Pu Shi
Impact in
- Molecular Biology top 10%
- Plant biochemistry and biosynthesis
- Plant Gene Expression Analysis
- Plant Reproductive Biology
- Plant tissue culture and regeneration
- Photosynthetic Processes and Mechanisms
- Pharmacology top 5%
- Pharmacological Effects of Natural Compounds
- Microbial Natural Products and Biosynthesis
Papers in
-
- Plant biochemistry and biosynthesis 13
- CRISPR and Genetic Engineering 3
- Plant Reproductive Biology 3
- Co-authors
- Kexuan Tang (14 shared papers)Qian Shen (14 shared papers)Xueqing Fu (14 shared papers)Tingxiang Yan (11 shared papers)Qifang Pan (7 shared papers)Yueli Tang (8 shared papers)Weimin Jiang (9 shared papers)Zongyou Lv (8 shared papers)
In The Last Decade
Pu Shi
27 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 69
- Molecular Biology 949
- Pharmacology 113
- Biotechnology 99
- Plant Science 401
- Pharmacology 136
Countries citing papers authored by Pu Shi
This map shows the geographic impact of Pu 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 Pu Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pu Shi more than expected).
Fields of papers citing papers by Pu Shi
This network shows the impact of papers produced by Pu 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 Pu Shi. The network helps show where Pu Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Pu 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 179 | |
| 2 | 2016 | 168 | |
| 3 | 2018 | 145 | |
| 4 | 2017 | 138 | |
| 5 | 2019 | 67 | |
| 6 | 2017 | 65 | |
| 7 | 2017 | 60 | |
| 8 | 2016 | 55 | |
| 9 | 2016 | 51 | |
| 10 | 2018 | 45 | |
| 11 | 2010 | 39 | |
| 12 | 2017 | 36 | |
| 13 | 2010 | 21 | |
| 14 | 2009 | 20 | |
| 15 | 2018 | 19 | |
| 16 | 2017 | 17 | |
| 17 | 2006 | 16 | |
| 18 | 2016 | 15 | |
| 19 | 2019 | 13 | |
| 20 | 2020 | 10 |
About Pu Shi
Pu Shi is a scholar working on Molecular Biology, Control and Systems Engineering, Pharmacology, Computer Vision and Pattern Recognition and Pharmacology, having authored 27 papers that have together received 1.2k indexed citations. Recurring topics across this work include Plant biochemistry and biosynthesis (13 papers), Robotics and Sensor-Based Localization (4 papers), Robotic Path Planning Algorithms (4 papers), Pharmacological Effects of Natural Compounds (4 papers), Microbial Natural Products and Biosynthesis (3 papers), Transgenic Plants and Applications (3 papers), CRISPR and Genetic Engineering (3 papers) and Plant Reproductive Biology (3 papers). The work is most often cited by research in Molecular Biology (949 citations), Pharmacology (113 citations), Biotechnology (99 citations), Plant Science (401 citations) and Pharmacology (136 citations). Pu Shi has collaborated with scholars based in China, Botswana and Sweden. Frequent co-authors include Kexuan Tang, Qian Shen, Xueqing Fu, Tingxiang Yan, Qifang Pan, Yueli Tang, Weimin Jiang, Zongyou Lv, Xiaofen Sun and Yanan Ma. Their work appears in journals such as Frontiers in Plant Science, New Phytologist, Plant Cell Tissue and Organ Culture (PCTOC), Biotechnology and Applied Biochemistry and BioMed Research International.
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.