Lesong Wei
Impact in
- Microbiology top 5%
- Antimicrobial Peptides and Activities
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- Computational Drug Discovery Methods
Papers in
-
- Machine Learning in Bioinformatics 5
- vaccines and immunoinformatics approaches 4
- Biochemical and Structural Characterization 3
- Protein Structure and Dynamics 3
- RNA and protein synthesis mechanisms 1
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- Computational Drug Discovery Methods 5
- Co-authors
- Leyi Wei (7 shared papers)Xiucai Ye (6 shared papers)Tetsuya Sakurai (4 shared papers)Zengchao Mu (1 shared paper)Jie Chen (1 shared paper)Yi Jiang (1 shared paper)Dong‐Qing Wei (1 shared paper)Yitian Fang (1 shared paper)
- Journals
- Briefings in Bioinformatics (4 papers)Methods (2 papers)Bioinformatics (2 papers)BMC Biology (1 paper)Frontiers in Genetics (1 paper)
- Partner nations
- ChinaJapanSouth Korea
In The Last Decade
Lesong Wei
13 papers receiving 417 citations
Peers
Comparison fields: 5 of 49
- Microbiology 85
- Computational Theory and Mathematics 132
- Molecular Biology 333
- Immunology 18
- Radiology, Nuclear Medicine and Imaging 17
Countries citing papers authored by Lesong Wei
This map shows the geographic impact of Lesong Wei'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 Lesong Wei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lesong Wei more than expected).
Fields of papers citing papers by Lesong Wei
This network shows the impact of papers produced by Lesong Wei. 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 Lesong Wei. The network helps show where Lesong Wei may publish in the future.
Co-authors
The 25 scholars most cited alongside Lesong Wei, 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 | 2022 | 122 | |
| 2 | 2021 | 86 | |
| 3 | 2023 | 48 | |
| 4 | 2022 | 40 | |
| 5 | 2022 | 39 | |
| 6 | 2022 | 22 | |
| 7 | 2021 | 18 | |
| 8 | 2021 | 13 | |
| 9 | 2022 | 12 | |
| 10 | 2024 | 10 | |
| 11 | 2021 | 4 | |
| 12 | 2025 | 3 | |
| 13 | 2022 | 2 |
About Lesong Wei
Lesong Wei is a scholar working on Molecular Biology, Computational Theory and Mathematics, Microbiology, Materials Chemistry and Infectious Diseases, having authored 13 papers that have together received 419 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Machine Learning in Bioinformatics (5 papers), vaccines and immunoinformatics approaches (4 papers), Biochemical and Structural Characterization (3 papers), Protein Structure and Dynamics (3 papers), Antimicrobial Peptides and Activities (2 papers), RNA and protein synthesis mechanisms (1 paper) and Machine Learning in Materials Science (1 paper). The work is most often cited by research in Microbiology (85 citations), Computational Theory and Mathematics (132 citations), Molecular Biology (333 citations), Immunology (18 citations) and Radiology, Nuclear Medicine and Imaging (17 citations). Lesong Wei has collaborated with scholars based in China, Japan and South Korea. Frequent co-authors include Leyi Wei, Xiucai Ye, Tetsuya Sakurai, Zengchao Mu, Jie Chen, Yi Jiang, Dong‐Qing Wei, Yitian Fang, Lizhen Cui and Wenjia He. Their work appears in journals such as Briefings in Bioinformatics, Methods, Bioinformatics, BMC Biology and Frontiers in Genetics.
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.