This article is part of the supplement: Selected articles from The 8th Annual Biotechnology and Bioinformatics Symposium (BIOT-2011)
Research
Phylogenetic search through partial tree mixing
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
Citation and License
BMC Bioinformatics 2012, 13(Suppl 13):S8 doi:10.1186/1471-2105-13-S13-S8
Published: 24 August 2012Abstract
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.
