Kai S. Yang
Impact in
- Immunology top 5%
- interferon and immune responses
- Immune Response and Inflammation
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
Papers in
-
- SARS-CoV-2 and COVID-19 Research 11
- COVID-19 Clinical Research Studies 3
-
- Heat shock proteins research 4
- Co-authors
- Chen Wang (8 shared papers)Shiqing Xu (15 shared papers)Wenshe Ray Liu (15 shared papers)Bianhong Zhang (6 shared papers)Shaogang Sun (6 shared papers)Yujie Tang (4 shared papers)Bo Wei (1 shared paper)Xing Liu (1 shared paper)
- Journals
- Journal of Medicinal Chemistry (3 papers)European Journal of Medicinal Chemistry (2 papers)Cell Research (1 paper)Environmental Toxicology (1 paper)Physics of Fluids (1 paper)
- Partner nations
- ChinaUnited StatesItaly
In The Last Decade
Kai S. Yang
38 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 102
- Immunology 534
- Infectious Diseases 311
- Computational Theory and Mathematics 198
- Cancer Research 125
- Virology 34
Countries citing papers authored by Kai S. Yang
This map shows the geographic impact of Kai S. Yang'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 Kai S. Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai S. Yang more than expected).
Fields of papers citing papers by Kai S. Yang
This network shows the impact of papers produced by Kai S. Yang. 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 Kai S. Yang. The network helps show where Kai S. Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai S. Yang, 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 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 222 | |
| 2 | 2009 | 147 | |
| 3 | 2006 | 85 | |
| 4 | 2021 | 84 | |
| 5 | 2022 | 74 | |
| 6 | 2004 | 62 | |
| 7 | 2009 | 53 | |
| 8 | 2007 | 52 | |
| 9 | 2004 | 48 | |
| 10 | 2019 | 39 | |
| 11 | 2022 | 39 | |
| 12 | 2016 | 37 | |
| 13 | 2005 | 36 | |
| 14 | 2022 | 35 | |
| 15 | 2021 | 33 | |
| 16 | 2021 | 31 | |
| 17 | 2022 | 29 | |
| 18 | 2016 | 28 | |
| 19 | 2014 | 23 | |
| 20 | 2016 | 23 |
About Kai S. Yang
Kai S. Yang is a scholar working on Infectious Diseases, Molecular Biology, Computational Theory and Mathematics, Immunology and Epidemiology, having authored 40 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), SARS-CoV-2 and COVID-19 Research (11 papers), interferon and immune responses (4 papers), Heat shock proteins research (4 papers), Endoplasmic Reticulum Stress and Disease (4 papers), NF-κB Signaling Pathways (4 papers), COVID-19 Clinical Research Studies (3 papers) and Immune Response and Inflammation (3 papers). The work is most often cited by research in Immunology (534 citations), Infectious Diseases (311 citations), Computational Theory and Mathematics (198 citations), Cancer Research (125 citations) and Virology (34 citations). Kai S. Yang has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Chen Wang, Shiqing Xu, Wenshe Ray Liu, Bianhong Zhang, Shaogang Sun, Yujie Tang, Bo Wei, Xing Liu, Bo Wei and She Chen. Their work appears in journals such as Journal of Medicinal Chemistry, European Journal of Medicinal Chemistry, Cell Research, Environmental Toxicology and Physics of Fluids.
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.