Title: PRec-I-DCM3: a parallel framework for fast and accurate large-scale phylogeny reconstruction

Authors: Yuri Dotsenko, Cristian Coarfa, Luay Nakhleh, John Mellor-Crummey, Usman Roshan

Addresses: Department of Computer Science, Rice University, 6100 Main Street, Houston TX 77005, USA. ' Department of Computer Science, Rice University, 6100 Main Street, Houston TX 77005, USA. ' Department of Computer Science, Rice University, 6100 Main Street, Houston TX 77005, USA. ' Department of Computer Science, Rice University, 6100 Main Street, Houston TX 77005, USA. ' Department of Computer Science, New Jersey Institute of Technology, GITC 4400, University Heights, Newark NJ 07102, USA

Abstract: Accurate reconstruction of phylogenetic trees often involves solving hard optimisation problems, particularly the Maximum Parsimony (MP) and Maximum Likelihood (ML) problems. Various heuristics yield good results for these problems within reasonable time only on small datasets. This is a major impediment for large-scale phylogeny reconstruction. Roshan et al. introduced Rec-I-DCM3, an efficient and accurate meta-method for solving the MP problem on large datasets of up to 14,000 taxa. We improve the performance of Rec-I-DCM3 via parallelisation. The experiments demonstrate that our parallel method, PRec-I-DCM3, achieves significant improvements, both in speed and accuracy, over its sequential counterpart.

Keywords: phylogeny reconstruction; phylogenetic trees; maximum parsimony; disk-covering method; DCM; DCM3; Rec-I-DCM3; PRec-I-DCM3; parallel computing; scalability; bioinformatics research; bioinformatics applications; high performance computing.

DOI: 10.1504/IJBRA.2006.011039

International Journal of Bioinformatics Research and Applications, 2006 Vol.2 No.4, pp.407 - 419

Published online: 05 Oct 2006 *

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