Shifan Ma
Impact in
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- Computational Drug Discovery Methods
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- Neuroscience and Neuropharmacology Research
Papers in
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- Receptor Mechanisms and Signaling 6
- Protein Degradation and Inhibitors 1
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- Computational Drug Discovery Methods 7
- Co-authors
- Xiang‐Qun Xie (9 shared papers)Zhiwei Feng (7 shared papers)Lirong Wang (3 shared papers)Yifeng Chai (2 shared papers)Ziheng Hu (3 shared papers)Yifan Xia (2 shared papers)Si Chen (2 shared papers)Peng Yang (1 shared paper)
- Journals
- Nano Energy (2 papers)The AAPS Journal (2 papers)Journal of Chemical Information and Modeling (2 papers)Scientific Reports (1 paper)Molecular Pharmaceutics (1 paper)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Shifan Ma
17 papers receiving 447 citations
Peers
Comparison fields: 5 of 87
- Computational Theory and Mathematics 98
- Cellular and Molecular Neuroscience 81
- Molecular Biology 231
- Pharmacology 26
- Pharmacology 46
Countries citing papers authored by Shifan Ma
This map shows the geographic impact of Shifan Ma'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 Shifan Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shifan Ma more than expected).
Fields of papers citing papers by Shifan Ma
This network shows the impact of papers produced by Shifan Ma. 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 Shifan Ma. The network helps show where Shifan Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Shifan Ma, 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 | 2019 | 125 | |
| 2 | 2017 | 56 | |
| 3 | 2024 | 42 | |
| 4 | 2015 | 33 | |
| 5 | 2019 | 33 | |
| 6 | 2016 | 32 | |
| 7 | 2015 | 29 | |
| 8 | 2016 | 29 | |
| 9 | 2016 | 18 | |
| 10 | 2024 | 16 | |
| 11 | 2024 | 11 | |
| 12 | 2018 | 9 | |
| 13 | 2018 | 7 | |
| 14 | 2021 | 6 | |
| 15 | 2021 | 4 | |
| 16 | 2020 | 1 | |
| 17 | 2022 | 1 |
About Shifan Ma
Shifan Ma is a scholar working on Molecular Biology, Computational Theory and Mathematics, Pharmacology, Cellular and Molecular Neuroscience and Cardiology and Cardiovascular Medicine, having authored 17 papers that have together received 452 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Receptor Mechanisms and Signaling (6 papers), Neuropeptides and Animal Physiology (2 papers), Tactile and Sensory Interactions (2 papers), Advanced Sensor and Energy Harvesting Materials (2 papers), Pancreatic function and diabetes (1 paper), Protein Degradation and Inhibitors (1 paper) and Neuroscience and Neural Engineering (1 paper). The work is most often cited by research in Computational Theory and Mathematics (98 citations), Cellular and Molecular Neuroscience (81 citations), Molecular Biology (231 citations), Pharmacology (26 citations) and Pharmacology (46 citations). Shifan Ma has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Xiang‐Qun Xie, Zhiwei Feng, Lirong Wang, Yifeng Chai, Ziheng Hu, Yifan Xia, Si Chen, Peng Yang, Yun Wang and Xin Wang. Their work appears in journals such as Nano Energy, The AAPS Journal, Journal of Chemical Information and Modeling, Scientific Reports and Molecular Pharmaceutics.
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.