Luonan Chen
- Aging top 0.5%
- Molecular Biology top 0.5%
- Bioinformatics and Genomic Networks 194
- Gene Regulatory Network Analysis 142
- Gene expression and cancer classification 69
- Single-cell and spatial transcriptomics 41
- Microbial Metabolic Engineering and Bioproduction 30
- Machine Learning in Bioinformatics 29
- Protein Structure and Dynamics 28
- Statistical and Nonlinear Physics top 0.2%
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods 58
- Cancer Research top 1%
- Co-authors
- Kazuyuki AiharaRui LiuXiang‐Sun ZhangXing‐Ming ZhaoTao ZengXiaoping LiuZhi‐Ping LiuMeiyi Li
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Luonan Chen
489 papers receiving 14.9k citations
Hit Papers
Peers
Comparison fields: 5 of 204
- Aging 322
- Molecular Biology 9.6k
- Statistical and Nonlinear Physics 1.6k
- Computational Theory and Mathematics 1.5k
- Cancer Research 1.3k
Countries citing papers authored by Luonan Chen
This map shows the geographic impact of Luonan 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 Luonan Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luonan Chen more than expected).
Fields of papers citing papers by Luonan Chen
This network shows the impact of papers produced by Luonan 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 Luonan Chen. The network helps show where Luonan Chen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Luonan 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
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 5 | |
| 4 | 2023 | 3 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 5 | |
| 7 | 2023 | 14 | |
| 8 | 2023 | 1 | |
| 9 | 2022 | 11 | |
| 10 | 2022 | 8 | |
| 11 | 2022 | 11 | |
| 12 | 2022 | 89 | |
| 13 | 2021 | 7 | |
| 14 | 2020 | 71 | |
| 15 | 2020 | 11 | |
| 16 | 2019 | 25 | |
| 17 | 2016 | 165 | |
| 18 | 2014 | 12 | |
| 19 | 2014 | 47 | |
| 20 | 2012 | 88 |
About Luonan Chen
Luonan Chen is a scholar working on Aging, Molecular Biology and Computational Theory and Mathematics, having authored 507 papers that have together received 15.3k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (194 papers), Gene Regulatory Network Analysis (142 papers), Gene expression and cancer classification (69 papers), Computational Drug Discovery Methods (58 papers), Single-cell and spatial transcriptomics (41 papers), Microbial Metabolic Engineering and Bioproduction (30 papers), Machine Learning in Bioinformatics (29 papers) and Protein Structure and Dynamics (28 papers). The work is most often cited by research in Aging (322 citations), Molecular Biology (9.6k citations) and Statistical and Nonlinear Physics (1.6k citations). Luonan Chen has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Kazuyuki Aihara, Rui Liu, Xiang‐Sun Zhang, Xing‐Ming Zhao, Tao Zeng, Xiaoping Liu, Zhi‐Ping Liu, Meiyi Li, Rui‐Sheng Wang and Yong Wang. Their work appears in journals such as Bioinformatics, BMC Systems Biology, Scientific Reports, Nucleic Acids Research and Briefings in Bioinformatics.
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.