Yaowen Gu
Impact in
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- Computational Drug Discovery Methods
Papers in
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- Bioinformatics and Genomic Networks 6
- Protein Structure and Dynamics 3
- Machine Learning in Bioinformatics 2
- Biomedical Text Mining and Ontologies 2
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- Computational Drug Discovery Methods 12
- Co-authors
- Jiao Li (15 shared papers)Si Zheng (11 shared papers)Qijin Yin (2 shared papers)Rui Jiang (4 shared papers)Hongyu Kang (5 shared papers)Liang Li (3 shared papers)Ziyang Wang (2 shared papers)Xiao Ting Lu (1 shared paper)
- Journals
- Computers in Biology and Medicine (3 papers)Journal of Medical Internet Research (2 papers)Briefings in Bioinformatics (2 papers)Journal of Chemical Information and Modeling (2 papers)Artificial Cells Nanomedicine and Biotechnology (1 paper)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Yaowen Gu
21 papers receiving 252 citations
Peers
Comparison fields: 5 of 70
- Computational Theory and Mathematics 94
- Health Informatics 4
- Molecular Biology 101
- Complementary and alternative medicine 9
- Pharmacy 5
Countries citing papers authored by Yaowen Gu
This map shows the geographic impact of Yaowen Gu'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 Yaowen Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yaowen Gu more than expected).
Fields of papers citing papers by Yaowen Gu
This network shows the impact of papers produced by Yaowen Gu. 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 Yaowen Gu. The network helps show where Yaowen Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Yaowen Gu, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 50 | |
| 2 | 2022 | 33 | |
| 3 | 2023 | 19 | |
| 4 | 2024 | 17 | |
| 5 | 2023 | 16 | |
| 6 | 2022 | 15 | |
| 7 | 2023 | 14 | |
| 8 | 2023 | 14 | |
| 9 | 2023 | 13 | |
| 10 | 2023 | 9 | |
| 11 | 2022 | 8 | |
| 12 | 2022 | 8 | |
| 13 | 2024 | 7 | |
| 14 | 2021 | 7 | |
| 15 | 2021 | 5 | |
| 16 | 2025 | 5 | |
| 17 | 2024 | 4 | |
| 18 | 2022 | 3 | |
| 19 | 2025 | 3 | |
| 20 | 2024 | 2 |
About Yaowen Gu
Yaowen Gu is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Artificial Intelligence and Epidemiology, having authored 22 papers that have together received 254 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), Bioinformatics and Genomic Networks (6 papers), Machine Learning in Materials Science (4 papers), Protein Structure and Dynamics (3 papers), Machine Learning in Healthcare (2 papers), Machine Learning in Bioinformatics (2 papers), Biomedical Text Mining and Ontologies (2 papers) and Urinary Tract Infections Management (2 papers). The work is most often cited by research in Computational Theory and Mathematics (94 citations), Health Informatics (4 citations), Molecular Biology (101 citations), Complementary and alternative medicine (9 citations) and Pharmacy (5 citations). Yaowen Gu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Jiao Li, Si Zheng, Qijin Yin, Rui Jiang, Hongyu Kang, Liang Li, Ziyang Wang, Xiao Ting Lu, Bao Song and Xiaozhong Wen. Their work appears in journals such as Computers in Biology and Medicine, Journal of Medical Internet Research, Briefings in Bioinformatics, Journal of Chemical Information and Modeling and Artificial Cells Nanomedicine and Biotechnology.
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.