Hao Fan
Impact in
- Molecular Biology top 5%
- Protein Structure and Dynamics
- Receptor Mechanisms and Signaling
- RNA and protein synthesis mechanisms
- Ubiquitin and proteasome pathways
-
- Computational Drug Discovery Methods
Papers in
- Pharmacology 11
- Pharmacogenetics and Drug Metabolism 10
- Co-authors
- Andrej SăliAlan E. MarkJohn J. IrwinBrian K. ShoichetAvner SchlessingerCheng ZhangDina Schneidman‐DuhovnyJiang Zhu
- Journals
- Proteins Structure Function and Bioinformatics (6 papers)Proceedings of the National Academy of Sciences (5 papers)Nature Communications (4 papers)Journal of Biological Chemistry (4 papers)Biochemistry (4 papers)
- Partner nations
- SingaporeUnited StatesChina
In The Last Decade
Hao Fan
87 papers receiving 3.0k citations
Peers
Comparison fields: 5 of 144
- Molecular Biology 2.1k
- Computational Theory and Mathematics 478
- Biochemistry 216
- Cellular and Molecular Neuroscience 336
- Pharmacology 148
Countries citing papers authored by Hao Fan
This map shows the geographic impact of Hao Fan'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 Hao Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao Fan more than expected).
Fields of papers citing papers by Hao Fan
This network shows the impact of papers produced by Hao Fan. 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 Hao Fan. The network helps show where Hao Fan may publish in the future.
Co-authors
The 25 scholars most cited alongside Hao Fan, 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 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 4 | |
| 7 | 2023 | 7 | |
| 8 | 2023 | 3 | |
| 9 | 2023 | 6 | |
| 10 | 2022 | 11 | |
| 11 | 2021 | 11 | |
| 12 | 2021 | 9 | |
| 13 | 2020 | 13 | |
| 14 | 2020 | 85 | |
| 15 | 2019 | 78 | |
| 16 | 2018 | 57 | |
| 17 | 2017 | 45 | |
| 18 | 2013 | 16 | |
| 19 | 2011 | 104 | |
| 20 | 2006 | 8 |
About Hao Fan
Hao Fan is a scholar working on Pharmacology, Biochemistry, Molecular Biology, Computational Theory and Mathematics and Oncology, having authored 93 papers that have together received 3.0k indexed citations. Recurring topics across this work include Enzyme Structure and Function (19 papers), Protein Structure and Dynamics (17 papers), Computational Drug Discovery Methods (12 papers), Pharmacogenetics and Drug Metabolism (10 papers), Receptor Mechanisms and Signaling (10 papers), Peptidase Inhibition and Analysis (8 papers), Ubiquitin and proteasome pathways (6 papers) and Biochemical and Molecular Research (5 papers). The work is most often cited by research in Molecular Biology (2.1k citations), Computational Theory and Mathematics (478 citations), Biochemistry (216 citations), Cellular and Molecular Neuroscience (336 citations) and Pharmacology (148 citations). Hao Fan has collaborated with scholars based in Singapore, United States and China. Frequent co-authors include Andrej Săli, Alan E. Mark, John J. Irwin, Brian K. Shoichet, Avner Schlessinger, Cheng Zhang, Dina Schneidman‐Duhovny, Jiang Zhu, Kathleen M. Giacomini and Guang Qiang Dong. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Proceedings of the National Academy of Sciences, Nature Communications, Journal of Biological Chemistry and Biochemistry.
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.