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ACM/IEEE SC 2006 Conference (SC'06)
This paper describes the implementation and performance of PBPI, a parallel implementation of Bayesian phylogenetic inference method for DNA sequence data. By combining the Markov Chain Monte Carlo (MCMC) method with likelihood-based assessment of phylogenies, Bayesian phylogenetic inferences can incorporate complex statistic models into the process of phylogenetic tree estimation. However, Bayesian analyses are extremely computationally expensive. PBPI uses algorithmic improvements anddoi:10.1109/sc.2006.47 fatcat:4hihqgsl3rdaddl676syatmfbu