World's Best Scientists 2026 revealed!

D-Index & Metrics

Genetics

D-Index
59
Citations
20870
World Ranking
3201
National Ranking
140

Toshimichi Ikemura publication distribution in Genetics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Genetics in 2026. The highlighted bar marks where Toshimichi Ikemura sits on this spectrum.

45–54 publications: 6 scientists 55–64 publications: 10 scientists 65–74 publications: 35 scientists 75–84 publications: 84 scientists 85–94 publications: 102 scientists 95–104 publications: 151 scientists 105–114 publications: 175 scientists 115–124 publications: 203 scientists 125–134 publications: 217 scientists 135–144 publications: 205 scientists 145–154 publications: 193 scientists 155–164 publications: 188 scientists 165–174 publications: 170 scientists 175–184 publications: 178 scientists 185–194 publications: 164 scientists 195–204 publications: 173 scientists 205–214 publications: 159 scientists 215–224 publications: 134 scientists 225–234 publications: 143 scientists 235–244 publications: 105 scientists 245–254 publications: 114 scientists 255–264 publications: 92 scientists 265–274 publications: 88 scientists 275–284 publications: 87 scientists 285–294 publications: 80 scientists 295–304 publications: 62 scientists 305–314 publications: 75 scientists 315–324 publications: 67 scientists 325–334 publications: 60 scientists 335–344 publications: 52 scientists 345–354 publications: 40 scientists 355–364 publications: 48 scientists 365–374 publications: 47 scientists 375–384 publications: 46 scientists 385–394 publications: 31 scientists 395–404 publications: 27 scientists 405–414 publications: 40 scientists 415–424 publications: 30 scientists 425–434 publications: 43 scientists 435–444 publications: 29 scientists 445–454 publications: 14 scientists 455–464 publications: 28 scientists 465–474 publications: 21 scientists 475–484 publications: 21 scientists 485–494 publications: 22 scientists 495–504 publications: 17 scientists 505–514 publications: 12 scientists 515–524 publications: 11 scientists 525–534 publications: 8 scientists 535–544 publications: 8 scientists 545–554 publications: 14 scientists 555–564 publications: 4 scientists 565–574 publications: 11 scientists 575–584 publications: 5 scientists 585–594 publications: 11 scientists 595–604 publications: 12 scientists 605–614 publications: 7 scientists 615–624 publications: 6 scientists 625–634 publications: 10 scientists 635–644 publications: 9 scientists 645–654 publications: 10 scientists 655–664 publications: 6 scientists 665–674 publications: 6 scientists 675–684 publications: 6 scientists 685–694 publications: 4 scientists 695–702 publications: 6 scientists 703+ publications: 100 scientists
45 publications 703+

This scientist: 178 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 703 publications or more.

Toshimichi Ikemura D-index placement in Genetics in 2026

The chart shows the D-index (discipline H-index) distribution of Genetics scientists ranked by Research.com in 2026. The highlighted bar marks where Toshimichi Ikemura sits on this spectrum.

