Na Yi
Impact in
- Ophthalmology top 2%
- Glaucoma and retinal disorders
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in ⓘ
-
- Intraocular Surgery and Lenses 5
- Glaucoma and retinal disorders 4
- Co-authors
- Li Qin (2 shared papers)Brian C. Gilger (8 shared papers)Qingling Zhang (2 shared papers)Jacklyn H. Salmon (6 shared papers)Kun Mao (1 shared paper)Dongmei Yang (1 shared paper)Kangmoon Seo (8 shared papers)Manbok Jeong (8 shared papers)
- Journals
- Veterinary Ophthalmology (4 papers)Journal of Veterinary Science (4 papers)Diabetes Research and Clinical Practice (3 papers)EXPERIMENTAL ANIMALS (2 papers)Tuberculosis (2 papers)
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Na Yi
88 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 152
- Ophthalmology 209
- Modeling and Simulation 81
- Parasitology 73
- Equine 17
- Immunology 177
Countries citing papers authored by Na Yi
This map shows the geographic impact of Na Yi'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 Na Yi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Na Yi more than expected).
Fields of papers citing papers by Na Yi
This network shows the impact of papers produced by Na Yi. 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 Na Yi. The network helps show where Na Yi may publish in the future.
Co-authors
The 25 scholars most cited alongside Na Yi, 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 93 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 128 | |
| 2 | 2007 | 87 | |
| 3 | 2009 | 77 | |
| 4 | 2018 | 67 | |
| 5 | 2013 | 59 | |
| 6 | 2017 | 51 | |
| 7 | 2008 | 47 | |
| 8 | 2011 | 42 | |
| 9 | 2008 | 41 | |
| 10 | 2020 | 36 | |
| 11 | 2017 | 35 | |
| 12 | 2017 | 32 | |
| 13 | 2013 | 30 | |
| 14 | 2008 | 30 | |
| 15 | 2018 | 30 | |
| 16 | 2022 | 28 | |
| 17 | 2014 | 26 | |
| 18 | 2006 | 24 | |
| 19 | 2018 | 24 | |
| 20 | 2013 | 22 |
About Na Yi
Na Yi is a scholar working on Ophthalmology, Modeling and Simulation, Aging, Small Animals and Nutrition and Dietetics, having authored 93 papers that have together received 1.5k indexed citations. Recurring topics across this work include Nutrition, Health and Food Behavior (8 papers), Mycobacterium research and diagnosis (6 papers), Tuberculosis Research and Epidemiology (5 papers), Corneal Surgery and Treatments (5 papers), Intraocular Surgery and Lenses (5 papers), Mathematical and Theoretical Epidemiology and Ecology Models (5 papers), RNA modifications and cancer (4 papers) and Glaucoma and retinal disorders (4 papers). The work is most often cited by research in Ophthalmology (209 citations), Modeling and Simulation (81 citations), Parasitology (73 citations), Equine (17 citations) and Immunology (177 citations). Na Yi has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Li Qin, Brian C. Gilger, Qingling Zhang, Jacklyn H. Salmon, Kun Mao, Dongmei Yang, Kangmoon Seo, Manbok Jeong, Buka Samten and Yudong Xia. Their work appears in journals such as Veterinary Ophthalmology, Journal of Veterinary Science, Diabetes Research and Clinical Practice, EXPERIMENTAL ANIMALS and Tuberculosis.
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.