PRec-I-DCM3: a parallel framework for fast and accurate large-scale phylogeny reconstruction.
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.
Department of Computer Science, Rice University, 6100 Main Street, Houston, TX 77005, USA.
Yuri
Y
Dotsenko
Cristian
C
Coarfa
Luay
L
Nakhleh
John
J
Mellor-Crummey
Usman
U
Roshan
D000465:Algorithms; D001499:Bayes Theorem; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003201:Computers; D030541:Databases, Genetic; D007091:Image Processing, Computer-Assisted; D016013:Likelihood Functions; D008957:Models, Genetic; D015233:Models, Statistical; D010802:Phylogeny; D012313:RNA / Q000737:chemistry; D015203:Reproducibility of Results; D017422:Sequence Analysis, DNA; D017423:Sequence Analysis, RNA; D013997:Time Factors
D012313:RNA