Kunhong Xiao
- Cellular and Molecular Neuroscience top 0.5%
- Neuropeptides and Animal Physiology 15
- Neuroscience and Neuropharmacology Research 6
- Molecular Biology top 1%
- Receptor Mechanisms and Signaling 37
- Protein Kinase Regulation and GTPase Signaling 13
- Photosynthetic Processes and Mechanisms 6
- Spectroscopy top 2%
- Mass Spectrometry Techniques and Applications 13
- Advanced Proteomics Techniques and Applications 6
- Cell Biology top 2%
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- Intraperitoneal and Appendiceal Malignancies 7
Kunhong Xiao
74 papers receiving 5.7k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Cellular and Molecular Neuroscience 2.1k
- Molecular Biology 4.6k
- Spectroscopy 478
- Cell Biology 472
- Computational Theory and Mathematics 353
Countries citing papers authored by Kunhong Xiao
This map shows the geographic impact of Kunhong Xiao'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 Kunhong Xiao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kunhong Xiao more than expected).
Fields of papers citing papers by Kunhong Xiao
This network shows the impact of papers produced by Kunhong Xiao. 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 Kunhong Xiao. The network helps show where Kunhong Xiao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kunhong Xiao, 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 | 2 | |
| 4 | 2024 | 6 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 4 | |
| 7 | 2022 | 9 | |
| 8 | 2020 | 38 | |
| 9 | 2020 | 39 | |
| 10 | 2019 | 44 | |
| 11 | 2016 | 21 | |
| 12 | 2012 | 32 | |
| 13 | Distinct Phosphorylation Sites on the β 2 -Adrenergic Receptor Establish a Barcode That Encodes Differential Functions of β-Arrestinbreakdown → | 2011 | 497 |
| 14 | 2010 | 164 | |
| 15 | 2010 | 92 | |
| 16 | 2009 | 125 | |
| 17 | 2009 | 125 | |
| 18 | Functional specialization of β-arrestin interactions revealed by proteomic analysisbreakdown → | 2007 | 327 |
| 19 | 2007 | 113 | |
| 20 | 2001 | 13 |
About Kunhong Xiao
Kunhong Xiao is a scholar working on Cellular and Molecular Neuroscience, Spectroscopy and Molecular Biology, having authored 81 papers that have together received 5.8k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (37 papers), Neuropeptides and Animal Physiology (15 papers), Mass Spectrometry Techniques and Applications (13 papers), Protein Kinase Regulation and GTPase Signaling (13 papers), Intraperitoneal and Appendiceal Malignancies (7 papers), Advanced Proteomics Techniques and Applications (6 papers), Neuroscience and Neuropharmacology Research (6 papers) and Photosynthetic Processes and Mechanisms (6 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (2.1k citations), Molecular Biology (4.6k citations) and Spectroscopy (478 citations). Kunhong Xiao has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Robert J. Lefkowitz, Sudha K. Shenoy, Arun K. Shukla, Seungkirl Ahn, Sudarshan Rajagopal, Makoto R. Hara, Minyong Chen, James W. Wisler, Olivier Lichtarge and Richard T. Premont. 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.