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This article is part of the supplement: Selected articles from The 8th Annual Biotechnology and Bioinformatics Symposium (BIOT-2011)

Open Access Research

Phylogenetic search through partial tree mixing

Kenneth Sundberg1, Mark Clement2*, Quinn Snell2, Dan Ventura2, Michael Whiting2 and Keith Crandall3

Author Affiliations

1 Department of Computer Science, Utah State University, Logan UT 84322, USA

2 Department of Computer Science, Brigham Young University, Provo, UT 84602, USA

3 Department of Biology, Brigham Young University, Provo, UT 84602, USA

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BMC Bioinformatics 2012, 13(Suppl 13):S8  doi:10.1186/1471-2105-13-S13-S8

Published: 24 August 2012

Abstract

Background

Recent advances in sequencing technology have created large data sets upon which phylogenetic inference can be performed. Current research is limited by the prohibitive time necessary to perform tree search on a reasonable number of individuals. This research develops new phylogenetic algorithms that can operate on tens of thousands of species in a reasonable amount of time through several innovative search techniques.

Results

When compared to popular phylogenetic search algorithms, better trees are found much more quickly for large data sets. These algorithms are incorporated in the PSODA application available at http://dna.cs.byu.edu/psoda webcite

Conclusions

The use of Partial Tree Mixing in a partition based tree space allows the algorithm to quickly converge on near optimal tree regions. These regions can then be searched in a methodical way to determine the overall optimal phylogenetic solution.