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Masatoshi Nei

dblp:09/5473 · DBLP profile ↗
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6ranked-venue papers
0as first author
0since 2021 · last 2008
0009-0004-5863-277XORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 6

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
4 papers
Bioinformatics and computational biology · 100%

Topics — the 10 heaviest of 10, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
molecular evolution
0.022001
ADAPTSITE: detecting natural selection at single amino acid sites · Bioinform. 2001
MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers · Comput. Appl. Biosci. 1994
Bioinformatics and computational biology
phylogenetics
0.022001
ADAPTSITE: detecting natural selection at single amino acid sites · Bioinform. 2001
METREE: a program package for inferring and testing minimum-evolution trees · Comput. Appl. Biosci. 1994
Bioinformatics and computational biology › phylogenetics › evolutionary history reconstruction
ancestral sequence reconstruction
0.012001
ADAPTSITE: detecting natural selection at single amino acid sites · Bioinform. 2001
Bioinformatics and computational biology › population genetics
natural selection detection
0.012001
ADAPTSITE: detecting natural selection at single amino acid sites · Bioinform. 2001
Bioinformatics and computational biology › phylogenetics › phyloinformatics
phylogenetic analysis software
0.012001
MEGA2: molecular evolutionary genetics analysis software · Bioinform. 2001
Bioinformatics and computational biology › phylogenetics
evolutionary distance estimation
0.011994
MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers · Comput. Appl. Biosci. 1994
Bioinformatics and computational biology › phylogenetics › phylogenetic inference
maximum parsimony
0.011994
MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers · Comput. Appl. Biosci. 1994
Bioinformatics and computational biology › phylogenetics
phylogenetic inference
0.011994
MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers · Comput. Appl. Biosci. 1994
Bioinformatics and computational biology
sequence analysis
0.012001
MEGA2: molecular evolutionary genetics analysis software · Bioinform. 2001
Bioinformatics and computational biology › phylogenetics › phyloinformatics
phylogenetic tree editing
0.011994
MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers · Comput. Appl. Biosci. 1994

Methods — techniques the papers use, named apart from their topics

visual data representation · 0.0statistical methods for molecular evolution · 0.0maximum likelihood · 0.0binomial test · 0.0neighbor-joining · 0.0minimum evolution method · 0.0heuristic search · 0.0branch-and-bound search · 0.0UPGMA · 0.0
YearPublicationVenuePosition
2008 MEGA: A biologist-centric software for evolutionary analysis of DNA and protein sequences
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.
Sudhir Kumar 0001, Masatoshi Nei, Joel Dudley, Koichiro Tamura
Briefings Bioinform.2
2004 MEGA3: Integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment
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.
Sudhir Kumar 0001, Koichiro Tamura, Masatoshi Nei
Briefings Bioinform.3
2001 MEGA2: molecular evolutionary genetics analysis software
abstract
UNLABELLED: 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. AVAILABILITY: http://www.megasoftware.net. CONTACT: [email protected]
Sudhir Kumar 0001, Koichiro Tamura, Ingrid B. Jakobsen, Masatoshi Nei
Bioinform.4
2001 ADAPTSITE: detecting natural selection at single amino acid sites
abstract
UNLABELLED: ADAPTSITE is a program package for detecting natural selection at single amino acid sites, using a multiple alignment of protein-coding sequences for a given phylogenetic tree. The program infers ancestral codons at all interior nodes, and computes the total numbers of synonymous (c(S)) and nonsynonymous (c(N)) substitutions as well as the average numbers of synonymous (s(S)) and nonsynonymous (s(N)) sites for each codon site. The probabilities of occurrence of synonymous and nonsynonymous substitutions are approximated by s(S) / (s(S) + s(N)) and s(N) / (s(S) + s(N)), respectively. The null hypothesis of selective neutrality is tested for each codon site, assuming a binomial distribution for the probability of obtaining c(S) and c(N). AVAILABILITY: ADAPTSITE is available free of charge at the World-Wide Web sites http://mep.bio.psu.edu/adaptivevol.html and http://www.cib.nig.ac.jp/dda/yossuzuk/welcome.html. The package includes the source code written in C, binary files for UNIX operating systems, manual, and example files.
Yoshiyuki Suzuki, Takashi Gojobori, Masatoshi Nei
Bioinform.3
1994 MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers
abstract
A computer program package called MEGA has been developed for estimating evolutionary distances, reconstructing phylogenetic trees and computing basic statistical quantities from molecular data. It is written in C++ and is intended to be used on IBM and IBM-compatible personal computers. In this program, various methods for estimating evolutionary distances from nucleotide and amino acid sequence data, three different methods of phylogenetic inference (UPGMA, neighbor-joining and maximum parsimony) and two statistical tests of topological differences are included. For the maximum parsimony method, new algorithms of branch-and-bound and heuristic searches are implemented. In addition, MEGA computes statistical quantities such as nucleotide and amino acid frequencies, transition/transversion biases, codon frequencies (codon usage tables), and the number of variable sites in specified segments in nucleotide and amino acid sequences. Advanced on-screen sequence data and phylogenetic-tree editors facilitate publication-quality outputs with a wide range of printers. Integrated and interactive designs, on-line context-sensitive helps, and a text-file editor make MEGA easy to use.
Sudhir Kumar 0001, Koichiro Tamura, Masatoshi Nei
Comput. Appl. Biosci.3
1994 METREE: a program package for inferring and testing minimum-evolution trees
abstract
The METREE program package for estimating phylogenetic trees with the minimum evolution method is written in Turbo C 2.0 and is intended to be used on any IBM-compatible personal computers that have a mathematical coprocessor. The package is simple to use and is menu driven. A program for visualizing and printing out the final tree is also included.
Andrey Rzhetsky, Masatoshi Nei
Comput. Appl. Biosci.2