Skip Navigation



Bioinformatics Advance Access published online on August 23, 2007

Bioinformatics, doi:10.1093/bioinformatics/btm413
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
23/22/2993    most recent
btm413v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
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 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 Buendia, P.
Right arrow Articles by Narasimhan, G.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Buendia, P.
Right arrow Articles by Narasimhan, G.
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

Sliding MinPD: Building evolutionary networks of serial samples via an automated recombination detection approach

Patricia Buendia 1 and Giri Narasimhan 1,*

1Bioinformatics Research Group (BioRG), School of Computing and Information Science, Florida International University, Miami, FL 33199, USA.

*To whom correspondence should be addressed. Giri Narasimhan, E-mail: giri{at}cis.fiu.edu


   Abstract

Motivation: Traditional phylogenetic methods assume tree-like evolutionary models and are likely to perform poorly when provided with sequence data from fast-evolving, recombining viruses. Furthermore, these methods assume that all the sequence data are from contemporaneous taxa, which is not valid for serially-sampled data. A more general approach is proposed here, referred to as the Sliding MinPD method, that reconstructs evolutionary networks for serially-sampled sequences in the presence of recombination.

Results: Sliding MinPD combines distance-based phylogenetic methods with automated recombination detection based on the best-known sliding window approaches to reconstruct serial evolutionary networks. Its performance was evaluated through comprehensive simulation studies and was also applied to a set of serially-sampled HIV sequences from a single patient. The resulting network organizations reveal unique patterns of viral evolution and may help explain the emergence of disease-associated mutants and drug-resistant strains, with implications for patient prognosis and treatment strategies.

Availability: From website http://biorg.cis.fiu.edu/SlidingMinPD

Contact: giri{at}cis.fiu.edu

Supplementary information: http://biorg.cis.fiu.edu/SlidingMinPD

Associate Editor: Prof. Martin Bishop


Received on May 16, 2007; revised on August 9, 2007; accepted on August 9, 2007

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


This article has been cited by other articles:


Home page
BioinformaticsHome page
P. Buendia, B. Cadwallader, and V. DeGruttola
A phylogenetic and Markov model approach for the reconstruction of mutational pathways of drug resistance
Bioinformatics, October 1, 2009; 25(19): 2522 - 2529.
[Abstract] [Full Text] [PDF]



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.