Danfeng Shi
Impact in
- Toxicology top 5%
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- Computational Drug Discovery Methods
Papers in
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- Receptor Mechanisms and Signaling 6
- Redox biology and oxidative stress 6
- Protein Structure and Dynamics 5
- Natural product bioactivities and synthesis 5
- Biochemical and Molecular Research 4
- Glycosylation and Glycoproteins Research 3
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- Phytochemistry and Biological Activities 4
- Co-authors
- Xiaojun Yao (28 shared papers)Huanxiang Liu (15 shared papers)Shuangyan Zhou (8 shared papers)Xue‐Wei Liu (6 shared papers)Hongli Liu (1 shared paper)Qifeng Bai (9 shared papers)Jianguo Fang (7 shared papers)Junmin Zhang (5 shared papers)
In The Last Decade
Danfeng Shi
55 papers receiving 1.3k citations
Danfeng Shi's Hit Papers
Peers
Comparison fields: 5 of 105
- Toxicology 43
- Computational Theory and Mathematics 209
- Molecular Biology 728
- Geriatrics and Gerontology 26
- Pharmacology 67
Countries citing papers authored by Danfeng Shi
This map shows the geographic impact of Danfeng Shi'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 Danfeng Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danfeng Shi more than expected).
Fields of papers citing papers by Danfeng Shi
This network shows the impact of papers produced by Danfeng Shi. 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 Danfeng Shi. The network helps show where Danfeng Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Danfeng Shi, 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Molecular dynamics simulations and novel drug discovery Hit paper breakdown → | 2017 | 371 |
| 2 | 2020 | 63 | |
| 3 | 2019 | 43 | |
| 4 | 2018 | 40 | |
| 5 | 2019 | 40 | |
| 6 | 2021 | 40 | |
| 7 | 2018 | 38 | |
| 8 | 2017 | 34 | |
| 9 | 2014 | 34 | |
| 10 | 2014 | 31 | |
| 11 | 2020 | 31 | |
| 12 | 2017 | 28 | |
| 13 | 2017 | 27 | |
| 14 | 2017 | 25 | |
| 15 | 2015 | 24 | |
| 16 | 2016 | 23 | |
| 17 | 2015 | 23 | |
| 18 | 2022 | 23 | |
| 19 | 2018 | 22 | |
| 20 | 2014 | 22 |
About Danfeng Shi
Danfeng Shi is a scholar working on Molecular Biology, Plant Science, Organic Chemistry, Oncology and Pharmacology, having authored 56 papers that have together received 1.3k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (6 papers), Redox biology and oxidative stress (6 papers), Protein Structure and Dynamics (5 papers), Natural product bioactivities and synthesis (5 papers), Phytochemistry and Biological Activities (4 papers), Biochemical and Molecular Research (4 papers), Pharmacological Effects of Natural Compounds (4 papers) and Glycosylation and Glycoproteins Research (3 papers). The work is most often cited by research in Toxicology (43 citations), Computational Theory and Mathematics (209 citations), Molecular Biology (728 citations), Geriatrics and Gerontology (26 citations) and Pharmacology (67 citations). Danfeng Shi has collaborated with scholars based in China, Macao and Japan. Frequent co-authors include Xiaojun Yao, Huanxiang Liu, Shuangyan Zhou, Xue‐Wei Liu, Hongli Liu, Qifeng Bai, Jianguo Fang, Junmin Zhang, Xin‐Sheng Yao and Ruijuan Liu. Their work appears in journals such as Fitoterapia, PLoS ONE, International Journal of Biological Macromolecules, Biomedical Chromatography and Journal of Medicinal Chemistry.
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.