Fangping Wan
Impact in
-
- Computational Drug Discovery Methods
- Microbiology top 5%
- Antimicrobial Peptides and Activities
Papers in
-
- vaccines and immunoinformatics approaches 5
- Machine Learning in Bioinformatics 4
- Protein Structure and Dynamics 4
- RNA and protein synthesis mechanisms 3
- Chemical Synthesis and Analysis 3
-
- Computational Drug Discovery Methods 6
- Co-authors
- Jianyang Zeng (10 shared papers)Tao Jiang (3 shared papers)César de la Fuente‐Núñez (8 shared papers)Dan Zhao (7 shared papers)Lixiang Hong (2 shared papers)Shuya Li (6 shared papers)An Xiao (2 shared papers)Felix Wong (1 shared paper)
- Journals
- Bioinformatics (3 papers)iScience (1 paper)Nature Communications (1 paper)Nature Machine Intelligence (1 paper)Expert Opinion on Drug Discovery (1 paper)
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Fangping Wan
17 papers receiving 1.1k citations
Fangping Wan's Hit Papers
Peers
Comparison fields: 5 of 103
- Computational Theory and Mathematics 523
- Microbiology 161
- Molecular Biology 847
- Applied Microbiology and Biotechnology 22
- Molecular Medicine 25
Countries citing papers authored by Fangping Wan
This map shows the geographic impact of Fangping Wan'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 Fangping Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fangping Wan more than expected).
Fields of papers citing papers by Fangping Wan
This network shows the impact of papers produced by Fangping Wan. 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 Fangping Wan. The network helps show where Fangping Wan may publish in the future.
Co-authors
The 25 scholars most cited alongside Fangping Wan, 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 | 2018 | 256 | |
| 2 | 2020 | 153 | |
| 3 | 2021 | 146 | |
| 4 | Machine learning for antimicrobial peptide identification and design Hit paper breakdown → | 2024 | 102 |
| 5 | 2019 | 74 | |
| 6 | Deep-learning-enabled antibiotic discovery through molecular de-extinction Hit paper breakdown → | 2024 | 72 |
| 7 | 2022 | 72 | |
| 8 | 2019 | 64 | |
| 9 | 2020 | 42 | |
| 10 | 2023 | 32 | |
| 11 | 2020 | 21 | |
| 12 | 2020 | 19 | |
| 13 | 2022 | 17 | |
| 14 | 2021 | 10 | |
| 15 | 2025 | 2 | |
| 16 | 2025 | 2 | |
| 17 | 2025 | 1 | |
| 18 | 2025 | 0 |
About Fangping Wan
Fangping Wan is a scholar working on Molecular Biology, Computational Theory and Mathematics, Microbiology, Materials Chemistry and Artificial Intelligence, having authored 18 papers that have together received 1.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Antimicrobial Peptides and Activities (6 papers), vaccines and immunoinformatics approaches (5 papers), Machine Learning in Bioinformatics (4 papers), Machine Learning in Materials Science (4 papers), Protein Structure and Dynamics (4 papers), RNA and protein synthesis mechanisms (3 papers) and Chemical Synthesis and Analysis (3 papers). The work is most often cited by research in Computational Theory and Mathematics (523 citations), Microbiology (161 citations), Molecular Biology (847 citations), Applied Microbiology and Biotechnology (22 citations) and Molecular Medicine (25 citations). Fangping Wan has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Jianyang Zeng, Tao Jiang, César de la Fuente‐Núñez, Dan Zhao, Lixiang Hong, Shuya Li, An Xiao, Felix Wong, James J. Collins and Hantao Shu. Their work appears in journals such as Bioinformatics, iScience, Nature Communications, Nature Machine Intelligence and Expert Opinion on Drug Discovery.
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.