Linqiang Pan
Impact in
- Computational Theory and Mathematics top 0.2%
- Cellular Automata and Applications
- Advanced Multi-Objective Optimization Algorithms
- Molecular Biology top 1%
- DNA and Biological Computing
- Advanced biosensing and bioanalysis techniques
Papers in
-
- Cellular Automata and Applications 41
- Advanced Multi-Objective Optimization Algorithms 15
-
- DNA and Biological Computing 151
- Advanced biosensing and bioanalysis techniques 149
- RNA Interference and Gene Delivery 10
- Co-authors
- Xingyi ZhangGheorghe PǎunTao SongMario J. Pérez-JímenezXiangxiang ZengBosheng SongTingfang WuCheng He
In The Last Decade
Linqiang Pan
237 papers receiving 5.7k citations
Hit Papers
Peers
Comparison fields: 5 of 125
- Computational Theory and Mathematics 1.6k
- Molecular Biology 4.4k
- Mechanical Engineering 2.0k
- Artificial Intelligence 960
- Electrical and Electronic Engineering 1.1k
Countries citing papers authored by Linqiang Pan
This map shows the geographic impact of Linqiang Pan'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 Linqiang Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Linqiang Pan more than expected).
Fields of papers citing papers by Linqiang Pan
This network shows the impact of papers produced by Linqiang Pan. 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 Linqiang Pan. The network helps show where Linqiang Pan may publish in the future.
Co-authors
The 25 scholars most cited alongside Linqiang Pan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 2 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 9 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 9 | |
| 9 | 2023 | 2 | |
| 10 | 2022 | 2 | |
| 11 | 2021 | 4 | |
| 12 | 2020 | 14 | |
| 13 | 2019 | 18 | |
| 14 | 2018 | 4 | |
| 15 | 2017 | 81 | |
| 16 | 2016 | 4 | |
| 17 | 2016 | 18 | |
| 18 | 2015 | 22 | |
| 19 | 2014 | 14 | |
| 20 | 2013 | 40 |
About Linqiang Pan
Linqiang Pan is a scholar working on Computational Theory and Mathematics, Molecular Biology, Mechanical Engineering, Discrete Mathematics and Combinatorics and Information Systems and Management, having authored 244 papers that have together received 5.9k indexed citations. Recurring topics across this work include DNA and Biological Computing (151 papers), Advanced biosensing and bioanalysis techniques (149 papers), Modular Robots and Swarm Intelligence (65 papers), Cellular Automata and Applications (41 papers), Advanced Memory and Neural Computing (26 papers), Advanced Multi-Objective Optimization Algorithms (15 papers), Metaheuristic Optimization Algorithms Research (14 papers) and RNA Interference and Gene Delivery (10 papers). The work is most often cited by research in Computational Theory and Mathematics (1.6k citations), Molecular Biology (4.4k citations), Mechanical Engineering (2.0k citations), Artificial Intelligence (960 citations) and Electrical and Electronic Engineering (1.1k citations). Linqiang Pan has collaborated with scholars based in China, Spain and Romania. Frequent co-authors include Xingyi Zhang, Gheorghe Pǎun, Tao Song, Mario J. Pérez-Jímenez, Xiangxiang Zeng, Bosheng Song, Tingfang Wu, Cheng He, Gexiang Zhang and Andrei Păun. Their work appears in journals such as Theoretical Computer Science, IEEE Transactions on NanoBioscience, Information Sciences, Swarm and Evolutionary Computation and Progress in Natural Science Materials 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.