World's Best Scientists 2026 revealed!
Tetsuya Sakurai

Tetsuya Sakurai

D-Index & Metrics

Genetics

D-Index
56
Citations
19816
World Ranking
3457
National Ranking
155

Tetsuya Sakurai 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 Tetsuya Sakurai 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: 100 publications — 7th percentile

7% of scientists in this discipline score the same or lower.

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

Tetsuya Sakurai 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 Tetsuya Sakurai 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: 56 D-Index — 21st percentile

21% of scientists in this discipline score the same or lower.

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

Overview

Tetsuya Sakurai is affiliated with Kōchi University in Japan. Their research spans primarily the fields of Biochemistry, Genetics and Molecular Biology, with significant contributions also in Computer Science.

Their subfields of study include Molecular Biology, Artificial Intelligence, Cancer Research, Plant Science, and Ecology.

The main topics covered in their work include:

  • Cancer-related molecular mechanisms research
  • Gene expression and cancer classification
  • Genomics and Phylogenetic Studies
  • Machine Learning in Bioinformatics
  • RNA and protein synthesis mechanisms
  • Single-cell and spatial transcriptomics
  • RNA modifications and cancer

Sakurai has contributed to several recent publications, including:

  • "A genome resource for green millet Setaria viridis enables discovery of agronomically valuable loci," 2020, Nature Biotechnology
  • "m5U-SVM: identification of RNA 5-methyluridine modification sites based on multi-view features of physicochemical features and distributed representation," 2023, BMC Biology
  • "Deep generative model for drug design from protein target sequence," 2023, Journal of Cheminformatics
  • "iLoc-miRNA: extracellular/intracellular miRNA prediction using deep BiLSTM with attention mechanism," 2022, Briefings in Bioinformatics
  • "A BERT-based model for the prediction of lncRNA subcellular localization in Homo sapiens," 2024, International Journal of Biological Macromolecules

Frequent co-authors collaborating with Sakurai include:

  • Xiucai Ye
  • Yasunori Futamura
  • Ruheng Wang
  • Yaxuan Cui
  • Kenta Nakai

Sakurai's publications often appear in venues such as:

  • arXiv (Cornell University)
  • BMC Biology
  • Scientific Reports
  • Proceedings of the Genetic and Evolutionary Computation Conference Companion
  • Microbiology Resource Announcements

Best Publications

  • Genome sequence of the palaeopolyploid soybean

    Jeremy Schmutz;Steven B. Cannon;Jessica Schlueter;Jessica Schlueter;Jianxin Ma

  • Monitoring the expression profiles of 7000 Arabidopsis genes under drought, cold and high-salinity stresses using a full-length cDNA microarray.

    Motoaki Seki;Mari Narusaka;Junko Ishida;Tokihiko Nanjo

  • Empirical analysis of transcriptional activity in the Arabidopsis genome.

    Kayoko Yamada;Jun Lim;Joseph M. Dale;Huaming Chen;Huaming Chen

  • Functional annotation of a full-length Arabidopsis cDNA collection.

    Motoaki Seki;Mari Narusaka;Asako Kamiya;Junko Ishida

  • Comparative Genomics in Salt Tolerance between Arabidopsis and Arabidopsis-Related Halophyte Salt Cress Using Arabidopsis Microarray

    Teruaki Taji;Motoaki Seki;Masakazu Satou;Tetsuya Sakurai

  • The AtGenExpress hormone and chemical treatment data set: experimental design, data evaluation, model data analysis and data access.

    Hideki Goda;Eriko Sasaki;Kenji Akiyama;Akiko Maruyama-Nakashita

  • Monitoring the expression pattern of around 7,000 Arabidopsis genes under ABA treatments using a full-length cDNA microarray

    Motoaki Seki;Junko Ishida;Mari Narusaka;Miki Fujita

  • Monitoring Expression Profiles of Arabidopsis Gene Expression during Rehydration Process after Dehydration Using ca. 7000 Full-Length cDNA Microarray

    Youko Oono;Motoaki Seki;Tokihiko Nanjo;Mari Narusaka

  • Identification of cis-acting promoter elements in cold- and dehydration-induced transcriptional pathways in Arabidopsis, rice, and soybean.

    Kyonoshin Maruyama;Daisuke Todaka;Junya Mizoi;Takuya Yoshida

  • RIKEN tandem mass spectral database (ReSpect) for phytochemicals: a plant-specific MS/MS-based data resource and database.

    Yuji Sawada;Ryo Nakabayashi;Yutaka Yamada;Makoto Suzuki

  • Widely targeted metabolomics based on large-scale MS/MS data for elucidating metabolite accumulation patterns in plants.

    Yuji Sawada;Kenji Akiyama;Akane Sakata;Ayuko Kuwahara

  • Genome-wide analysis of alternative pre-mRNA splicing in Arabidopsis thaliana based on full-length cDNA sequences

    Kei Iida;Motoaki Seki;Tetsuya Sakurai;Masakazu Satou

  • A collection of 11 800 single-copy Ds transposon insertion lines in Arabidopsis.

    Takashi Kuromori;Takashi Hirayama;Yuki Kiyosue;Hiroko Takabe

  • Identification of Arabidopsis genes regulated by high light-stress using cDNA microarray.

    Mitsuhiro Kimura;Yoshiharu Y. Yamamoto;Motoaki Seki;Tetsuya Sakurai

  • Curated genome annotation of Oryza sativa ssp. japonica and comparative genome analysis with Arabidopsis thaliana

    Takeshi Itoh;Takeshi Itoh;Tsuyoshi Tanaka;Roberto A. Barrero;Chisato Yamasaki

  • AtMetExpress Development: A Phytochemical Atlas of Arabidopsis Development

    Fumio Matsuda;Masami Y. Hirai;Eriko Sasaki;Kenji Akiyama

  • PRIMe: a Web site that assembles tools for metabolomics and transcriptomics.

    Kenji Akiyama;Eisuke Chikayama;Hiroaki Yuasa;Yukihisa Shimada

  • Identification of plant promoter constituents by analysis of local distribution of short sequences

    Yoshiharu Y Yamamoto;Hiroyuki Ichida;Minami Matsui;Junichi Obokata

  • Monitoring expression profiles of Arabidopsis genes during cold acclimation and deacclimation using DNA microarrays

    Youko Oono;Motoaki Seki;Masakazu Satou;Kei Iida

  • Monitoring the expression profiles of genes induced by hyperosmotic, high salinity, and oxidative stress and abscisic acid treatment in Arabidopsis cell culture using a full-length cDNA microarray

    Seiji Takahashi;Motoaki Seki;Junko Ishida;Masakazu Satou

Frequent Co-Authors

Kazuko Yamaguchi-Shinozaki
Kazuko Yamaguchi-Shinozaki University of Tokyo
Mari Narusaka
Mari Narusaka National Institute for Basic Biology
Hitoshi Sakakibara
Hitoshi Sakakibara Nagoya University
Miki Fujita
Miki Fujita University of British Columbia
Takashi Kuromori
Takashi Kuromori Okayama University

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