Tadaki Suzuki

16.8k citations
224 papers · 6.3k indexed · 3 hit papers · h-index 39
    • SARS-CoV-2 and COVID-19 Research 61
    • COVID-19 Clinical Research Studies 49
    • Viral Infections and Vectors 29
    • SARS-CoV-2 detection and testing 26
    • Viral Infections and Outbreaks Research 19
  • Immunology top 2%
    • Influenza Virus Research Studies 34
    • Respiratory viral infections research 27
  • Virology top 5%
    • Polyomavirus and related diseases 30

Tadaki Suzuki

207 papers receiving 6.3k citations

Hit Papers

SARS-CoV-2 D614G spike mutation ...3102013202620172021250500750

Peers

Tadaki Suzuki
Comparison fields: 5 of 144
  • Infectious Diseases 3.3k
  • Immunology 1.3k
  • Epidemiology 1.5k
  • Animal Science and Zoology 433
  • Virology 138
Replace Jie Zhou with:
Jie Zhou China
Jinxia Zhang China
Yi Shi China
Atsushi Okumura United States
Vincent Kwok‐Man Poon Hong Kong
Mehul S. Suthar United States
Olfert Landt Germany
Anja Kipar United Kingdom
Colleen B. Jonsson United States
Raymond J. Pickles United States
Tadaki Suzuki relative to Jie Zhou China Jie Zhou's profile →
Citations per field
00.5×1.6×
Jie Zhou · 1×
Citations per year

Countries citing papers authored by Tadaki Suzuki

Since Specialization
Citations

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

Fields of papers citing papers by Tadaki Suzuki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Tadaki Suzuki, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tadaki Suzuki Line = papers co-authored together Tadaki Suzuki links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20252
2 20250
3 20242
4 202338
5 20230
6 20232
7 20231
8 20231
9 202231
10 202223
11 202210
12 202113
13 20205
14 202011
15 2019124
16 20192
17 20196
18 201841
19 201210
20 200721

About Tadaki Suzuki

Tadaki Suzuki is a scholar working on Infectious Diseases, Immunology and Epidemiology, having authored 224 papers that have together received 6.3k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (61 papers), COVID-19 Clinical Research Studies (49 papers), Influenza Virus Research Studies (34 papers), Polyomavirus and related diseases (30 papers), Viral Infections and Vectors (29 papers), Respiratory viral infections research (27 papers), SARS-CoV-2 detection and testing (26 papers) and Viral Infections and Outbreaks Research (19 papers). The work is most often cited by research in Infectious Diseases (3.3k citations), Immunology (1.3k citations) and Epidemiology (1.5k citations). Tadaki Suzuki has collaborated with scholars based in Japan, United States and Mongolia. Frequent co-authors include Hideki Hasegawa, Hirofumi Sawa, Akira Ainai, Noriyo Nagata, Yasuko Orba, Makoto Takeda, Kenichi Niikura, Makoto Kuroda, Yuko Sato and Tsuyoshi Sekizuka. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

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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