Shingo Iwami
- Modeling and Simulation top 0.2%
- COVID-19 epidemiological studies 25
- Virology top 1%
- HIV Research and Treatment 38
- Infectious Diseases top 2%
- SARS-CoV-2 and COVID-19 Research 22
- HIV/AIDS Research and Interventions 15
- SARS-CoV-2 detection and testing 12
- Hepatology top 2%
- Hepatitis C virus research 16
-
- Mathematical and Theoretical Epidemiology and Ecology Models 23
-
- Immune Cell Function and Interaction 12
- Co-authors
- Yasuhiro TakeuchiXianning LiuShinji NakaokaKei SatoKazuyuki AiharaYoshiki KoizumiTomoyuki MiuraYoshio Koyanagi
- Journals
- Journal of Theoretical Biology (19 papers)Scientific Reports (6 papers)PLoS Computational Biology (5 papers)
- Partner nations
- JapanUnited StatesSouth Korea
In The Last Decade
Shingo Iwami
100 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 127
- Modeling and Simulation 836
- Virology 585
- Infectious Diseases 873
- Hepatology 295
- Public Health, Environmental and Occupational Health 826
Countries citing papers authored by Shingo Iwami
This map shows the geographic impact of Shingo Iwami'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 Shingo Iwami with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shingo Iwami more than expected).
Fields of papers citing papers by Shingo Iwami
This network shows the impact of papers produced by Shingo Iwami. 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 Shingo Iwami. The network helps show where Shingo Iwami may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shingo Iwami, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 7 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 7 | |
| 8 | 2023 | 6 | |
| 9 | 2023 | 2 | |
| 10 | 2022 | 2 | |
| 11 | 2022 | 57 | |
| 12 | 2022 | 19 | |
| 13 | 2021 | 22 | |
| 14 | 2021 | 32 | |
| 15 | 2021 | 39 | |
| 16 | 2021 | 16 | |
| 17 | 2020 | 1 | |
| 18 | 2020 | 2 | |
| 19 | 2020 | 10 | |
| 20 | 2017 | 30 |
About Shingo Iwami
Shingo Iwami is a scholar working on Virology, Modeling and Simulation, Infectious Diseases, Hepatology and Epidemiology, having authored 109 papers that have together received 2.7k indexed citations. Recurring topics across this work include HIV Research and Treatment (38 papers), COVID-19 epidemiological studies (25 papers), Mathematical and Theoretical Epidemiology and Ecology Models (23 papers), SARS-CoV-2 and COVID-19 Research (22 papers), Hepatitis C virus research (16 papers), HIV/AIDS Research and Interventions (15 papers), Immune Cell Function and Interaction (12 papers) and SARS-CoV-2 detection and testing (12 papers). The work is most often cited by research in Modeling and Simulation (836 citations), Virology (585 citations), Infectious Diseases (873 citations), Hepatology (295 citations) and Public Health, Environmental and Occupational Health (826 citations). Shingo Iwami has collaborated with scholars based in Japan, United States and South Korea. Frequent co-authors include Yasuhiro Takeuchi, Xianning Liu, Shinji Nakaoka, Kei Sato, Kazuyuki Aihara, Yoshiki Koizumi, Tomoyuki Miura, Yoshio Koyanagi, Koichi Watashi and Naoko Misawa. Their work appears in journals such as Journal of Theoretical Biology, Scientific Reports, PLoS Computational Biology, Nature Communications and Proceedings of the National Academy of Sciences.
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.