40–41 D-Index: 24 scientists 42–43 D-Index: 52 scientists 44–45 D-Index: 84 scientists 46–47 D-Index: 112 scientists 48–49 D-Index: 118 scientists 50–51 D-Index: 141 scientists 52–53 D-Index: 143 scientists 54–55 D-Index: 145 scientists 56–57 D-Index: 179 scientists 58–59 D-Index: 162 scientists 60–61 D-Index: 175 scientists 62–63 D-Index: 191 scientists 64–65 D-Index: 172 scientists 66–67 D-Index: 184 scientists 68–69 D-Index: 164 scientists 70–71 D-Index: 158 scientists 72–73 D-Index: 150 scientists 74–75 D-Index: 136 scientists 76–77 D-Index: 127 scientists 78–79 D-Index: 127 scientists 80–81 D-Index: 111 scientists 82–83 D-Index: 110 scientists 84–85 D-Index: 110 scientists 86–87 D-Index: 84 scientists 88–89 D-Index: 102 scientists 90–91 D-Index: 66 scientists 92–93 D-Index: 72 scientists 94–95 D-Index: 70 scientists 96–97 D-Index: 54 scientists 98–99 D-Index: 60 scientists 100–101 D-Index: 49 scientists 102–103 D-Index: 55 scientists 104–105 D-Index: 45 scientists 106–107 D-Index: 42 scientists 108–109 D-Index: 28 scientists 110–111 D-Index: 39 scientists 112–113 D-Index: 25 scientists 114–115 D-Index: 31 scientists 116–117 D-Index: 29 scientists 118–119 D-Index: 34 scientists 120–121 D-Index: 29 scientists 122–123 D-Index: 29 scientists 124–125 D-Index: 18 scientists 126–127 D-Index: 27 scientists 128–129 D-Index: 22 scientists 130–131 D-Index: 16 scientists 132–133 D-Index: 11 scientists 134–135 D-Index: 17 scientists 136–137 D-Index: 12 scientists 138–139 D-Index: 21 scientists 140–141 D-Index: 4 scientists 142–143 D-Index: 9 scientists 144–145 D-Index: 14 scientists 146–147 D-Index: 6 scientists 148–149 D-Index: 10 scientists 150–151 D-Index: 7 scientists 152–153 D-Index: 9 scientists 154–155 D-Index: 8 scientists 156–157 D-Index: 8 scientists 158–159 D-Index: 9 scientists 160+ D-Index: 96 scientists
40 D-Index 160+

This scientist: 59 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 160 D-Index or more.

Overview

Toshimichi Ikemura is affiliated with the Nagahama Institute of Bio-Science and Technology in Japan. Their research spans multiple disciplines within the life sciences, focusing primarily on areas related to biochemistry, genetics, molecular biology, medicine, and agricultural and biological sciences.

Their work heavily involves subfields such as molecular biology, infectious diseases, plant science, animal science and zoology, and ecology. Within these fields, Ikemura has contributed to topics including genomics and phylogenetic studies, SARS-CoV-2 and COVID-19 research, viral gastroenteritis research and epidemiology, chromosomal and genetic variations, machine learning in bioinformatics, RNA and protein synthesis mechanisms, and animal virus infection studies.

Ikemura has published regularly in notable venues. Frequent publication outlets include:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Research Square
  • Genes & Genetic Systems
  • BMC Microbiology
  • PLoS ONE

Collaborations have been significant throughout their career. Noteworthy coauthors consist of:

  • Yuki Iwasaki
  • Kennosuke Wada
  • Yoshiko Wada
  • Takashi Abe
  • Y Katsura

Representative recent papers authored or coauthored by Ikemura include:

  • "Time-series analyses of directional sequence changes in SARS-CoV-2 genomes and an efficient search method for candidates for advantageous mutations for growth in human cells," 2020, Gene
  • "Human cell-dependent, directional, time-dependent changes in the mono- and oligonucleotide compositions of SARS-CoV-2 genomes," 2021, BMC Microbiology
  • "Mb-level CpG and TFBS islands visualized by AI and their roles in the nuclear organization of the human genome," 2020, Genes & Genetic Systems
  • "Comparative genomics of Glandirana rugosa using unsupervised AI reveals a high CG frequency," 2021, Life Science Alliance
  • "Time-Series Trend of Pandemic SARS-CoV-2 Variants Visualized Using Batch-Learning Self-Organizing Map for Oligonucleotide Compositions," 2021, Data Science Journal

Their scientific output emphasizes the use of computational and artificial intelligence methods in genomics, particularly in visualizing genetic features and analyzing viral sequence evolution. This intersects with their broad interest in molecular mechanisms and pathogen genomics.

Best Publications

  • Codon usage and tRNA content in unicellular and multicellular organisms.

    T Ikemura

  • Correlation Between the Abundance of Escherichia Coli Transfer RNAs and the Occurrence of the Respective Codons in Its Protein Genes: A Proposal for a Synonymous Codon Choice That Is Optimal for the E. Coli Translational System

    Toshimichi Ikemura

  • Codon usage tabulated from international DNA sequence databases: status for the year 2000

    Yasukazu Nakamura;Takashi Gojobori;Toshimichi Ikemura

  • Correlation between the abundance of Escherichia coli transfer RNAs and the occurrence of the respective codons in its protein genes

    Toshimichi Ikemura

  • Rice Annotation Project Database (RAP-DB): an integrative and interactive database for rice genomics.

