Da‐Peng Dai
Impact in
- Pharmacology top 0.5%
- Pharmacogenetics and Drug Metabolism
- Inflammatory mediators and NSAID effects
- Biochemistry top 5%
- Eicosanoids and Hypertension Pharmacology
Papers in
- Pharmacology 49
- Pharmacogenetics and Drug Metabolism 47
- Inflammatory mediators and NSAID effects 6
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- DNA Repair Mechanisms 7
- Co-authors
- Jian‐Ping Cai (28 shared papers)Guoxin Hu (30 shared papers)Shuanghu Wang (35 shared papers)Peiwu Geng (28 shared papers)Jianping Cai (28 shared papers)Samuel H. Wilson (4 shared papers)Julie K. Horton (3 shared papers)Jie Cai (8 shared papers)
- Journals
- Frontiers in Pharmacology (8 papers)Pharmacogenomics (5 papers)Drug Metabolism and Disposition (5 papers)Chemico-Biological Interactions (4 papers)Pharmaceutical Biology (4 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Da‐Peng Dai
85 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 97
- Pharmacology 546
- Biochemistry 97
- Geriatrics and Gerontology 41
- Oncology 219
- Pharmacology 128
Countries citing papers authored by Da‐Peng Dai
This map shows the geographic impact of Da‐Peng Dai'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 Da‐Peng Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da‐Peng Dai more than expected).
Fields of papers citing papers by Da‐Peng Dai
This network shows the impact of papers produced by Da‐Peng Dai. 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 Da‐Peng Dai. The network helps show where Da‐Peng Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Da‐Peng Dai, 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 87 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 67 | |
| 2 | 2014 | 63 | |
| 3 | 2017 | 54 | |
| 4 | 2013 | 53 | |
| 5 | 2013 | 53 | |
| 6 | 2017 | 51 | |
| 7 | 2018 | 40 | |
| 8 | 2020 | 39 | |
| 9 | 2012 | 36 | |
| 10 | 2013 | 34 | |
| 11 | 2011 | 33 | |
| 12 | 2013 | 32 | |
| 13 | 2014 | 30 | |
| 14 | 2016 | 26 | |
| 15 | 2014 | 26 | |
| 16 | 2015 | 25 | |
| 17 | 2014 | 22 | |
| 18 | 2015 | 20 | |
| 19 | 2015 | 19 | |
| 20 | 2015 | 19 |
About Da‐Peng Dai
Da‐Peng Dai is a scholar working on Pharmacology, Molecular Biology, Pharmacology, Oncology and Endocrinology, Diabetes and Metabolism, having authored 87 papers that have together received 1.2k indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (47 papers), DNA Repair Mechanisms (7 papers), Hormonal Regulation and Hypertension (7 papers), Drug Transport and Resistance Mechanisms (7 papers), Hormonal and reproductive studies (6 papers), Eicosanoids and Hypertension Pharmacology (6 papers), Inflammatory mediators and NSAID effects (6 papers) and Computational Drug Discovery Methods (6 papers). The work is most often cited by research in Pharmacology (546 citations), Biochemistry (97 citations), Geriatrics and Gerontology (41 citations), Oncology (219 citations) and Pharmacology (128 citations). Da‐Peng Dai has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Jian‐Ping Cai, Guoxin Hu, Shuanghu Wang, Peiwu Geng, Jianping Cai, Samuel H. Wilson, Julie K. Horton, Jie Cai, Rajendra Prasad and Donna F. Stefanick. Their work appears in journals such as Frontiers in Pharmacology, Pharmacogenomics, Drug Metabolism and Disposition, Chemico-Biological Interactions and Pharmaceutical Biology.
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.