, 2007

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.