Long Dai
Impact in
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- Natural Compounds in Disease Treatment
- Traditional Chinese Medicine Analysis
- Pharmacology top 10%
- Drug-Induced Hepatotoxicity and Protection
Papers in
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- Metabolomics and Mass Spectrometry Studies 8
- Natural product bioactivities and synthesis 7
- Protein Hydrolysis and Bioactive Peptides 4
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- Traditional Chinese Medicine Analysis 8
- Co-authors
- Shaoping Wang (24 shared papers)Jing Song (2 shared papers)Shengguang Wang (4 shared papers)Guannan He (1 shared paper)Peng Fei Gao (3 shared papers)Shiming Zhang (1 shared paper)Yanan Li (14 shared papers)Zedong Xiang (4 shared papers)
In The Last Decade
Long Dai
50 papers receiving 707 citations
Long Dai's Hit Papers
Peers
Comparison fields: 5 of 112
- Complementary and alternative medicine 101
- Pharmacology 68
- Biochemistry 35
- Molecular Biology 322
- Pathology and Forensic Medicine 77
Countries citing papers authored by Long Dai
This map shows the geographic impact of Long 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 Long Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Long Dai more than expected).
Fields of papers citing papers by Long Dai
This network shows the impact of papers produced by Long 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 Long Dai. The network helps show where Long Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Long 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 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 145 | |
| 2 | A comprehensive review on celastrol, triptolide and triptonide: Insights on their pharmacological activity, toxicity, combination therapy, new dosage form and novel drug delivery routes Hit paper breakdown → | 2023 | 96 |
| 3 | 2022 | 66 | |
| 4 | 2022 | 45 | |
| 5 | 2016 | 23 | |
| 6 | 2013 | 22 | |
| 7 | 2021 | 21 | |
| 8 | 2022 | 18 | |
| 9 | 2022 | 18 | |
| 10 | 2019 | 16 | |
| 11 | 2021 | 16 | |
| 12 | 2022 | 15 | |
| 13 | 1994 | 15 | |
| 14 | 2023 | 14 | |
| 15 | 2019 | 11 | |
| 16 | 2022 | 10 | |
| 17 | 2023 | 10 | |
| 18 | 2019 | 10 | |
| 19 | 2023 | 10 | |
| 20 | 2021 | 9 |
About Long Dai
Long Dai is a scholar working on Molecular Biology, Complementary and alternative medicine, Plant Science, Pharmacology and Analytical Chemistry, having authored 53 papers that have together received 716 indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (8 papers), Traditional Chinese Medicine Analysis (8 papers), Natural product bioactivities and synthesis (7 papers), Chromatography in Natural Products (5 papers), Phytochemistry and Biological Activities (4 papers), Protein Hydrolysis and Bioactive Peptides (4 papers), Insect Utilization and Effects (3 papers) and Internet Traffic Analysis and Secure E-voting (3 papers). The work is most often cited by research in Complementary and alternative medicine (101 citations), Pharmacology (68 citations), Biochemistry (35 citations), Molecular Biology (322 citations) and Pathology and Forensic Medicine (77 citations). Long Dai has collaborated with scholars based in China, Macao and Canada. Frequent co-authors include Shaoping Wang, Jing Song, Shengguang Wang, Guannan He, Peng Fei Gao, Shiming Zhang, Yanan Li, Zedong Xiang, Jiayu Zhang and Gary A. Quamme. Their work appears in journals such as Molecules, Current Drug Metabolism, Frontiers in Pharmacology, Arabian Journal of Chemistry and Biomedicine & Pharmacotherapy.
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.