Huixian Wu
- Molecular Biology top 2%
- Cellular and Molecular Neuroscience top 1%
- Radiology, Nuclear Medicine and Imaging top 5%
- Oncology top 10%
- Computational Theory and Mathematics top 1%
- Co-authors
- Raymond C. StevensVadim CherezovVsevolod KatritchGye Won HanBryan L. RothXi‐Ping HuangEyal VardyKenneth A. Jacobson
- Topics
- Neuropeptides and Animal Physiology (9 papers)Semiconductor materials and devices (9 papers)Integrated Circuits and Semiconductor Failure Analysis (8 papers)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Huixian Wu
29 papers receiving 3.4k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Molecular Biology 3.0k
- Cellular and Molecular Neuroscience 1.8k
- Radiology, Nuclear Medicine and Imaging 464
- Oncology 362
- Computational Theory and Mathematics 356
Countries citing papers authored by Huixian Wu
This map shows the geographic impact of Huixian Wu'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 Huixian Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Huixian Wu more than expected).
Fields of papers citing papers by Huixian Wu
This network shows the impact of papers produced by Huixian Wu. 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 Huixian Wu. The network helps show where Huixian Wu may publish in the future.
Co-authorship network of co-authors of Huixian Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Huixian Wu. A scholar is included among the top collaborators of Huixian Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Huixian Wu. Huixian Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 69 | |
| 5 | 313 | |
| 6 | 200 | |
| 7 | 369 | |
| 8 | 54 | |
| 9 | Structure of the human κ-opioid receptor in complex with JDTicbreakdown → | 718 |
| 10 | 388 | |
| 11 | 22 | |
| 12 | Structure of an Agonist-Bound Human A 2A Adenosine Receptorbreakdown → | 679 |
| 13 | 73 | |
| 14 | 50 | |
| 15 | 0 | |
| 16 | 2 | |
| 17 | 1 | |
| 18 | 4 | |
| 19 | 2 | |
| 20 | 8 |
About Huixian Wu
Huixian Wu is a scholar working on Cellular and Molecular Neuroscience, Physiology and Immunology, having authored 30 papers that have together received 3.6k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (9 papers), Semiconductor materials and devices (9 papers) and Integrated Circuits and Semiconductor Failure Analysis (8 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.8k citations), Physiology (272 citations) and Molecular Biology (3.0k citations). Huixian Wu has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Raymond C. Stevens, Vadim Cherezov, Vsevolod Katritch, Gye Won Han, Bryan L. Roth, Xi‐Ping Huang, Eyal Vardy, Kenneth A. Jacobson, Fei Xu and Zhan‐Guo Gao. Their work appears in journals such as Nature, Science 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.