Dan Mi
Impact in
- Infectious Diseases top 0.5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
- Viral gastroenteritis research and epidemiology
- Neurology top 5%
- Long-Term Effects of COVID-19
Papers in
-
- SARS-CoV-2 and COVID-19 Research 4
- COVID-19 Clinical Research Studies 2
- Viral gastroenteritis research and epidemiology 1
- SARS-CoV-2 detection and testing 1
- Viral Infections and Outbreaks Research 1
-
- Animal Virus Infections Studies 2
- Co-authors
- Zhaohui Qian (6 shared papers)Xiuyuan Ou (5 shared papers)Zhixia Mu (5 shared papers)Jianwei Wang (3 shared papers)Yan Liu (3 shared papers)Qi Jin (3 shared papers)Jiaxin Hu (4 shared papers)Zichun Xiang (2 shared papers)
- Journals
- Journal of Virology (2 papers)Nature Communications (2 papers)Science Bulletin (1 paper)Methods in molecular biology (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Dan Mi
6 papers receiving 2.3k citations
Dan Mi's Hit Papers
Peers
Comparison fields: 5 of 127
- Infectious Diseases 1.7k
- Neurology 264
- Physiology 78
- Animal Science and Zoology 173
- Modeling and Simulation 59
Countries citing papers authored by Dan Mi
This map shows the geographic impact of Dan Mi'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 Dan Mi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Mi more than expected).
Fields of papers citing papers by Dan Mi
This network shows the impact of papers produced by Dan Mi. 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 Dan Mi. The network helps show where Dan Mi may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Mi, 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 | Characterization of spike glycoprotein of SARS-CoV-2 on virus entry and its immune cross-reactivity with SARS-CoV Hit paper breakdown → | 2020 | 2252 |
| 2 | 2021 | 28 | |
| 3 | 2021 | 19 | |
| 4 | 2018 | 9 | |
| 5 | 2019 | 6 | |
| 6 | 2022 | 1 |
About Dan Mi
Dan Mi is a scholar working on Infectious Diseases, Animal Science and Zoology, Epidemiology, Genetics and Immunology, having authored 6 papers that have together received 2.3k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (4 papers), COVID-19 Clinical Research Studies (2 papers), Animal Virus Infections Studies (2 papers), Viral gastroenteritis research and epidemiology (1 paper), SARS-CoV-2 detection and testing (1 paper), Hepatitis B Virus Studies (1 paper), Hepatitis C virus research (1 paper) and Viral Infections and Outbreaks Research (1 paper). The work is most often cited by research in Infectious Diseases (1.7k citations), Neurology (264 citations), Physiology (78 citations), Animal Science and Zoology (173 citations) and Modeling and Simulation (59 citations). Dan Mi has collaborated with scholars based in China and United States. Frequent co-authors include Zhaohui Qian, Xiuyuan Ou, Zhixia Mu, Jianwei Wang, Yan Liu, Qi Jin, Jiaxin Hu, Zichun Xiang, Keping Hu and Lili Ren. Their work appears in journals such as Journal of Virology, Nature Communications, Science Bulletin and Methods in molecular biology.
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.