Limeng Pu
Impact in
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- Computational Drug Discovery Methods
- Health Informatics top 10%
Papers in
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- Protein Structure and Dynamics 6
- Bioinformatics and Genomic Networks 5
- Machine Learning in Bioinformatics 2
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- Computational Drug Discovery Methods 9
- Co-authors
- Hsiao‐Chun Wu (17 shared papers)Michał Bryliński (11 shared papers)Supratik Mukhopadhyay (3 shared papers)Misagh Naderi (1 shared paper)Tairan Liu (1 shared paper)Rajiv Gandhi Govindaraj (1 shared paper)J. Ramanujam (8 shared papers)Jin‐Woo Choi (3 shared papers)
- Journals
- American Mineralogist (1 paper)BMC Pharmacology and Toxicology (1 paper)IEEE Transactions on Wireless Communications (1 paper)Bioinformatics (1 paper)BMC Cancer (1 paper)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Limeng Pu
25 papers receiving 404 citations
Peers
Comparison fields: 5 of 97
- Computational Theory and Mathematics 211
- Health Informatics 12
- Biophysics 22
- Molecular Biology 215
- Pharmacology 31
Countries citing papers authored by Limeng Pu
This map shows the geographic impact of Limeng Pu'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 Limeng Pu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Limeng Pu more than expected).
Fields of papers citing papers by Limeng Pu
This network shows the impact of papers produced by Limeng Pu. 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 Limeng Pu. The network helps show where Limeng Pu may publish in the future.
Co-authors
The 25 scholars most cited alongside Limeng Pu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 122 | |
| 2 | 2019 | 86 | |
| 3 | 2018 | 28 | |
| 4 | 2023 | 20 | |
| 5 | 2021 | 17 | |
| 6 | 2022 | 17 | |
| 7 | 2022 | 16 | |
| 8 | 2022 | 15 | |
| 9 | 2020 | 13 | |
| 10 | 2017 | 11 | |
| 11 | 2022 | 11 | |
| 12 | 2019 | 11 | |
| 13 | 2022 | 10 | |
| 14 | 2014 | 10 | |
| 15 | 2022 | 9 | |
| 16 | 2016 | 7 | |
| 17 | 2022 | 6 | |
| 18 | 2020 | 2 | |
| 19 | 2018 | 2 | |
| 20 | 2016 | 1 |
About Limeng Pu
Limeng Pu is a scholar working on Molecular Biology, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Biomedical Engineering, having authored 27 papers that have together received 419 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Protein Structure and Dynamics (6 papers), Bioinformatics and Genomic Networks (5 papers), Non-Invasive Vital Sign Monitoring (3 papers), Machine Learning in Bioinformatics (2 papers), Advanced Wireless Network Optimization (2 papers), Wireless Signal Modulation Classification (2 papers) and Image Processing Techniques and Applications (2 papers). The work is most often cited by research in Computational Theory and Mathematics (211 citations), Health Informatics (12 citations), Biophysics (22 citations), Molecular Biology (215 citations) and Pharmacology (31 citations). Limeng Pu has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Hsiao‐Chun Wu, Michał Bryliński, Supratik Mukhopadhyay, Misagh Naderi, Tairan Liu, Rajiv Gandhi Govindaraj, J. Ramanujam, Jin‐Woo Choi, Wentao Shi and Weidong Xiang. Their work appears in journals such as American Mineralogist, BMC Pharmacology and Toxicology, IEEE Transactions on Wireless Communications, Bioinformatics and BMC Cancer.
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.