Pu Han
Impact in
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- 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 4
- SARS-CoV-2 detection and testing 2
-
- Protein Structure and Dynamics 2
- Co-authors
- George F. Gao (11 shared papers)Jianxun Qi (11 shared papers)Xin Zhao (6 shared papers)Kefang Liu (7 shared papers)Zepeng Xu (6 shared papers)Qihui Wang (8 shared papers)Anqi Zheng (5 shared papers)Linjie Li (3 shared papers)
In The Last Decade
Pu Han
23 papers receiving 171 citations
Peers
Comparison fields: 5 of 44
- Infectious Diseases 136
- Animal Science and Zoology 59
- Immunology 19
- Modeling and Simulation 4
- Genetics 20
Countries citing papers authored by Pu Han
This map shows the geographic impact of Pu Han'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 Pu Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pu Han more than expected).
Fields of papers citing papers by Pu Han
This network shows the impact of papers produced by Pu Han. 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 Pu Han. The network helps show where Pu Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Pu Han, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 38 | |
| 2 | 2022 | 19 | |
| 3 | 2022 | 13 | |
| 4 | 2022 | 13 | |
| 5 | 2022 | 13 | |
| 6 | The protein X4 of severe acute respiratory syndrome-associated coronavirus is expressed on both virus-infected cells and lung tissue of severe acute respiratory syndrome patients and inhibits growth of Balb/c 3T3 cell line. | 2005 | 13 |
| 7 | 2019 | 9 | |
| 8 | 2024 | 7 | |
| 9 | 2023 | 7 | |
| 10 | 2023 | 7 | |
| 11 | 2023 | 5 | |
| 12 | 2022 | 5 | |
| 13 | 2024 | 3 | |
| 14 | 2021 | 3 | |
| 15 | 2022 | 3 | |
| 16 | 2014 | 3 | |
| 17 | 2024 | 2 | |
| 18 | 2023 | 2 | |
| 19 | 2017 | 2 | |
| 20 | [Adenosine triphosphate-binding gene messenger ribonucleic acid expression in brains of drug-resistant epileptics]. | 2011 | 2 |
About Pu Han
Pu Han is a scholar working on Infectious Diseases, Molecular Biology, Animal Science and Zoology, Genetics and Immunology, having authored 24 papers that have together received 172 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (13 papers), Animal Virus Infections Studies (5 papers), Viral gastroenteritis research and epidemiology (5 papers), COVID-19 Clinical Research Studies (4 papers), Virus-based gene therapy research (3 papers), SARS-CoV-2 detection and testing (2 papers), Protein Structure and Dynamics (2 papers) and Immunotherapy and Immune Responses (2 papers). The work is most often cited by research in Infectious Diseases (136 citations), Animal Science and Zoology (59 citations), Immunology (19 citations), Modeling and Simulation (4 citations) and Genetics (20 citations). Pu Han has collaborated with scholars based in China, Macao and Czechia. Frequent co-authors include George F. Gao, Jianxun Qi, Xin Zhao, Kefang Liu, Zepeng Xu, Qihui Wang, Anqi Zheng, Linjie Li, Bin Bai and Pei Du. Their work appears in journals such as Journal of Virology, Energies, Nature Communications, Cell Reports and Cell Discovery.
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.