Lin Pan
Impact in
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
- Viral gastroenteritis research and epidemiology
- Animal Science and Zoology top 10%
- Animal Virus Infections Studies
Papers in
-
- SARS-CoV-2 and COVID-19 Research 13
- Viral gastroenteritis research and epidemiology 5
- COVID-19 Clinical Research Studies 2
- SARS-CoV-2 detection and testing 2
-
- Animal Virus Infections Studies 6
- Co-authors
- Yusuke Kosugi (2 shared papers)Daichi Yamasoba (1 shared paper)Arnon Plianchaisuk (1 shared paper)Keiya Uriu (1 shared paper)Jiří Zahradník (1 shared paper)Jumpei Ito (1 shared paper)Kei Sato (2 shared papers)Yu Kaku (1 shared paper)
In The Last Decade
Lin Pan
13 papers receiving 477 citations
Lin Pan's Hit Papers
Peers
Comparison fields: 5 of 45
- Infectious Diseases 414
- Animal Science and Zoology 77
- Modeling and Simulation 25
- Radiology, Nuclear Medicine and Imaging 37
- Health 13
Countries citing papers authored by Lin Pan
This map shows the geographic impact of Lin Pan'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 Lin Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lin Pan more than expected).
Fields of papers citing papers by Lin Pan
This network shows the impact of papers produced by Lin Pan. 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 Lin Pan. The network helps show where Lin Pan may publish in the future.
Co-authors
The 11 scholars most cited alongside Lin Pan, 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 | Virological characteristics of the SARS-CoV-2 XBB variant derived from recombination of two Omicron subvariants Hit paper breakdown → | 2023 | 225 |
| 2 | Virological characteristics of the SARS-CoV-2 omicron XBB.1.16 variant Hit paper breakdown → | 2023 | 106 |
| 3 | Virological characteristics of the SARS-CoV-2 Omicron XBB.1.5 variant Hit paper breakdown → | 2024 | 64 |
| 4 | 2024 | 31 | |
| 5 | 2024 | 13 | |
| 6 | 2024 | 11 | |
| 7 | 2023 | 11 | |
| 8 | 2023 | 6 | |
| 9 | 2024 | 5 | |
| 10 | 2023 | 4 | |
| 11 | 2024 | 3 | |
| 12 | 2025 | 2 | |
| 13 | 2025 | 1 | |
| 14 | 2026 | 0 |
About Lin Pan
Lin Pan is a scholar working on Infectious Diseases, Animal Science and Zoology, Modeling and Simulation, Pathology and Forensic Medicine and Cardiology and Cardiovascular Medicine, having authored 14 papers that have together received 482 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (13 papers), Animal Virus Infections Studies (6 papers), Viral gastroenteritis research and epidemiology (5 papers), COVID-19 Clinical Research Studies (2 papers), SARS-CoV-2 detection and testing (2 papers), Bacillus and Francisella bacterial research (2 papers), Multiple Sclerosis Research Studies (1 paper) and COVID-19 epidemiological studies (1 paper). The work is most often cited by research in Infectious Diseases (414 citations), Animal Science and Zoology (77 citations), Modeling and Simulation (25 citations), Radiology, Nuclear Medicine and Imaging (37 citations) and Health (13 citations). Lin Pan has collaborated with scholars based in Japan, Czechia and Tanzania. Frequent co-authors include Yusuke Kosugi, Daichi Yamasoba, Arnon Plianchaisuk, Keiya Uriu, Jiří Zahradník, Jumpei Ito, Kei Sato, Yu Kaku, Jarel Elgin Tolentino and Jiajie Yu. Their work appears in journals such as Nature Communications, Journal of Virology, mBio, The Lancet Infectious Diseases and The Lancet Microbe.
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.