MEGA: the genetics software and the MEGA-minds behind it

MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers. Kumar S, Tamura K, Nei M. Comput Appl Biosci. 1994 Apr;10(2):189-91. doi: 10.1093/bioinformatics/10.2.189.
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How is phylogenetic analysis so quick and easy these days? The current software available in the genetics world have made genetic analysis extremely efficient to conduct. But what was it like before this software, and how did one of the most influential ones, MEGA, become what it is today?
MEGA, first released in 1994, is comprehensive and efficient genetics software that aids in the production of phylogenetic trees and conducting statistical analysis of genetic data. Even the first version released in 1994 contained many highly advanced genetic analysis tools, making the software ahead of its time. MEGA is extremely powerful and can conduct genetic analysis and produce visualisation of molecular evolution by determining the relationships of DNA sequences inputted by users. The sequences can either be in the form of nucleotides or amino acids, and MEGA is capable of determining evolutionary relationships even with missing data points. The algorithm is not only highly capable of great genetic analysis, but the software is designed to be user friendly, with a simple interface and easy to use editing tools provided so users can produce the exact outcome they require.
The algorithm has been refined and improved with the increased prevalence of technology in the scientific world, with the software now being a highly capable tool which is able to extend much further beyond its original capabilities. That’s MEGA-mazing if you ask me.
Creator: Lily
References:
Hall BG. Building phylogenetic trees from molecular data with MEGA. Mol Biol Evol. 2013;30(5):1229-1235.
Ellsworth DL, Hallman DM, Boerwinkle E. Impact of the Human Genome Project on epidemiologic research. Epidemiol Rev. 1997;19(1):3-13.
Sigwart JD, Garbett A. Biodiversity assessment, DNA barcoding, and the minority majority. Integr Comp Biol. 2018;58(6):1146-1156.
Gonzales MJ, Dugan JM, Shafer RW. Synonymous-non-synonymous mutation rates between sequences containing ambiguous nucleotides (Syn-SCAN). Bioinformatics. 2002;18(6):886-887.
Wunderlich S, Gatto KA. Consumer perception of genetically modified organisms and sources of information. Adv Nutr. 2015;6(6):842-851.
Kumar S, Stecher G, Tamura K. MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33(7):1870-1874.
Kumar S, Tamura K, Nei M. MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers. Comput Appl Biosci. 1994;10(2):189-191.
Kumar S, Nei M, Dudley J, Tamura K. MEGA: a biologist-centric software for evolutionary analysis of DNA and protein sequences. Brief Bioinform. 2008;9(4):299-306.