Jun Wang
- Infectious Diseases top 0.5%
- SARS-CoV-2 and COVID-19 Research 34
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods 20
- Geriatrics and Gerontology top 0.5%
- Epidemiology top 1%
- Influenza Virus Research Studies 59
- Molecular Biology top 1%
- RNA and protein synthesis mechanisms 36
- Protein Structure and Dynamics 21
- Receptor Mechanisms and Signaling 14
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- Viral Infections and Immunology Research 29
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- Antimicrobial Peptides and Activities 22
- Co-authors
- Chunlong MaYanmei HuWilliam F. DeGradoMei HongMichael T. MartyJulia A. TownsendGiulio Maria PasinettiYu Chen
- Journals
- Journal of Medicinal Chemistry (17 papers)Journal of the American Chemical Society (13 papers)ACS Infectious Diseases (7 papers)
- Partner nations
- United StatesChinaGreece
In The Last Decade
Jun Wang
243 papers receiving 9.8k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Infectious Diseases 2.3k
- Computational Theory and Mathematics 1.7k
- Geriatrics and Gerontology 415
- Epidemiology 2.3k
- Molecular Biology 4.4k
Countries citing papers authored by Jun Wang
This map shows the geographic impact of Jun Wang'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 Jun Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Wang more than expected).
Fields of papers citing papers by Jun Wang
This network shows the impact of papers produced by Jun Wang. 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 Jun Wang. The network helps show where Jun Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jun Wang, 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 | 1 | |
| 3 | 2025 | 6 | |
| 4 | 2024 | 7 | |
| 5 | 2024 | 12 | |
| 6 | Design of a SARS-CoV-2 papain-like protease inhibitor with antiviral efficacy in a mouse modelbreakdown → | 2024 | 43 |
| 7 | 2023 | 1 | |
| 8 | 2023 | 7 | |
| 9 | 2023 | 4 | |
| 10 | 2023 | 22 | |
| 11 | 2023 | 17 | |
| 12 | 2023 | 11 | |
| 13 | 2022 | 19 | |
| 14 | 2022 | 19 | |
| 15 | 2020 | 27 | |
| 16 | 2019 | 21 | |
| 17 | 2018 | 83 | |
| 18 | 2017 | 24 | |
| 19 | Citizen's Satisfaction with Public Education Service in China:A Quantitative Analysis via Hierarchical Linear Model | 2011 | 1 |
| 20 | 2005 | 88 |
About Jun Wang
Jun Wang is a scholar working on Microbiology, Geriatrics and Gerontology and Infectious Diseases, having authored 257 papers that have together received 9.9k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (59 papers), RNA and protein synthesis mechanisms (36 papers), SARS-CoV-2 and COVID-19 Research (34 papers), Viral Infections and Immunology Research (29 papers), Antimicrobial Peptides and Activities (22 papers), Protein Structure and Dynamics (21 papers), Computational Drug Discovery Methods (20 papers) and Receptor Mechanisms and Signaling (14 papers). The work is most often cited by research in Infectious Diseases (2.3k citations), Computational Theory and Mathematics (1.7k citations) and Geriatrics and Gerontology (415 citations). Jun Wang has collaborated with scholars based in United States, China and Greece. Frequent co-authors include Chunlong Ma, Yanmei Hu, William F. DeGrado, Mei Hong, Michael T. Marty, Julia A. Townsend, Giulio Maria Pasinetti, Yu Chen, Sarah D. Cady and Cinque Soto. Their work appears in journals such as Journal of Medicinal Chemistry, Journal of the American Chemical Society, ACS Infectious Diseases, Nature Communications and Antiviral Research.
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.