Shaofei Chen
Impact in
- Hepatology top 10%
- Hepatocellular Carcinoma Treatment and Prognosis
- Pharmacology top 10%
- Microbial Natural Products and Biosynthesis
- Fungal Biology and Applications
Papers in
-
- Phytochemical Studies and Bioactivities 5
-
- Reinforcement Learning in Robotics 7
- Artificial Intelligence in Games 5
- Co-authors
- Jing Chen (14 shared papers)Lincheng Shen (8 shared papers)Libo Zhao (1 shared paper)Jialing Wang (1 shared paper)Xiaomin Wang (1 shared paper)Haifeng Wang (14 shared papers)Yue‐Hu Pei (14 shared papers)Gang Chen (14 shared papers)
- Journals
- Journal of Asian Natural Products Research (7 papers)Electronics (4 papers)Physical review. C (3 papers)RSC Advances (2 papers)Chinese Journal of Natural Medicines (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Shaofei Chen
63 papers receiving 754 citations
Peers
Comparison fields: 5 of 126
- Hepatology 65
- Pharmacology 126
- Pharmacology 45
- Cancer Research 68
- Biotechnology 35
Countries citing papers authored by Shaofei Chen
This map shows the geographic impact of Shaofei 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 Shaofei Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaofei Chen more than expected).
Fields of papers citing papers by Shaofei Chen
This network shows the impact of papers produced by Shaofei 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 Shaofei Chen. The network helps show where Shaofei Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Shaofei 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
Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 103 | |
| 2 | 2018 | 67 | |
| 3 | 2010 | 49 | |
| 4 | 2016 | 41 | |
| 5 | 2010 | 36 | |
| 6 | 2017 | 32 | |
| 7 | 2015 | 31 | |
| 8 | 2020 | 24 | |
| 9 | 2013 | 20 | |
| 10 | 2018 | 18 | |
| 11 | 2013 | 18 | |
| 12 | 2016 | 18 | |
| 13 | 2016 | 17 | |
| 14 | 2020 | 17 | |
| 15 | 2017 | 15 | |
| 16 | 2016 | 15 | |
| 17 | 2024 | 14 | |
| 18 | 2015 | 14 | |
| 19 | 2016 | 14 | |
| 20 | 2017 | 14 |
About Shaofei Chen
Shaofei Chen is a scholar working on Molecular Biology, Artificial Intelligence, Pharmacology, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 67 papers that have together received 769 indexed citations. Recurring topics across this work include Microbial Natural Products and Biosynthesis (10 papers), Fungal Biology and Applications (8 papers), Phytochemistry and Bioactive Compounds (7 papers), Reinforcement Learning in Robotics (7 papers), Robotic Path Planning Algorithms (6 papers), Distributed Control Multi-Agent Systems (5 papers), Phytochemical Studies and Bioactivities (5 papers) and Artificial Intelligence in Games (5 papers). The work is most often cited by research in Hepatology (65 citations), Pharmacology (126 citations), Pharmacology (45 citations), Cancer Research (68 citations) and Biotechnology (35 citations). Shaofei Chen has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Jing Chen, Lincheng Shen, Libo Zhao, Jialing Wang, Xiaomin Wang, Haifeng Wang, Yue‐Hu Pei, Gang Chen, Chidan Wan and Ping Fan. Their work appears in journals such as Journal of Asian Natural Products Research, Electronics, Physical review. C, RSC Advances and Chinese Journal of Natural Medicines.
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.