Pan Tan
Impact in
Papers in
-
- Protein Structure and Dynamics 11
- RNA and protein synthesis mechanisms 6
- Machine Learning in Bioinformatics 5
- Genomics and Phylogenetic Studies 2
-
- Enzyme Structure and Function 4
- Material Dynamics and Properties 4
- Co-authors
- Liang Hong (20 shared papers)Xiangjun Xing (2 shared papers)Eugene Mamontov (2 shared papers)Qin Xu (1 shared paper)Jinglai Li (2 shared papers)Lirong Zheng (5 shared papers)Loukas Petridis (2 shared papers)Jeremy C. Smith (1 shared paper)
- Journals
- Nature Communications (3 papers)Physical Chemistry Chemical Physics (2 papers)Acta Pharmaceutica Sinica B (2 papers)Physical Review Research (2 papers)Journal of Cheminformatics (2 papers)
- Partner nations
- ChinaUnited StatesNorth Korea
In The Last Decade
Pan Tan
25 papers receiving 330 citations
Peers
Comparison fields: 5 of 82
- Filtration and Separation 7
- Modeling and Simulation 15
- Molecular Biology 157
- Spectroscopy 36
- Atomic and Molecular Physics, and Optics 62
Countries citing papers authored by Pan Tan
This map shows the geographic impact of Pan Tan'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 Pan Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pan Tan more than expected).
Fields of papers citing papers by Pan Tan
This network shows the impact of papers produced by Pan Tan. 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 Pan Tan. The network helps show where Pan Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Pan Tan, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 63 | |
| 2 | 2021 | 34 | |
| 3 | 2024 | 34 | |
| 4 | 2018 | 26 | |
| 5 | 2023 | 24 | |
| 6 | 2020 | 18 | |
| 7 | 2022 | 16 | |
| 8 | 2024 | 16 | |
| 9 | 2022 | 13 | |
| 10 | 2020 | 12 | |
| 11 | 2022 | 12 | |
| 12 | 2024 | 11 | |
| 13 | 2020 | 10 | |
| 14 | 2020 | 9 | |
| 15 | 2024 | 8 | |
| 16 | 2025 | 7 | |
| 17 | 2024 | 5 | |
| 18 | 2019 | 5 | |
| 19 | 2020 | 4 | |
| 20 | 2022 | 4 |
About Pan Tan
Pan Tan is a scholar working on Molecular Biology, Materials Chemistry, Atomic and Molecular Physics, and Optics, Biomedical Engineering and Spectroscopy, having authored 26 papers that have together received 341 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (11 papers), RNA and protein synthesis mechanisms (6 papers), Spectroscopy and Quantum Chemical Studies (5 papers), Machine Learning in Bioinformatics (5 papers), Enzyme Structure and Function (4 papers), Material Dynamics and Properties (4 papers), Quantum, superfluid, helium dynamics (2 papers) and Genomics and Phylogenetic Studies (2 papers). The work is most often cited by research in Filtration and Separation (7 citations), Modeling and Simulation (15 citations), Molecular Biology (157 citations), Spectroscopy (36 citations) and Atomic and Molecular Physics, and Optics (62 citations). Pan Tan has collaborated with scholars based in China, United States and North Korea. Frequent co-authors include Liang Hong, Xiangjun Xing, Eugene Mamontov, Qin Xu, Jinglai Li, Lirong Zheng, Loukas Petridis, Jeremy C. Smith, Guisheng Fan and Zhuo Liu. Their work appears in journals such as Nature Communications, Physical Chemistry Chemical Physics, Acta Pharmaceutica Sinica B, Physical Review Research and Journal of Cheminformatics.
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.