Taiyi Wang
Impact in
-
- Traditional Chinese Medicine Analysis
- Pharmacology top 5%
- Pharmacological Effects of Natural Compounds
- Plant-based Medicinal Research
Papers in
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- Traditional Chinese Medicine Analysis 9
- Co-authors
- Yan Zhu (12 shared papers)Ming Lyu (5 shared papers)Yuling Ma (8 shared papers)P. Segall (7 shared papers)K. R. Anderson (4 shared papers)Han Zhang (2 shared papers)Guangxu Xiao (2 shared papers)Yuan‐Lu Cui (1 shared paper)
- Journals
- Frontiers in Pharmacology (4 papers)Cell & Bioscience (3 papers)Phytomedicine (3 papers)Geophysical Research Letters (3 papers)Scientific Reports (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Taiyi Wang
36 papers receiving 630 citations
Taiyi Wang's Hit Papers
Peers
Comparison fields: 5 of 113
- Complementary and alternative medicine 148
- Pharmacology 121
- Molecular Medicine 58
- Geophysics 86
- Biological Psychiatry 16
Countries citing papers authored by Taiyi Wang
This map shows the geographic impact of Taiyi 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 Taiyi Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Taiyi Wang more than expected).
Fields of papers citing papers by Taiyi Wang
This network shows the impact of papers produced by Taiyi 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 Taiyi Wang. The network helps show where Taiyi Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Taiyi Wang, 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 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Traditional Chinese medicine in COVID-19 Hit paper breakdown → | 2021 | 153 |
| 2 | 2017 | 80 | |
| 3 | 2013 | 68 | |
| 4 | 2015 | 26 | |
| 5 | 2023 | 25 | |
| 6 | 2020 | 24 | |
| 7 | 2017 | 23 | |
| 8 | 2021 | 19 | |
| 9 | 2018 | 17 | |
| 10 | 2017 | 16 | |
| 11 | 2021 | 15 | |
| 12 | 2019 | 13 | |
| 13 | 2021 | 13 | |
| 14 | 2022 | 13 | |
| 15 | 2021 | 12 | |
| 16 | 2023 | 12 | |
| 17 | 2019 | 11 | |
| 18 | 2022 | 10 | |
| 19 | 2023 | 10 | |
| 20 | 2022 | 9 |
About Taiyi Wang
Taiyi Wang is a scholar working on Complementary and alternative medicine, Molecular Biology, Cardiology and Cardiovascular Medicine, Pharmacology and Geophysics, having authored 40 papers that have together received 635 indexed citations. Recurring topics across this work include Traditional Chinese Medicine Analysis (9 papers), earthquake and tectonic studies (8 papers), Cardiac electrophysiology and arrhythmias (7 papers), Geological and Geochemical Analysis (7 papers), High-pressure geophysics and materials (7 papers), Plant-based Medicinal Research (6 papers), Pharmacological Effects of Natural Compounds (5 papers) and Heart Rate Variability and Autonomic Control (4 papers). The work is most often cited by research in Complementary and alternative medicine (148 citations), Pharmacology (121 citations), Molecular Medicine (58 citations), Geophysics (86 citations) and Biological Psychiatry (16 citations). Taiyi Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yan Zhu, Ming Lyu, Yuling Ma, P. Segall, K. R. Anderson, Han Zhang, Guangxu Xiao, Yuan‐Lu Cui, Dong Xu and Guanwei Fan. Their work appears in journals such as Frontiers in Pharmacology, Cell & Bioscience, Phytomedicine, Geophysical Research Letters and Scientific Reports.
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.