Ying Ye
Impact in
- Animal Science and Zoology top 5%
- Animal Virus Infections Studies
- Microbiology top 10%
- Antimicrobial Peptides and Activities
Papers in
-
- Immunotherapy and Immune Responses 2
- Virology 2
- HIV Research and Treatment 2
- Co-authors
- Hsing-Jien Kung (1 shared paper)Lucy F. Lee (1 shared paper)Juinn-Lin Liu (1 shared paper)David Camerini (2 shared papers)Yathi M. Naidu (1 shared paper)Noriko N. Yokoyama (1 shared paper)Maira Soto (1 shared paper)Michael E. Selsted (1 shared paper)
- Journals
- Evidence-based Complementary and Alternative Medicine (2 papers)Retrovirology (1 paper)Infection and Drug Resistance (1 paper)BMC Infectious Diseases (1 paper)BMC Ophthalmology (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Ying Ye
17 papers receiving 443 citations
Peers
Comparison fields: 5 of 56
- Animal Science and Zoology 88
- Microbiology 57
- Virology 34
- Oncology 74
- Complementary and alternative medicine 28
Countries citing papers authored by Ying Ye
This map shows the geographic impact of Ying 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 Ying Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Ye more than expected).
Fields of papers citing papers by Ying Ye
This network shows the impact of papers produced by Ying 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 Ying Ye. The network helps show where Ying Ye may publish in the future.
Co-authors
The 25 scholars most cited alongside Ying 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
| # | Work | ||
|---|---|---|---|
| 1 | 1998 | 108 | |
| 2 | 2010 | 75 | |
| 3 | 2018 | 50 | |
| 4 | 2005 | 49 | |
| 5 | 1998 | 35 | |
| 6 | 2020 | 33 | |
| 7 | 2022 | 20 | |
| 8 | 2020 | 16 | |
| 9 | 2016 | 12 | |
| 10 | 2012 | 11 | |
| 11 | 2023 | 10 | |
| 12 | 1999 | 9 | |
| 13 | 2017 | 8 | |
| 14 | 2022 | 5 | |
| 15 | 2025 | 5 | |
| 16 | 2021 | 4 | |
| 17 | 2023 | 3 |
About Ying Ye
Ying Ye is a scholar working on Immunology, Virology, Microbiology, Oncology and Epidemiology, having authored 17 papers that have together received 453 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (2 papers), HIV Research and Treatment (2 papers), Hepatitis B Virus Studies (2 papers), Immunotherapy and Immune Responses (2 papers), Cancer, Hypoxia, and Metabolism (1 paper), Antimicrobial Peptides and Activities (1 paper), Phytochemistry and Biological Activities (1 paper) and Cancer therapeutics and mechanisms (1 paper). The work is most often cited by research in Animal Science and Zoology (88 citations), Microbiology (57 citations), Virology (34 citations), Oncology (74 citations) and Complementary and alternative medicine (28 citations). Ying Ye has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Hsing-Jien Kung, Lucy F. Lee, Juinn-Lin Liu, David Camerini, Yathi M. Naidu, Noriko N. Yokoyama, Maira Soto, Michael E. Selsted, Juhua Zhuang and Jing Ni. Their work appears in journals such as Evidence-based Complementary and Alternative Medicine, Retrovirology, Infection and Drug Resistance, BMC Infectious Diseases and BMC Ophthalmology.
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.