Peng Chen
- Molecular Biology top 10%
- Plant Science top 2%
- Computational Theory and Mathematics top 1%
- Computer Vision and Pattern Recognition top 2%
- Materials Chemistry top 10%
- Co-authors
- Bing WangJun ZhangJianhua ZhangStefano NicheleZhong YinChengjun XieJinyan LiWenyan Wang
- Topics
- Protein Structure and Dynamics (36 papers)Machine Learning in Bioinformatics (30 papers)Computational Drug Discovery Methods (26 papers)
- Cited by
- Computational Theory and MathematicsAnalytical ChemistryExperimental and Cognitive Psychology
- Journals
- Nucleic Acids ResearchJournal of Biological ChemistrySHILAP Revista de lepidopterología
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Peng Chen
193 papers receiving 3.9k citations
Hit Papers
Peers
Comparison fields: 5 of 183
- Molecular Biology 1.1k
- Plant Science 919
- Computational Theory and Mathematics 505
- Computer Vision and Pattern Recognition 390
- Materials Chemistry 361
Countries citing papers authored by Peng Chen
This map shows the geographic impact of Peng 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 Peng Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peng Chen more than expected).
Fields of papers citing papers by Peng Chen
This network shows the impact of papers produced by Peng 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 Peng Chen. The network helps show where Peng Chen may publish in the future.
Co-authorship network of co-authors of Peng Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Peng Chen. A scholar is included among the top collaborators of Peng Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peng Chen. Peng Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | Fe–Mn bimetallic catalyst to activate peroxymonosulfate (PMS) for efficient degradation of tetracycline: Mechanism insights and application for pharmaceutical wastewaterbreakdown → | 125 |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 3 | |
| 9 | 14 | |
| 10 | 42 | |
| 11 | 32 | |
| 12 | 11 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 1 | |
| 17 | 0 | |
| 18 | 3 | |
| 19 | 4 | |
| 20 | 22 |
About Peng Chen
Peng Chen is a scholar working on Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Analytical Chemistry, having authored 210 papers that have together received 4.0k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (36 papers), Machine Learning in Bioinformatics (30 papers) and Computational Drug Discovery Methods (26 papers). The work is most often cited by research in Computational Theory and Mathematics (505 citations), Analytical Chemistry (292 citations) and Experimental and Cognitive Psychology (349 citations). Peng Chen has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Bing Wang, Jun Zhang, Jianhua Zhang, Stefano Nichele, Zhong Yin, Chengjun Xie, Jinyan Li, Wenyan Wang, Jie Zhang and Rui Li. Their work appears in journals such as Nucleic Acids Research, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.
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.