MEGA3: Integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment (original) (raw)

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Director of the Center for Evolutionary Functional Genomics in The Biodesign Institute at Arizona State University since 2002. His research interests include development of software, statistical methods and computational tools for comparative sequence analysis. He and Koichiro Tamura are joint first authors of the MEGA3 software.

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Molecular evolutionist at the Tokyo Metropolitan University. His research interests are in the area of experimental, theoretical and computational molecular evolution.

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Director of the Institute of Molecular Evolutionary Genetics at the Penn State University since 1990. His research interests are in molecular evolutionary genetics and genomics.

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Sudhir Kumar, Koichiro Tamura, Masatoshi Nei, MEGA3: Integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment, Briefings in Bioinformatics, Volume 5, Issue 2, June 2004, Pages 150–163, https://doi.org/10.1093/bib/5.2.150
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Abstract

With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of species and multigene families, estimating rates of molecular evolution, and inferring the nature and extent of selective forces shaping the evolution of genes and genomes. The scope of these investigations has now expanded greatly owing to the development of high-throughput sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. One such effort has been to produce Molecular Evolutionary Genetics Analysis (MEGA) software, with its focus on facilitating the exploration and analysis of the DNA and protein sequence variation from an evolutionary perspective. Currently in its third major release, MEGA3 contains facilities for automatic and manual sequence alignment, web-based mining of databases, inference of the phylogenetic trees, estimation of evolutionary distances and testing evolutionary hypotheses. This paper provides an overview of the statistical methods, computational tools, and visual exploration modules for data input and the results obtainable in MEGA.

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