Run‐Ze Ye
Impact in
- Parasitology top 10%
- Vector-borne infectious diseases
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
Papers in
-
- Viral Infections and Vectors 12
- Viral Infections and Outbreaks Research 4
- SARS-CoV-2 and COVID-19 Research 3
- Parasitology 12
- Vector-borne infectious diseases 12
- Co-authors
- Wu‐Chun Cao (24 shared papers)Na Jia (14 shared papers)Lin Zhao (14 shared papers)Xiao-Ming Cui (13 shared papers)Yuhao Zhou (5 shared papers)Wenqiang Shi (7 shared papers)Chongqi Jia (2 shared papers)Li-Feng Du (5 shared papers)
- Journals
- BMJ Open (2 papers)Emerging Microbes & Infections (2 papers)One Health (1 paper)Infection Genetics and Evolution (1 paper)iScience (1 paper)
- Partner nations
- ChinaBelarusUnited Kingdom
In The Last Decade
Run‐Ze Ye
25 papers receiving 145 citations
Peers
Comparison fields: 5 of 61
- Parasitology 51
- Modeling and Simulation 29
- Infectious Diseases 77
- Ecology, Evolution, Behavior and Systematics 31
- Nephrology 10
Countries citing papers authored by Run‐Ze Ye
This map shows the geographic impact of Run‐Ze Ye'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 Run‐Ze Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Run‐Ze Ye more than expected).
Fields of papers citing papers by Run‐Ze Ye
This network shows the impact of papers produced by Run‐Ze Ye. 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 Run‐Ze Ye. The network helps show where Run‐Ze Ye may publish in the future.
Co-authors
The 25 scholars most cited alongside Run‐Ze Ye, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 15 | |
| 2 | 2020 | 14 | |
| 3 | 2020 | 13 | |
| 4 | 2024 | 11 | |
| 5 | 2019 | 11 | |
| 6 | 2018 | 11 | |
| 7 | 2020 | 8 | |
| 8 | 2022 | 7 | |
| 9 | 2024 | 6 | |
| 10 | 2021 | 6 | |
| 11 | 2021 | 6 | |
| 12 | 2024 | 5 | |
| 13 | 2019 | 5 | |
| 14 | 2024 | 5 | |
| 15 | 2023 | 4 | |
| 16 | 2025 | 4 | |
| 17 | 2022 | 4 | |
| 18 | 2024 | 3 | |
| 19 | 2024 | 3 | |
| 20 | 2024 | 2 |
About Run‐Ze Ye
Run‐Ze Ye is a scholar working on Infectious Diseases, Parasitology, Ecology, Evolution, Behavior and Systematics, Modeling and Simulation and Public Health, Environmental and Occupational Health, having authored 28 papers that have together received 150 indexed citations. Recurring topics across this work include Viral Infections and Vectors (12 papers), Vector-borne infectious diseases (12 papers), Vector-Borne Animal Diseases (6 papers), COVID-19 epidemiological studies (6 papers), Viral Infections and Outbreaks Research (4 papers), Insect symbiosis and bacterial influences (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers) and Mosquito-borne diseases and control (3 papers). The work is most often cited by research in Parasitology (51 citations), Modeling and Simulation (29 citations), Infectious Diseases (77 citations), Ecology, Evolution, Behavior and Systematics (31 citations) and Nephrology (10 citations). Run‐Ze Ye has collaborated with scholars based in China, Belarus and United Kingdom. Frequent co-authors include Wu‐Chun Cao, Na Jia, Lin Zhao, Xiao-Ming Cui, Yuhao Zhou, Wenqiang Shi, Chongqi Jia, Li-Feng Du, Jia‐Fu Jiang and Xiaoming Cui. Their work appears in journals such as BMJ Open, Emerging Microbes & Infections, One Health, Infection Genetics and Evolution and iScience.
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.