Pei‐Yu Wang
- Molecular Biology
- Genetics top 10%
- Public Health, Environmental and Occupational Health top 10%
- Physiology top 10%
- Cellular and Molecular Neuroscience top 10%
- Co-authors
- Akio SatoLi‐Qiang QinTakashi KanekoIan S. McLennanKyoko KoishiJui‐Hung YenHui-Chun YangWei‐Sheng Lin
- Topics
- Genetics, Aging, and Longevity in Model Organisms (12 papers)Neurobiology and Insect Physiology Research (11 papers)Phytoestrogen effects and research (6 papers)
- Partner nations
- ChinaTaiwanUnited States
In The Last Decade
Pei‐Yu Wang
110 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 151
- Molecular Biology 676
- Genetics 242
- Public Health, Environmental and Occupational Health 196
- Physiology 196
- Cellular and Molecular Neuroscience 186
Countries citing papers authored by Pei‐Yu Wang
This map shows the geographic impact of Pei‐Yu Wang'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 Pei‐Yu Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pei‐Yu Wang more than expected).
Fields of papers citing papers by Pei‐Yu Wang
This network shows the impact of papers produced by Pei‐Yu Wang. 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 Pei‐Yu Wang. The network helps show where Pei‐Yu Wang may publish in the future.
Co-authorship network of co-authors of Pei‐Yu Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Pei‐Yu Wang. A scholar is included among the top collaborators of Pei‐Yu Wang 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 Pei‐Yu Wang. Pei‐Yu Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 8 | |
| 5 | 7 | |
| 6 | 5 | |
| 7 | 6 | |
| 8 | 8 | |
| 9 | 9 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | 14 | |
| 13 | 7 | |
| 14 | Tequila Regulates Insulin-Like Signaling and Extends Life Span in Drosophila melanogaster | 1 |
| 15 | [Postpartum weight retention in Beijing, Suzhou and Guangzhou women and its associated factors]. | 2 |
| 16 | 1 | |
| 17 | 14 | |
| 18 | The Analysis and Design of Educational Recommender Systems | 3 |
| 19 | 21 | |
| 20 | 79 |
About Pei‐Yu Wang
Pei‐Yu Wang is a scholar working on Aging, Sensory Systems and Complementary and alternative medicine, having authored 117 papers that have together received 1.9k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (12 papers), Neurobiology and Insect Physiology Research (11 papers) and Phytoestrogen effects and research (6 papers). The work is most often cited by research in Aging (160 citations), Reproductive Medicine (154 citations) and Biological Psychiatry (26 citations). Pei‐Yu Wang has collaborated with scholars based in China, Taiwan and United States. Frequent co-authors include Akio Sato, Li‐Qiang Qin, Takashi Kaneko, Ian S. McLennan, Kyoko Koishi, Jui‐Hung Yen, Hui-Chun Yang, Wei‐Sheng Lin, Davaasambuu Ganmaa and Kazuhiko Hoshi. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications 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.