Literature DB >> 18417537

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

Sudhir Kumar1, Masatoshi Nei, Joel Dudley, Koichiro Tamura.   

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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Year:  2008        PMID: 18417537      PMCID: PMC2562624          DOI: 10.1093/bib/bbn017

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  8 in total

1.  MEGA2: molecular evolutionary genetics analysis software.

Authors:  S Kumar; K Tamura; I B Jakobsen; M Nei
Journal:  Bioinformatics       Date:  2001-12       Impact factor: 6.937

2.  MEGA3: Integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment.

Authors:  Sudhir Kumar; Koichiro Tamura; Masatoshi Nei
Journal:  Brief Bioinform       Date:  2004-06       Impact factor: 11.622

3.  Bioinformatics software for biologists in the genomics era.

Authors:  Sudhir Kumar; Joel Dudley
Journal:  Bioinformatics       Date:  2007-05-07       Impact factor: 6.937

4.  MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0.

Authors:  Koichiro Tamura; Joel Dudley; Masatoshi Nei; Sudhir Kumar
Journal:  Mol Biol Evol       Date:  2007-05-07       Impact factor: 16.240

5.  Using CLUSTAL for multiple sequence alignments.

Authors:  D G Higgins; J D Thompson; T J Gibson
Journal:  Methods Enzymol       Date:  1996       Impact factor: 1.600

6.  The neighbor-joining method: a new method for reconstructing phylogenetic trees.

Authors:  N Saitou; M Nei
Journal:  Mol Biol Evol       Date:  1987-07       Impact factor: 16.240

7.  Phylogenetic test of the molecular clock and linearized trees.

Authors:  N Takezaki; A Rzhetsky; M Nei
Journal:  Mol Biol Evol       Date:  1995-09       Impact factor: 16.240

8.  MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers.

Authors:  S Kumar; K Tamura; M Nei
Journal:  Comput Appl Biosci       Date:  1994-04
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