Xiaoyun Ren
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- Viral gastroenteritis research and epidemiology
Papers in
-
- SARS-CoV-2 and COVID-19 Research 4
- Co-authors
- Daniel Kuebler (1 shared paper)Mark A. Tanouye (1 shared paper)Haiguang Zhang (1 shared paper)Richard J. Hall (2 shared papers)Nicole E. Moore (2 shared papers)Jing Wang (2 shared papers)Matthew Peacey (2 shared papers)Q. Sue Huang (2 shared papers)
- Journals
- Emerging infectious diseases (5 papers)Developmental Biology (2 papers)Entomologia Generalis (1 paper)Business Strategy and the Environment (1 paper)PLoS ONE (1 paper)
- Partner nations
- New ZealandChinaUnited States
In The Last Decade
Xiaoyun Ren
33 papers receiving 742 citations
Peers
Comparison fields: 5 of 111
- Modeling and Simulation 69
- Infectious Diseases 161
- Cell Biology 121
- Aging 11
- Cellular and Molecular Neuroscience 111
Countries citing papers authored by Xiaoyun Ren
This map shows the geographic impact of Xiaoyun Ren'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 Xiaoyun Ren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoyun Ren more than expected).
Fields of papers citing papers by Xiaoyun Ren
This network shows the impact of papers produced by Xiaoyun Ren. 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 Xiaoyun Ren. The network helps show where Xiaoyun Ren may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaoyun Ren, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 155 | |
| 2 | 2001 | 70 | |
| 3 | 2010 | 59 | |
| 4 | 2021 | 56 | |
| 5 | 2012 | 52 | |
| 6 | 2015 | 42 | |
| 7 | 2013 | 28 | |
| 8 | 2017 | 27 | |
| 9 | 2006 | 27 | |
| 10 | 2021 | 26 | |
| 11 | 2021 | 25 | |
| 12 | 2021 | 22 | |
| 13 | 2016 | 21 | |
| 14 | 2021 | 20 | |
| 15 | 2022 | 19 | |
| 16 | 2013 | 18 | |
| 17 | 2022 | 15 | |
| 18 | 2017 | 13 | |
| 19 | 2015 | 12 | |
| 20 | 2022 | 10 |
About Xiaoyun Ren
Xiaoyun Ren is a scholar working on Infectious Diseases, Molecular Biology, Microbiology, Ecology and Epidemiology, having authored 36 papers that have together received 754 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (4 papers), Zoonotic diseases and public health (3 papers), Microtubule and mitosis dynamics (3 papers), COVID-19 epidemiological studies (3 papers), Animal Virus Infections Studies (3 papers), Bacterial Infections and Vaccines (3 papers), Bacteriophages and microbial interactions (3 papers) and Pneumonia and Respiratory Infections (2 papers). The work is most often cited by research in Modeling and Simulation (69 citations), Infectious Diseases (161 citations), Cell Biology (121 citations), Aging (11 citations) and Cellular and Molecular Neuroscience (111 citations). Xiaoyun Ren has collaborated with scholars based in New Zealand, China and United States. Frequent co-authors include Daniel Kuebler, Mark A. Tanouye, Haiguang Zhang, Richard J. Hall, Nicole E. Moore, Jing Wang, Matthew Peacey, Q. Sue Huang, Philip E. Carter and Ange Bissielo. Their work appears in journals such as Emerging infectious diseases, Developmental Biology, Entomologia Generalis, Business Strategy and the Environment and PLoS ONE.
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.