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PAUP^* : Phylogenetic Analysis Using Parsimony (and other methods) 4.0b8
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The article was published on 2001-01-01 and is currently open access. It has received 13011 citations till now. The article focuses on the topics: Phylogenetic tree.read more
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MEGA5: Molecular Evolutionary Genetics Analysis using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods
Koichiro Tamura,Daniel S. Peterson,Nicholas Peterson,Glen Stecher,Masatoshi Nei,Sudhir Kumar +5 more
TL;DR: The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models, inferring ancestral states and sequences, and estimating evolutionary rates site-by-site.
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MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0
TL;DR: An advanced version of the Molecular Evolutionary Genetics Analysis software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis, is released, which enables the inference of timetrees, as it implements the RelTime method for estimating divergence times for all branching points in a phylogeny.
Brief Communication MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0
TL;DR: The Molecular Evolutionary Genetics Analysis (MEGA) software as discussed by the authors provides facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis, including the inference of timetrees.
Journal ArticleDOI
A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood.
Stéphane Guindon,Olivier Gascuel +1 more
TL;DR: This work has used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance of distance-based and parsimony approaches.
Journal ArticleDOI
IQ-TREE: A fast and effective stochastic algorithm for estimating maximum likelihood phylogenies
TL;DR: It is shown that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented and found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space.