Taosheng Chen
- Pharmacology top 0.1%
- Pharmacogenetics and Drug Metabolism 59
- Oncology top 2%
- Drug Transport and Resistance Mechanisms 26
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- Hormonal Regulation and Hypertension 36
- Molecular Biology top 5%
- Ubiquitin and proteasome pathways 15
- Protein Degradation and Inhibitors 14
- Physiology top 2%
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- Estrogen and related hormone effects 30
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- Computational Drug Discovery Methods 7
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- Multiple Myeloma Research and Treatments 7
- Co-authors
- Wenwei LinSergio C. ChaiWilliam L. FarrarLihua WangYueming WangPeter OladimejiSu Sien OngJing Wu
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Taosheng Chen
149 papers receiving 4.9k citations
Peers
Comparison fields: 5 of 139
- Pharmacology 1.4k
- Oncology 1.3k
- Endocrinology, Diabetes and Metabolism 803
- Molecular Biology 2.3k
- Physiology 136
Countries citing papers authored by Taosheng Chen
This map shows the geographic impact of Taosheng Chen'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 Taosheng Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Taosheng Chen more than expected).
Fields of papers citing papers by Taosheng Chen
This network shows the impact of papers produced by Taosheng Chen. 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 Taosheng Chen. The network helps show where Taosheng Chen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Taosheng Chen, 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 13 | |
| 4 | 2023 | 9 | |
| 5 | 2023 | 2 | |
| 6 | 2022 | 9 | |
| 7 | 2022 | 8 | |
| 8 | 2021 | 27 | |
| 9 | 2020 | 40 | |
| 10 | 2020 | 27 | |
| 11 | 2020 | 34 | |
| 12 | 2020 | 6 | |
| 13 | 2019 | 59 | |
| 14 | 2017 | 12 | |
| 15 | 2017 | 20 | |
| 16 | 2016 | 38 | |
| 17 | 2006 | 10 | |
| 18 | 2006 | 6 | |
| 19 | 2005 | 3 | |
| 20 | Interleukin 6 activates androgen receptor-mediated gene expression through a signal transducer and activator of transcription 3-dependent pathway in LNCaP prostate cancer cells. | 2000 | 214 |
About Taosheng Chen
Taosheng Chen is a scholar working on Pharmacology, Endocrinology, Diabetes and Metabolism and Oncology, having authored 154 papers that have together received 5.0k indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (59 papers), Hormonal Regulation and Hypertension (36 papers), Estrogen and related hormone effects (30 papers), Drug Transport and Resistance Mechanisms (26 papers), Ubiquitin and proteasome pathways (15 papers), Protein Degradation and Inhibitors (14 papers), Computational Drug Discovery Methods (7 papers) and Multiple Myeloma Research and Treatments (7 papers). The work is most often cited by research in Pharmacology (1.4k citations), Oncology (1.3k citations) and Endocrinology, Diabetes and Metabolism (803 citations). Taosheng Chen has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Wenwei Lin, Sergio C. Chai, William L. Farrar, Lihua Wang, Yueming Wang, Peter Oladimeji, Su Sien Ong, Jing Wu, William C. Wright and Jing Wu. Their work appears in journals such as Science, Cell and Proceedings of the National Academy of Sciences.
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.