MEGA2: Molecular evolutionary genetics analysis software

Sudhir Kumar; Koichiro Tamura; Ingrid B. Jakobsen; Masatoshi Nei

doi:10.1093/bioinformatics/17.12.1244

MEGA2: Molecular evolutionary genetics analysis software

Sudhir Kumar, Koichiro Tamura, Ingrid B. Jakobsen, Masatoshi Nei

Life Sciences, School of (SOLS)

Research output: Contribution to journal › Article › peer-review

4579 Scopus citations

Abstract

We have developed a new software package, Molecular Evolutionary Genetics Analysis version 2 (MEGA2), for exploring and analyzing aligned DNA or protein sequences from an evolutionary perspective. MEGA2 vastly extends the capabilities of MEGA version 1 by: (1) facilitating analyses of large datasets; (2) enabling creation and analyses of groups of sequences; (3) enabling specification of domains and genes; (4) expanding the repertoire of statistical methods for molecular evolutionary studies; and (5) adding new modules for visual representation of input data and output results on the Microsoft Windows platform.

Original language	English (US)
Pages (from-to)	1244-1245
Number of pages	2
Journal	Bioinformatics
Volume	17
Issue number	12
DOIs	https://doi.org/10.1093/bioinformatics/17.12.1244
State	Published - 2002

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/17.12.1244

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title = "MEGA2: Molecular evolutionary genetics analysis software",

abstract = "We have developed a new software package, Molecular Evolutionary Genetics Analysis version 2 (MEGA2), for exploring and analyzing aligned DNA or protein sequences from an evolutionary perspective. MEGA2 vastly extends the capabilities of MEGA version 1 by: (1) facilitating analyses of large datasets; (2) enabling creation and analyses of groups of sequences; (3) enabling specification of domains and genes; (4) expanding the repertoire of statistical methods for molecular evolutionary studies; and (5) adding new modules for visual representation of input data and output results on the Microsoft Windows platform.",

author = "Sudhir Kumar and Koichiro Tamura and Jakobsen, {Ingrid B.} and Masatoshi Nei",

note = "Funding Information: We thank colleagues, students, and volunteers for testing the pre-release versions and to Sudhindra Gadagkar for comments on an earlier draft. This project is supported by research grants from NIH, NSF and Burroughs–Wellcome Fund to S.K. and NIH, NSF and NASA to M.N.",

year = "2002",

doi = "10.1093/bioinformatics/17.12.1244",

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AU - Kumar, Sudhir

AU - Tamura, Koichiro

AU - Jakobsen, Ingrid B.

AU - Nei, Masatoshi

N1 - Funding Information: We thank colleagues, students, and volunteers for testing the pre-release versions and to Sudhindra Gadagkar for comments on an earlier draft. This project is supported by research grants from NIH, NSF and Burroughs–Wellcome Fund to S.K. and NIH, NSF and NASA to M.N.

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N2 - We have developed a new software package, Molecular Evolutionary Genetics Analysis version 2 (MEGA2), for exploring and analyzing aligned DNA or protein sequences from an evolutionary perspective. MEGA2 vastly extends the capabilities of MEGA version 1 by: (1) facilitating analyses of large datasets; (2) enabling creation and analyses of groups of sequences; (3) enabling specification of domains and genes; (4) expanding the repertoire of statistical methods for molecular evolutionary studies; and (5) adding new modules for visual representation of input data and output results on the Microsoft Windows platform.

AB - We have developed a new software package, Molecular Evolutionary Genetics Analysis version 2 (MEGA2), for exploring and analyzing aligned DNA or protein sequences from an evolutionary perspective. MEGA2 vastly extends the capabilities of MEGA version 1 by: (1) facilitating analyses of large datasets; (2) enabling creation and analyses of groups of sequences; (3) enabling specification of domains and genes; (4) expanding the repertoire of statistical methods for molecular evolutionary studies; and (5) adding new modules for visual representation of input data and output results on the Microsoft Windows platform.

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MEGA2: Molecular evolutionary genetics analysis software

Abstract

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