Wang Qu
Impact in
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Viral gastroenteritis research and epidemiology
-
- Computational Drug Discovery Methods
Papers in
-
- SARS-CoV-2 and COVID-19 Research 5
- COVID-19 Clinical Research Studies 3
- Viral gastroenteritis research and epidemiology 2
-
- Long-Term Effects of COVID-19 2
- Co-authors
- Kaifeng Liu (1 shared paper)Xiaohua Liu (1 shared paper)Liao Cui (1 shared paper)Ying Li (1 shared paper)Fangfang Huang (1 shared paper)Lianxiang Luo (1 shared paper)Hui Luo (1 shared paper)Xiaohong Li (1 shared paper)
- Journals
- Science (1 paper)动物学研究 (1 paper)Cell Discovery (1 paper)Pharmacological Research (1 paper)Optik (1 paper)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Wang Qu
8 papers receiving 564 citations
Wang Qu's Hit Papers
Peers
Comparison fields: 5 of 76
- Infectious Diseases 306
- Computational Theory and Mathematics 257
- Pharmacology 45
- Complementary and alternative medicine 39
- Organic Chemistry 100
Countries citing papers authored by Wang Qu
This map shows the geographic impact of Wang Qu'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 Wang Qu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wang Qu more than expected).
Fields of papers citing papers by Wang Qu
This network shows the impact of papers produced by Wang Qu. 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 Wang Qu. The network helps show where Wang Qu may publish in the future.
Co-authors
The 25 scholars most cited alongside Wang Qu, 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 | SARS-CoV-2 M pro inhibitors with antiviral activity in a transgenic mouse model Hit paper breakdown → | 2021 | 370 |
| 2 | 2020 | 109 | |
| 3 | 2022 | 54 | |
| 4 | 2022 | 28 | |
| 5 | 2024 | 6 | |
| 6 | 2022 | 5 | |
| 7 | 2022 | 4 | |
| 8 | 2015 | 3 |
About Wang Qu
Wang Qu is a scholar working on Infectious Diseases, Neurology, Complementary and alternative medicine, Media Technology and Animal Science and Zoology, having authored 8 papers that have together received 579 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (5 papers), COVID-19 Clinical Research Studies (3 papers), Viral gastroenteritis research and epidemiology (2 papers), Long-Term Effects of COVID-19 (2 papers), Computational Drug Discovery Methods (1 paper), Alzheimer's disease research and treatments (1 paper), Image and Signal Denoising Methods (1 paper) and Animal Virus Infections Studies (1 paper). The work is most often cited by research in Infectious Diseases (306 citations), Computational Theory and Mathematics (257 citations), Pharmacology (45 citations), Complementary and alternative medicine (39 citations) and Organic Chemistry (100 citations). Wang Qu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Kaifeng Liu, Xiaohua Liu, Liao Cui, Ying Li, Fangfang Huang, Lianxiang Luo, Hui Luo, Xiaohong Li, Jian-Bao Han and Xiaochun Xie. Their work appears in journals such as Science, 动物学研究, Cell Discovery, Pharmacological Research and Optik.
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.