Changlong He
Impact in
- Aging top 10%
- Genetics, Aging, and Longevity in Model Organisms
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
Papers in
-
- COVID-19 Clinical Research Studies 3
- SARS-CoV-2 and COVID-19 Research 3
- Co-authors
- Jie Hu (2 shared papers)Ailong Huang (3 shared papers)Kai Wang (3 shared papers)Qingzhu Gao (2 shared papers)Ni Tang (3 shared papers)Guiji Zhang (1 shared paper)Jieli Hu (1 shared paper)Haijun Deng (2 shared papers)
- Journals
- Clinical Infectious Diseases (1 paper)iScience (1 paper)Scientific Reports (1 paper)RSC Advances (1 paper)Expert Systems with Applications (1 paper)
- Partner nations
- ChinaMacaoUnited States
In The Last Decade
Changlong He
16 papers receiving 366 citations
Peers
Comparison fields: 5 of 66
- Aging 29
- Infectious Diseases 182
- Neurology 40
- Modeling and Simulation 12
- Complementary and alternative medicine 21
Countries citing papers authored by Changlong He
This map shows the geographic impact of Changlong He'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 Changlong He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Changlong He more than expected).
Fields of papers citing papers by Changlong He
This network shows the impact of papers produced by Changlong He. 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 Changlong He. The network helps show where Changlong He may publish in the future.
Co-authors
The 25 scholars most cited alongside Changlong He, 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 | 2020 | 130 | |
| 2 | 2020 | 64 | |
| 3 | 2022 | 43 | |
| 4 | 2017 | 23 | |
| 5 | 2021 | 19 | |
| 6 | 2015 | 15 | |
| 7 | 2022 | 13 | |
| 8 | 2022 | 13 | |
| 9 | 2024 | 10 | |
| 10 | 2018 | 10 | |
| 11 | 2023 | 9 | |
| 12 | 2021 | 6 | |
| 13 | 2014 | 5 | |
| 14 | 2022 | 4 | |
| 15 | 2023 | 4 | |
| 16 | 2024 | 1 | |
| 17 | 2024 | 0 | |
| 18 | 2025 | 0 |
About Changlong He
Changlong He is a scholar working on Molecular Biology, Infectious Diseases, Cellular and Molecular Neuroscience, Aging and Radiology, Nuclear Medicine and Imaging, having authored 18 papers that have together received 369 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (3 papers), Genetics, Aging, and Longevity in Model Organisms (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Neuroscience and Neuropharmacology Research (3 papers), Peptidase Inhibition and Analysis (1 paper), Long-Term Effects of COVID-19 (1 paper), MicroRNA in disease regulation (1 paper) and Alzheimer's disease research and treatments (1 paper). The work is most often cited by research in Aging (29 citations), Infectious Diseases (182 citations), Neurology (40 citations), Modeling and Simulation (12 citations) and Complementary and alternative medicine (21 citations). Changlong He has collaborated with scholars based in China, Macao and United States. Frequent co-authors include Jie Hu, Ailong Huang, Kai Wang, Qingzhu Gao, Ni Tang, Guiji Zhang, Jieli Hu, Haijun Deng, Luyi Huang and Juan Chen. Their work appears in journals such as Clinical Infectious Diseases, iScience, Scientific Reports, RSC Advances and Expert Systems with Applications.
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.