Min Li
Impact in
- Computational Theory and Mathematics top 0.05%
- Computational Drug Discovery Methods
- Molecular Biology top 0.5%
- Bioinformatics and Genomic Networks
- Machine Learning in Bioinformatics
- Protein Structure and Dynamics
- Gene expression and cancer classification
- Circular RNAs in diseases
Papers in
-
- Computational Drug Discovery Methods 99
-
- Bioinformatics and Genomic Networks 122
- Machine Learning in Bioinformatics 79
- Protein Structure and Dynamics 53
- Gene expression and cancer classification 44
- RNA and protein synthesis mechanisms 34
- Microbial Metabolic Engineering and Bioproduction 24
Min Li
446 papers receiving 10.6k citations
Hit Papers
Peers
Comparison fields: 5 of 203
- Computational Theory and Mathematics 2.8k
- Molecular Biology 7.3k
- Cancer Research 1.4k
- Health Information Management 203
- Neurology 263
Countries citing papers authored by Min Li
This map shows the geographic impact of Min Li'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 Min Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Min Li more than expected).
Fields of papers citing papers by Min Li
This network shows the impact of papers produced by Min Li. 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 Min Li. The network helps show where Min Li may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Min Li, 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 | 1 | |
| 2 | 2025 | 7 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 4 | |
| 7 | 2024 | 9 | |
| 8 | 2024 | 2 | |
| 9 | 2024 | 7 | |
| 10 | 2023 | 5 | |
| 11 | 2023 | 8 | |
| 12 | 2023 | 1 | |
| 13 | 2023 | 8 | |
| 14 | 2023 | 2 | |
| 15 | 2023 | 3 | |
| 16 | 2023 | 11 | |
| 17 | 2023 | 2 | |
| 18 | 2023 | 3 | |
| 19 | 2022 | 10 | |
| 20 | 2021 | 65 |
About Min Li
Min Li is a scholar working on Computational Theory and Mathematics, Molecular Biology, Cancer Research, Numerical Analysis and Artificial Intelligence, having authored 489 papers that have together received 10.8k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (122 papers), Computational Drug Discovery Methods (99 papers), Machine Learning in Bioinformatics (79 papers), Protein Structure and Dynamics (53 papers), Gene expression and cancer classification (44 papers), RNA and protein synthesis mechanisms (34 papers), Cancer-related molecular mechanisms research (28 papers) and Microbial Metabolic Engineering and Bioproduction (24 papers). The work is most often cited by research in Computational Theory and Mathematics (2.8k citations), Molecular Biology (7.3k citations), Cancer Research (1.4k citations), Health Information Management (203 citations) and Neurology (263 citations). Min Li has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Jianxin Wang, Yi Pan, Fang‐Xiang Wu, Yaohang Li, Min Zeng, Yu Tang, Ruiqing Zheng, Chengqian Lu, Fuhao Zhang and Wei Lan. Their work appears in journals such as IEEE/ACM Transactions on Computational Biology and Bioinformatics, Bioinformatics, Briefings in Bioinformatics, Methods and IEEE Journal of Biomedical and Health Informatics.
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.