Wei Qiang
- Physiology top 1%
- Alzheimer's disease research and treatments 31
- Biomaterials top 2%
- Supramolecular Self-Assembly in Materials 15
- Spectroscopy top 2%
- Advanced NMR Techniques and Applications 22
- Molecular Biology top 5%
- Lipid Membrane Structure and Behavior 14
- Protein Structure and Dynamics 11
- Prion Diseases and Protein Misfolding 6
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- Solid-state spectroscopy and crystallography 5
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- NMR spectroscopy and applications 5
- Co-authors
- Robert TyckoWai‐Ming YauJunxia LuCharles D. SchwietersStephen C. MeredithJohn CollingeYongquan LuoMark P. Mattson
- Cited by
- PhysiologyBiomaterialsSpectroscopy
- Journals
- Journal of Biological Chemistry (5 papers)Biochimica et Biophysica Acta (BBA) - Biomembranes (4 papers)The Journal of Physical Chemistry B (3 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Wei Qiang
63 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Physiology 2.0k
- Biomaterials 617
- Spectroscopy 576
- Molecular Biology 2.0k
- Computational Theory and Mathematics 327
Countries citing papers authored by Wei Qiang
This map shows the geographic impact of Wei Qiang'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 Wei Qiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Qiang more than expected).
Fields of papers citing papers by Wei Qiang
This network shows the impact of papers produced by Wei Qiang. 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 Wei Qiang. The network helps show where Wei Qiang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Wei Qiang, 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 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 6 | |
| 7 | 2021 | 9 | |
| 8 | 2021 | 12 | |
| 9 | 2021 | 5 | |
| 10 | 2021 | 12 | |
| 11 | 2020 | 13 | |
| 12 | 2020 | 10 | |
| 13 | 2019 | 16 | |
| 14 | 2018 | 41 | |
| 15 | 2018 | 6 | |
| 16 | 2018 | 20 | |
| 17 | 2017 | 5 | |
| 18 | 2017 | 13 | |
| 19 | 2016 | 8 | |
| 20 | 2016 | 50 |
About Wei Qiang
Wei Qiang is a scholar working on Spectroscopy, Physiology, Biomaterials, Microbiology and Molecular Biology, having authored 65 papers that have together received 3.1k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (31 papers), Advanced NMR Techniques and Applications (22 papers), Supramolecular Self-Assembly in Materials (15 papers), Lipid Membrane Structure and Behavior (14 papers), Protein Structure and Dynamics (11 papers), Prion Diseases and Protein Misfolding (6 papers), Solid-state spectroscopy and crystallography (5 papers) and NMR spectroscopy and applications (5 papers). The work is most often cited by research in Physiology (2.0k citations), Biomaterials (617 citations), Spectroscopy (576 citations), Molecular Biology (2.0k citations) and Computational Theory and Mathematics (327 citations). Wei Qiang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Robert Tycko, Wai‐Ming Yau, Junxia Lu, Charles D. Schwieters, Stephen C. Meredith, John Collinge, Yongquan Luo, Mark P. Mattson, Kevin A. Kelley and Nikolaos G. Sgourakis. Their work appears in journals such as Journal of Biological Chemistry, Biochimica et Biophysica Acta (BBA) - Biomembranes, The Journal of Physical Chemistry B, Biochemistry and Proceedings of the National Academy of Sciences.
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.