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Cited by 39,969

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MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods

Open access
Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., Kumar, S.·2011·Molecular Biology and Evolution

Abstract

Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.

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Cited by

Items 101–163 of 163

Metadata

Authors
Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., & Kumar, S.
Venue
Molecular Biology and Evolution
Published
2011-05-04
Volume
28
Issue
10
Pages
2731-2739
ISSN
  • 0737-4038 (ISSN-L)
  • 1537-1719
OpenAlex
W2132632499
Cited by
39,969
References
4
FWCI
2078.08
Type
journal article
Language
en
Open access
green

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