    Hiroaki Sakai;Sung Shin Lee;Tsuyoshi Tanaka;Hisataka Numa

  • Correlation between the abundance of yeast transfer RNAs and the occurrence of the respective codons in protein genes: Differences in synonymous codon choice patterns of yeast and Escherichia coli with reference to the abundance of isoaccepting transfer RNAs

    Toshimichi Ikemura

  • Codon usage tabulated from the GenBank genetic sequence data.

    Shin-ichi Aota;Takashi Gojobori;Fumie Ishibashi;Takeo Maruyama

  • Studies of codon usage and tRNA genes of 18 unicellular organisms and quantification of Bacillus subtilis tRNAs: gene expression level and species-specific diversity of codon usage based on multivariate analysis.

    Shigehiko Kanaya;Yuko Yamada;Yoshihiro Kudo;Toshimichi Ikemura

  • Substrate-induced gene-expression screening of environmental metagenome libraries for isolation of catabolic genes

    Taku Uchiyama;Takashi Abe;Toshimichi Ikemura;Kazuya Watanabe

  • Codon usage and tRNA genes in eukaryotes: correlation of codon usage diversity with translation efficiency and with CG-dinucleotide usage as assessed by multivariate analysis.

    Shigehiko Kanaya;Yuko Yamada;Makoto Kinouchi;Yoshihiro Kudo

  • Codon usage tabulated from the international DNA sequence databases

    Yasukazu Nakamura;Takashi Gojobori;Toshimichi Ikemura

  • Small Ribonucleic Acids of Escherichia coli I. CHARACTERIZATION BY POLYACRYLAMIDE GEL ELECTROPHORESIS AND FINGERPRINT ANALYSIS

    Toshimichi Ikemura;James E. Dahlberg

  • Informatics for Unveiling Hidden Genome Signatures

    Takashi Abe;Shigehiko Kanaya;Makoto Kinouchi;Yuta Ichiba

  • Three genes in the human MHC class III region near the junction with the class II: gene for receptor of advanced glycosylation end products, PBX2 homeobox gene and a notch homolog, human counterpart of mouse mammary tumor gene int-3.

    Kimihiko Sugaya;Tatsuo Fukagawa;Ken-ichi Matsumoto;Kazuei Mita

  • Specific Inactivation of 16S Ribosomal RNA Induced by Colicin E3 In Vivo

    C. M. Bowman;J. E. Dahlberg;T. Ikemura;J. Konisky

  • Diversity in G+C content at the third position of codons in vertebrate genes and its cause

    Shin-ichi Aota;Toshimichi Ikemura

  • Analysis of codon usage diversity of bacterial genes with a self-organizing map (SOM): characterization of horizontally transferred genes with emphasis on the E. coli O157 genome

    Shigehiko Kanaya;Makoto Kinouchi;Takashi Abe;Yoshihiro Kudo

  • Molecular dynamics of MHC genesis unraveled by sequence analysis of the 1,796,938-bp HLA class I region.

    Takashi Shiina;Gen Tamiya;Akira Oka;Nobusada Takishima

  • Chromosomal localization of the proteasome Z subunit gene reveals an ancient chromosomal duplication involving the major histocompatibility complex.

    Masanori Kasahara;Masaru Hayashi;Keiji Tanaka;Hidetoshi Inoko

  • Cordon usage tabulated from the Gen Bank genetic sequence data

    K. Wada;S. Aota;R. Tsuchiya;F. Ishibashi

Frequent Co-Authors

Shigehiko Kanaya
Shigehiko Kanaya Nara Institute of Science and Technology
Tatsuo Fukagawa
Tatsuo Fukagawa Osaka University
Hidetoshi Inoko
Hidetoshi Inoko Tokai University
Yasukazu Nakamura
Yasukazu Nakamura National Institute of Genetics
Takashi Gojobori
Takashi Gojobori King Abdullah University of Science and Technology
Hirotada Mori
Hirotada Mori Nara Institute of Science and Technology
Nobuhisa Mizuki
Nobuhisa Mizuki Yokohama City University
Ken Kurokawa
Ken Kurokawa National Institute of Genetics
Norihiro Okada
Norihiro Okada National Cheng Kung University

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