Cunjin Wu
Impact in
- Infectious Diseases top 5%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in
-
- Influenza Virus Research Studies 3
- Acute Ischemic Stroke Management 1
-
- COVID-19 Clinical Research Studies 2
- SARS-CoV-2 and COVID-19 Research 2
- Co-authors
- Sean X. Leng (4 shared papers)Huifen Li (3 shared papers)Sabra L. Klein (2 shared papers)Yiyin Chen (2 shared papers)Taisheng Li (1 shared paper)Joseph B. Margolick (1 shared paper)Graham Pawelec (1 shared paper)Brian T. Garibaldi (1 shared paper)
- Journals
- Ageing Research Reviews (2 papers)Cell Death Discovery (1 paper)BMC Medicine (1 paper)Hypertension (1 paper)npj Vaccines (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Cunjin Wu
16 papers receiving 745 citations
Cunjin Wu's Hit Papers
Peers
Comparison fields: 5 of 112
- Infectious Diseases 332
- Modeling and Simulation 64
- Neurology 181
- Health 69
- Aging 11
Countries citing papers authored by Cunjin Wu
This map shows the geographic impact of Cunjin Wu'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 Cunjin Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cunjin Wu more than expected).
Fields of papers citing papers by Cunjin Wu
This network shows the impact of papers produced by Cunjin Wu. 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 Cunjin Wu. The network helps show where Cunjin Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Cunjin Wu, 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 | Aging in COVID-19: Vulnerability, immunity and intervention Hit paper breakdown → | 2020 | 608 |
| 2 | 2020 | 29 | |
| 3 | 2014 | 27 | |
| 4 | 2021 | 23 | |
| 5 | 2016 | 15 | |
| 6 | 2020 | 11 | |
| 7 | 2016 | 8 | |
| 8 | 2018 | 6 | |
| 9 | [Impact of adding folic acid, vitamin B(12) and probucol to standard antihypertensive medication on plasma homocysteine and asymmetric dimethylarginine levels of essential hypertension patients]. | 2012 | 6 |
| 10 | 2018 | 6 | |
| 11 | 2022 | 5 | |
| 12 | 2021 | 5 | |
| 13 | 2023 | 5 | |
| 14 | 2021 | 4 | |
| 15 | 2022 | 3 | |
| 16 | 2025 | 2 | |
| 17 | 2025 | 0 |
About Cunjin Wu
Cunjin Wu is a scholar working on Epidemiology, Infectious Diseases, Molecular Biology, Pulmonary and Respiratory Medicine and Physiology, having authored 17 papers that have together received 763 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (3 papers), COVID-19 Clinical Research Studies (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Thyroid Disorders and Treatments (1 paper), Long-Term Effects of COVID-19 (1 paper), Alcohol Consumption and Health Effects (1 paper), Acute Ischemic Stroke Management (1 paper) and Respiratory Support and Mechanisms (1 paper). The work is most often cited by research in Infectious Diseases (332 citations), Modeling and Simulation (64 citations), Neurology (181 citations), Health (69 citations) and Aging (11 citations). Cunjin Wu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Sean X. Leng, Huifen Li, Sabra L. Klein, Yiyin Chen, Taisheng Li, Joseph B. Margolick, Graham Pawelec, Brian T. Garibaldi, Lin Wang and Xiaoshuang Xia. Their work appears in journals such as Ageing Research Reviews, Cell Death Discovery, BMC Medicine, Hypertension and npj Vaccines.
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.