Shi Ying
- Molecular Biology top 10%
- Endocrinology, Diabetes and Metabolism top 2%
- Public Health, Environmental and Occupational Health top 5%
- Genetics top 10%
- Reproductive Medicine top 5%
- Co-authors
- Roger GuilleminFrederick EschNaoto UenoN. R. LingShunichi ShimasakiNicholas LingN LingLuc Denoroy
- Topics
- Growth Hormone and Insulin-like Growth Factors (8 papers)TGF-β signaling in diseases (4 papers)Reproductive Biology and Fertility (2 papers)
- Journals
- Proceedings of the National Academy of SciencesThe Annual Review of Pharmacology and ToxicologyExperimental Biology and Medicine
- Partner nations
- United StatesFinlandChina
In The Last Decade
Shi Ying
14 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 82
- Molecular Biology 977
- Endocrinology, Diabetes and Metabolism 505
- Public Health, Environmental and Occupational Health 279
- Genetics 196
- Reproductive Medicine 186
Countries citing papers authored by Shi Ying
This map shows the geographic impact of Shi Ying'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 Shi Ying with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shi Ying more than expected).
Fields of papers citing papers by Shi Ying
This network shows the impact of papers produced by Shi Ying. 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 Shi Ying. The network helps show where Shi Ying may publish in the future.
Co-authorship network of co-authors of Shi Ying
This figure shows the co-authorship network connecting the top 25 collaborators of Shi Ying. A scholar is included among the top collaborators of Shi Ying based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shi Ying. Shi Ying is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | Effects of Endophytic Fungus on Sugar Content and Key Enzymes Activity in Nitrogen and Sugar Metabolism of Sugar Beet (Beta vulgaris L.) | 1 |
| 3 | F99-909 A, an acetylcholinesterase inhibitors from metabolites of microorganisms | 1 |
| 4 | 15 | |
| 5 | 70 | |
| 6 | 4 | |
| 7 | 202 | |
| 8 | 53 | |
| 9 | 355 | |
| 10 | 65 | |
| 11 | 115 | |
| 12 | 18 | |
| 13 | 357 | |
| 14 | 147 | |
| 15 | 129 |
About Shi Ying
Shi Ying is a scholar working on Endocrinology, Diabetes and Metabolism, Behavioral Neuroscience and Pharmaceutical Science, having authored 15 papers that have together received 1.5k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (8 papers), TGF-β signaling in diseases (4 papers) and Reproductive Biology and Fertility (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (505 citations), Reproductive Medicine (186 citations) and Molecular Biology (977 citations). Shi Ying has collaborated with scholars based in United States, Finland and China. Frequent co-authors include Roger Guillemin, Frederick Esch, Naoto Ueno, N. R. Ling, Shunichi Shimasaki, Nicholas Ling, N Ling, Luc Denoroy, Peter Böhlen and Paul Brazeau. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Annual Review of Pharmacology and Toxicology and Experimental Biology and Medicine.
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.