Tomoki Yoshikawa

5.6k total citations
106 papers, 2.9k citations indexed

About

Tomoki Yoshikawa is a scholar working on Infectious Diseases, Epidemiology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Tomoki Yoshikawa has authored 106 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Infectious Diseases, 37 papers in Epidemiology and 20 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Tomoki Yoshikawa's work include Viral Infections and Vectors (41 papers), Viral Infections and Outbreaks Research (31 papers) and Vector-Borne Animal Diseases (19 papers). Tomoki Yoshikawa is often cited by papers focused on Viral Infections and Vectors (41 papers), Viral Infections and Outbreaks Research (31 papers) and Vector-Borne Animal Diseases (19 papers). Tomoki Yoshikawa collaborates with scholars based in Japan, United States and China. Tomoki Yoshikawa's co-authors include Masayuki Saijo, Shigeru Morikawa, Masayuki Shimojima, Shuetsu Fukushi, Takeshi Kurata, C. J. Peters, Terence E. Hill, Chien‐Te K. Tseng, Hideki Hasegawa and Tetsutaro Sata and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Journal of Clinical Investigation.

In The Last Decade

Tomoki Yoshikawa

102 papers receiving 2.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Tomoki Yoshikawa Japan 28 1.5k 1.0k 644 439 342 106 2.9k
Xiao‐Ai Zhang China 34 1.9k 1.3× 573 0.6× 307 0.5× 549 1.3× 511 1.5× 174 3.6k
Masayuki Shimojima Japan 35 2.8k 1.9× 1.2k 1.1× 547 0.8× 734 1.7× 624 1.8× 155 4.3k
Tino F. Schwarz Germany 33 1.6k 1.0× 2.1k 2.1× 542 0.8× 284 0.6× 477 1.4× 132 4.0k
Maria Grazia Cusi Italy 32 1.3k 0.9× 746 0.7× 996 1.5× 232 0.5× 531 1.6× 158 3.3k
Nazir Savji United States 23 1.3k 0.9× 440 0.4× 382 0.6× 377 0.9× 868 2.5× 38 2.5k
Young Ki Choi South Korea 43 3.1k 2.1× 2.9k 2.9× 770 1.2× 328 0.7× 349 1.0× 188 5.8k
Anita K. McElroy United States 30 2.3k 1.5× 687 0.7× 384 0.6× 370 0.8× 426 1.2× 76 3.3k
Jonas Klingström Sweden 33 2.6k 1.7× 384 0.4× 843 1.3× 495 1.1× 630 1.8× 98 3.6k
Harutaka Katano Japan 39 1.6k 1.1× 1.7k 1.6× 813 1.3× 272 0.6× 165 0.5× 194 4.8k

Countries citing papers authored by Tomoki Yoshikawa

Since Specialization
Citations

This map shows the geographic impact of Tomoki Yoshikawa'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 Tomoki Yoshikawa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tomoki Yoshikawa more than expected).

Fields of papers citing papers by Tomoki Yoshikawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tomoki Yoshikawa. 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 Tomoki Yoshikawa. The network helps show where Tomoki Yoshikawa may publish in the future.

