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. 2008 Jul;9(4):299-306.
doi: 10.1093/bib/bbn017. Epub 2008 Apr 16.

MEGA: a biologist-centric software for evolutionary analysis of DNA and protein sequences

Sudhir Kumar  1 , Masatoshi Nei, Joel Dudley, Koichiro Tamura
Affiliations

MEGA: a biologist-centric software for evolutionary analysis of DNA and protein sequences

Sudhir Kumar et al. Brief Bioinform. 2008 Jul.

Abstract

The Molecular Evolutionary Genetics Analysis (MEGA) software is a desktop application designed for comparative analysis of homologous gene sequences either from multigene families or from different species with a special emphasis on inferring evolutionary relationships and patterns of DNA and protein evolution. In addition to the tools for statistical analysis of data, MEGA provides many convenient facilities for the assembly of sequence data sets from files or web-based repositories, and it includes tools for visual presentation of the results obtained in the form of interactive phylogenetic trees and evolutionary distance matrices. Here we discuss the motivation, design principles and priorities that have shaped the development of MEGA. We also discuss how MEGA might evolve in the future to assist researchers in their growing need to analyze large data set using new computational methods.

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Figures

Figure 1
Figure 1
A list of primary features in MEGA. An asterix (*) marks features that are expected to be included in versions 4.1, 4.2, and 5.
Figure 2
Figure 2
Screenshots of the first version of MEGA containg a character-based point-and-click interface for use on DOS (A). MEGA 1 evolved into a Windows program (MEGA 2) with an extensive graphical user-interface (B). The main MEGA windows are overlaid with the Input Sequence Data Explorer, in which columns containing at least two different types of nucleotides (variable sites) are highlighted.
Figure 3
Figure 3
Number of MEGA citations each year (ISI Web of Science, February 2008 edition).
See this image and copyright information in PMC

References

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    1. Felsenstein J. PHYLIP: Phylogenetic Inference Package. University of Washington; Seattle, WA: 1993.
    1. Felsenstein J. Inferring phylogenies. Sunderland, Mass.: Sinauer Associates; 2004.
    1. Nei M. Molecular evolutionary genetics. New York: Columbia University Press; 1987.
    1. Nei M, Kumar S. Molecular Evolution and Phylogenetics. New York: Oxford University Press; 2000.

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