MEGA6: Molecular Evolutionary Genetics Analysis version 6.0.

@article{Tamura2013MEGA6ME,
  title={MEGA6: Molecular Evolutionary Genetics Analysis version 6.0.},
  author={Koichiro Tamura and Glen Stecher and Daniel Peterson and Alan J. Filipski and Sudhir Kumar},
  journal={Molecular biology and evolution},
  year={2013},
  volume={30 12},
  pages={
          2725-9
        }
}
We announce the release of an advanced version of the Molecular Evolutionary Genetics Analysis (MEGA) software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis. [...] Key Method This version also contains enhanced algorithms to search for the optimal trees under evolutionary criteria and implements a more advanced memory management that can double the size of sequence data sets to which MEGA can be applied…Expand
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References

SHOWING 1-10 OF 11 REFERENCES
MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis
TLDR
MEGA-CC provides users with access to all the computational analyses available through MEGA's graphical user interface version, including methods for multiple sequence alignment, substitution model selection, evolutionary distance estimation, phylogeny inference, substitution rate and pattern estimation, tests of natural selection and ancestral sequence inference.
MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers
TLDR
In this program, various methods for estimating evolutionary distances from nucleotide and amino acid sequence data, three different methods of phylogenetic inference (UPGMA, neighbor-joining and maximum parsimony) and two statistical tests of topological differences are included.
MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods.
TLDR
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.
The optimization principle in phylogenetic analysis tends to give incorrect topologies when the number of nucleotides or amino acids used is small.
  • M. Nei, S. Kumar, K. Takahashi
  • Mathematics, Medicine
    Proceedings of the National Academy of Sciences of the United States of America
  • 1998
TLDR
This finding indicates that the optimization principle tends to give incorrect topologies when n is small, and it is suggested that more attention should be given to testing the statistical reliability of an estimated tree rather than to finding the optimal tree with excessive efforts.
Molecular Evolution and Phylogenetics
TLDR
This chapter discusses the molecular basis of evolution, the evolution of organisms based on the fossil record, and the implications of these events for phylogenetic inference.
Estimating divergence times in large molecular phylogenies
TLDR
RelTime is presented, a method that estimates relative times of divergences for all branching points (nodes) in very large phylogenetic trees without assuming a specific model for lineage rate variation or specifying any clock calibrations.
TimeTree2: species divergence times on the iPhone
TLDR
TimeTree2 is a public knowledgebase that enables data-driven access to the collection of peer-reviewed publications in molecular evolution and phylogenetics that have reported estimates of time of divergence between species.
Estimating the Rate of Intersubtype Recombination in Early HIV-1 Group M Strains
TLDR
The results imply that intersubtype recombination may have occurred in approximately 20% of lineages evolving over a period of 30 years and confirm intersub type recombination as a substantial force in generating HIV-1 group M diversity.
MEGA 5 : molecular evolutionary genetics analysis using maximum likelihood , evolutionary distance , and maximum parsimony meth
  • Mol Biol Evol .
  • 2011
PAUP* [Phylogenetic Analysis Using Parsimony (and Other Methods)]
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