2009
DOI: 10.1093/bioinformatics/btp244
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Many-core algorithms for statistical phylogenetics

Abstract: Source code provided in BEAGLE: Broad-platform Evolutionary Analysis General Likelihood Evaluator, a cross-platform/processor library for phylogenetic likelihood computation (http://beagle-lib.googlecode.com/). We employ a BEAGLE-implementation using the Bayesian phylogenetics framework BEAST (http://beast.bio.ed.ac.uk/).

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Cited by 390 publications
(304 citation statements)
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“…This is especially true for more-variable genes, like the glycoprotein gene, that undergo strong purifying selection (26,51).…”
Section: Resultsmentioning
confidence: 99%
“…This is especially true for more-variable genes, like the glycoprotein gene, that undergo strong purifying selection (26,51).…”
Section: Resultsmentioning
confidence: 99%
“…We used relaxed molecular clock and fossil calibrations to obtain time-calibrated phylogenies by: (i) running 50 independent RAXML searches with the best partition scheme to obtain a ML estimate of phylogeny; (ii) selecting the best tree model in many-core parallel BEAST v. 1.6.1 [39,40] with the ML phylogeny as the starting tree; and (iii) applying the best tree model in parameter and tree searches in BEAST. The best fit between the pure-speciation (Yule) and birth-death (speciationextinction) model was evaluated in BEAST by running 20 million generations in MCMCMC searches.…”
Section: Methodsmentioning
confidence: 99%
“…Bayesian phylogenetic analyses were performed in BEAST v. 1.7.1 [6] using BEAGLE [13]. We used the HKY85 þ G substitution model, and the uncorrelated lognormal model of changes in substitution rate [6], and partitioned our alignment by codon position [14].…”
Section: Methodsmentioning
confidence: 99%