Co-authorship network of co-authors of Tomoki Yoshikawa

This figure shows the co-authorship network connecting the top 25 collaborators of Tomoki Yoshikawa. A scholar is included among the top collaborators of Tomoki Yoshikawa 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 Tomoki Yoshikawa. Tomoki Yoshikawa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kiyotoki, Shu, Toru Takahashi, Masayuki Shimojima, et al.. (2025). First case of nosocomial transmission of severe fever with thrombocytopenia syndrome in Japan. International Journal of Infectious Diseases. 160. 108057–108057.
2.
Saijo, Masayuki, Koichi Izumikawa, Koichiro Suemori, et al.. (2025). Efficacy of favipiravir treatment for patients with severe fever with thrombocytopenia syndrome assessed with a historical control. Antimicrobial Agents and Chemotherapy. 69(12). e0106225–e0106225.
3.
Kurosu, Takeshi, Yusuke Sakai, Masayuki Shimojima, et al.. (2024). Mice, myeloid cells, and dengue: a new model for unraveling vascular leakage mysteries. Frontiers in Microbiology. 15. 1367672–1367672. 1 indexed citations
4.
Kurosu, Takeshi, Daisuke Okuzaki, Yusuke Sakai, et al.. (2023). Dengue virus infection induces selective expansion of Vγ4 and Vγ6TCR γδ T cells in the small intestine and a cytokine storm driving vascular leakage in mice. PLoS neglected tropical diseases. 17(11). e0011743–e0011743. 4 indexed citations
5.
6.
Suzuki, Tetsuya, Sho Saito, Shinya Tsuzuki, et al.. (2023). Protocol of Tecopox study: a multicentre, open-label, double-arm trial to evaluate the efficacy and safety of oral tecovirimat therapy for patients with smallpox or monkeypox. BMJ Open. 13(8). e069550–e069550. 4 indexed citations
7.
8.
Taniguchi, Satoshi, Takuya Inagaki, Shigeru Tajima, et al.. (2022). Reverse Genetics System for Heartland Bandavirus: NSs Protein Contributes to Heartland Bandavirus Virulence. Journal of Virology. 96(7). e0004922–e0004922. 10 indexed citations
9.
Shimojima, Masayuki, Kunihiko Umekita, Taishi Onodera, et al.. (2022). Neutralizing mAbs against SFTS Virus Gn Protein Show Strong Therapeutic Effects in an SFTS Animal Model. Viruses. 14(8). 1665–1665. 10 indexed citations
10.
Еремеев, С. В., Tomoki Yoshikawa, Takayuki Muro, et al.. (2021). Bulk Dirac cone and highly anisotropic electronic structure of NiTe2. Physical review. B.. 104(15). 8 indexed citations
11.
Yoshikawa, Tomoki, Souichi Yamada, Takuya Inagaki, et al.. (2020). Association of human cytomegalovirus (HCMV) neutralizing antibodies with antibodies to the HCMV glycoprotein complexes. Virology Journal. 17(1). 120–120. 8 indexed citations
12.
Shimojima, Masayuki, et al.. (2020). Efficient functional screening of a cellular cDNA library to identify severe fever with thrombocytopenia syndrome virus entry factors. Scientific Reports. 10(1). 5996–5996. 9 indexed citations
13.
Suzuki, Tadaki, Yuko Sato, Kaori Sano, et al.. (2020). Severe fever with thrombocytopenia syndrome virus targets B cells in lethal human infections. Journal of Clinical Investigation. 130(2). 799–812. 79 indexed citations
14.
Fujii, H, Tomoki Yoshikawa, Souichi Yamada, et al.. (2017). Association between sensitivity of viral thymidine kinase-associated acyclovir-resistant herpes simplex virus type 1 and virulence. Virology Journal. 14(1). 59–59. 8 indexed citations
15.
16.
Inoue, Kōichi, Hiroshi Takano, Rie Yanagisawa, et al.. (2007). Effects of inhaled nanoparticles on acute lung injury induced by lipopolysaccharide in mice. Toxicology. 238(2-3). 99–110. 56 indexed citations
17.
Ito, Kazuo, Junichi Shimada, Dai Kato, et al.. (2004). Protective effects of preischemic treatment with pioglitazone, a peroxisome proliferator-activated receptor-γ ligand, on lung ischemia-reperfusion injury in rats. European Journal of Cardio-Thoracic Surgery. 25(4). 530–536. 56 indexed citations
18.
Chen, Ze, Shin-etsu Kadowaki, Yukari Hagiwara, et al.. (2001). Protection against influenza B virus infection by immunization with DNA vaccines. Vaccine. 19(11-12). 1446–1455. 31 indexed citations
19.
SATO, Kunitada, et al.. (1975). Die schnelle kolorimetrische bestimmung der ostrogenen hormone bei trachtigen stuten. 9(2). 249–256. 1 indexed citations
20.
SATO, Kunitada, et al.. (1973). An Analytical Study on the Duration of Gestation in Horses. Nihon Chikusan Gakkaiho. 44(7). 375–379. 7 indexed citations

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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