World's Best Scientists 2026 revealed!

D-Index & Metrics

Genetics

D-Index
60
Citations
20212
World Ranking
3118
National Ranking
137

Kenta Nakai 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 Kenta Nakai 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: 228 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Kenta Nakai 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 Kenta Nakai 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: 60 D-Index — 29th percentile

29% of scientists in this discipline score the same or lower.

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

Overview

Kenta Nakai is affiliated with the University of Tokyo in Japan. Their research primarily focuses on the field of Biochemistry, Genetics and Molecular Biology, with a particular emphasis on Molecular Biology, Cancer Research, Genetics, Immunology, and Surgery. The scientist's work encompasses a broad range of topics, including:

  • Single-cell and spatial transcriptomics
  • RNA and protein synthesis mechanisms
  • Machine Learning in Bioinformatics
  • Genomics and Chromatin Dynamics
  • Gene expression and cancer classification
  • Epigenetics and DNA Methylation
  • Immune cells in cancer

The recent scholarly contributions by Kenta Nakai include several papers published between 2022 and 2023. Notable publications are:

  • "iDNA-ABF: multi-scale deep biological language learning model for the interpretable prediction of DNA methylations" (2022), published in Genome Biology
  • "DeepBIO: an automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation and visualization analysis" (2023), published in Nucleic Acids Research
  • "Predicting protein-peptide binding residues via interpretable deep learning" (2022), published in Bioinformatics
  • "Protein design via deep learning" (2022), published in Briefings in Bioinformatics
  • "scIMC: a platform for benchmarking comparison and visualization analysis of scRNA-seq data imputation methods" (2022), published in Nucleic Acids Research

Kenta Nakai frequently collaborates with a group of co-authors, among whom the most frequent are:

  • Sung-Joon Park
  • Martin Loza
  • Leyi Wei
  • Ruheng Wang
  • Weihang Zhang

The scientist's work appears regularly in several publication venues. These include:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Briefings in Bioinformatics
  • Frontiers in Genetics
  • NAR Genomics and Bioinformatics
  • Nucleic Acids Research

Best Publications

  • A knowledge base for predicting protein localization sites in eukaryotic cells

    Kenta Nakai;Minoru Kanehisa

  • The Jmjd3-Irf4 axis regulates M2 macrophage polarization and host responses against helminth infection

    Takashi Satoh;Osamu Takeuchi;Alexis Vandenbon;Koubun Yasuda

  • Complete sequencing and characterization of 21,243 full-length human cDNAs

    Toshio Ota;Yutaka Suzuki;Tetsuo Nishikawa;Tetsuji Otsuki

  • Expert System for predicting protein localization sites in Gram-negative bacteria

    Kenta Nakai;Minoru Kanehisa

  • PrognoScan: a new database for meta-analysis of the prognostic value of genes

    Hideaki Mizuno;Hideaki Mizuno;Kunio Kitada;Kenta Nakai;Akinori Sarai

  • Extensive feature detection of N-terminal protein sorting signals.

    Hideo Bannai;Yoshinori Tamada;Osamu Maruyama;Kenta Nakai

  • T Cell Receptor Stimulation-Induced Epigenetic Changes and Foxp3 Expression Are Independent and Complementary Events Required for Treg Cell Development

    Naganari Ohkura;Naganari Ohkura;Masahide Hamaguchi;Masahide Hamaguchi;Hiromasa Morikawa;Hiromasa Morikawa;Kyoko Sugimura

  • Diversification of transcriptional modulation: Large-scale identification and characterization of putative alternative promoters of human genes

    Kouichi Kimura;Ai Wakamatsu;Yutaka Suzuki;Toshio Ota

  • PSORT-B: Improving protein subcellular localization prediction for Gram-negative bacteria.

    Jennifer L. Gardy;Cory Spencer;Ke Wang;Martin Ester

  • Assessment of prediction accuracy of protein function from protein–protein interaction data

    Haretsugu Hishigaki;Haretsugu Hishigaki;Kenta Nakai;Toshihide Ono;Akira Tanigami

  • DBTBS: a database of transcriptional regulation in Bacillus subtilis containing upstream intergenic conservation information

    Nicolas Sierro;Yuko Makita;Michiel J. L. de Hoon;Kenta Nakai

  • ATTED-II: a database of co-expressed genes and cis elements for identifying co-regulated gene groups in Arabidopsis

    Takeshi Obayashi;Kengo Kinoshita;Kenta Nakai;Masayuki Shibaoka

  • Integrative Annotation of 21,037 Human Genes Validated by Full-Length cDNA Clones

    Tadashi Imanishi;Takeshi Itoh;Yutaka Suzuki;Claire O'Donovan

  • Protein sorting signals and prediction of subcellular localization.

    Kenta Nakai

  • Cluster analysis of amino acid indices for prediction of protein structure and function.

    Kenta Nakai;Akinori Kidera;Minoru Kanehisa

  • PROTEIN SUBCELLULAR LOCALIZATION PREDICTION WITH WOLF PSORT

    Paul Horton;Keun-Joon Park;Keun-Joon Park;Takeshi Obayashi;Kenta Nakai

  • DBTSS: DataBase of human Transcriptional Start Sites and full-length cDNAs

    Yutaka Suzuki;Riu Yamashita;Kenta Nakai;Sumio Sugano

  • Prediction of Transcriptional Terminators in Bacillus subtilis and Related Species

    Michiel J. L. de Hoon;Yuko Makita;Kenta Nakai;Satoru Miyano

  • DBTSS: DataBase of Human Transcription Start Sites, progress report 2006

    Riu Yamashita;Yutaka Suzuki;Hiroyuki Wakaguri;Katsuki Tsuritani

  • Encyclopedia of bioinformatics and computational biology

    Shoba Ranganathan;Michael Gribskov;Kenta Nakai;Christian Schönbach

Frequent Co-Authors

Yutaka Suzuki
Yutaka Suzuki University of Tokyo
Sumio Sugano
Sumio Sugano University of Tokyo
Satoru Miyano
Satoru Miyano Tokyo Medical and Dental University
Toshihisa Takagi
Toshihisa Takagi University of Tokyo
Takashi Gojobori
Takashi Gojobori King Abdullah University of Science and Technology
Shoba Ranganathan
Shoba Ranganathan Macquarie University
Hitomi Mimuro
Hitomi Mimuro Osaka University
Kengo Kinoshita
Kengo Kinoshita Tohoku University
Minoru Kanehisa
Minoru Kanehisa Kyoto University

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