Tohru Daikoku

109 total papers · 3.8k total citations
102 papers, 3.1k citations indexed

About

Tohru Daikoku is a scholar working on Epidemiology, Immunology and Genetics. According to data from OpenAlex, Tohru Daikoku has authored 102 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 83 papers in Epidemiology, 31 papers in Immunology and 24 papers in Genetics. Recurrent topics in Tohru Daikoku's work include Herpesvirus Infections and Treatments (56 papers), Cytomegalovirus and herpesvirus research (40 papers) and Virus-based gene therapy research (24 papers). Tohru Daikoku is often cited by papers focused on Herpesvirus Infections and Treatments (56 papers), Cytomegalovirus and herpesvirus research (40 papers) and Virus-based gene therapy research (24 papers). Tohru Daikoku collaborates with scholars based in Japan, United Kingdom and United States. Tohru Daikoku's co-authors include Yukihiro Nishiyama, Kimíyasu Shiraki, Tatsuya Tsurumi, Fumi Goshima, Hiroki Isomura, Ayumi Kudoh, Hiroki Takakuwa, Noriko Shirata, Yutaka Sugaya and Masatoshi Fujita and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and The Journal of Immunology.

In The Last Decade

Tohru Daikoku

97 papers receiving 3.0k citations

Hit Papers

Favipiravir, an anti-infl... 2020 2026 2022 2024 2020 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Tohru Daikoku 1.9k 750 682 634 567 102 3.1k
Meihan Nonoyama 1.7k 0.9× 1.8k 2.4× 495 0.7× 432 0.7× 867 1.5× 116 3.3k
Nathaniel J. Moorman 1.6k 0.8× 457 0.6× 1.3k 1.9× 793 1.3× 626 1.1× 90 3.3k
Robert T. Sarisky 1.5k 0.8× 446 0.6× 644 0.9× 809 1.3× 560 1.0× 65 3.0k
Luis M. Schang 1.3k 0.7× 364 0.5× 803 1.2× 648 1.0× 321 0.6× 70 2.7k
Eng‐Shang Huang 1.8k 1.0× 719 1.0× 875 1.3× 622 1.0× 368 0.6× 60 3.2k
Dong Yü 2.2k 1.2× 345 0.5× 1.5k 2.1× 906 1.4× 621 1.1× 71 3.9k
P. De Somer 1.0k 0.5× 703 0.9× 1.4k 2.1× 1.3k 2.0× 562 1.0× 156 4.4k
Tao Peng 1.4k 0.7× 500 0.7× 1.9k 2.8× 928 1.5× 788 1.4× 179 4.9k
Arianna Loregian 1.8k 0.9× 365 0.5× 1.2k 1.7× 572 0.9× 525 0.9× 112 3.3k
Brian E. Gilbert 1.8k 0.9× 337 0.4× 1.2k 1.7× 684 1.1× 1.0k 1.8× 118 4.6k

Countries citing papers authored by Tohru Daikoku

Since Specialization
Citations

This map shows the geographic impact of Tohru Daikoku's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tohru Daikoku with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tohru Daikoku more than expected).

Fields of papers citing papers by Tohru Daikoku

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tohru Daikoku. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tohru Daikoku. The network helps show where Tohru Daikoku may publish in the future.

Co-authorship network of co-authors of Tohru Daikoku

This figure shows the co-authorship network connecting the top 25 collaborators of Tohru Daikoku. A scholar is included among the top collaborators of Tohru Daikoku based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tohru Daikoku. Tohru Daikoku is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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