Beili Wu
- Physiology top 0.5%
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- Neuropeptides and Animal Physiology 18
- Virology top 2%
- HIV Research and Treatment 6
- Molecular Biology top 2%
- Receptor Mechanisms and Signaling 32
- Signaling Pathways in Disease 6
- Immunology top 5%
- Immune Cell Function and Interaction 5
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- Monoclonal and Polyclonal Antibodies Research 9
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- Chemokine receptors and signaling 8
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- Mass Spectrometry Techniques and Applications 6
- Co-authors
- Raymond C. StevensQiang ZhaoVadim CherezovVsevolod KatritchGustavo FenaltiRuben AbagyanTracy M. HandelDamon J. Hamel
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Beili Wu
59 papers receiving 4.9k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Physiology 471
- Cellular and Molecular Neuroscience 1.5k
- Virology 327
- Molecular Biology 3.6k
- Immunology 814
Countries citing papers authored by Beili Wu
This map shows the geographic impact of Beili 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 Beili Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beili Wu more than expected).
Fields of papers citing papers by Beili Wu
This network shows the impact of papers produced by Beili 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 Beili Wu. The network helps show where Beili Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Beili Wu, 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 | 2024 | 2 | |
| 2 | 2023 | 28 | |
| 3 | 2023 | 31 | |
| 4 | 2022 | 34 | |
| 5 | 2022 | 35 | |
| 6 | 2022 | 73 | |
| 7 | 2022 | 2 | |
| 8 | 2021 | 14 | |
| 9 | 2021 | 96 | |
| 10 | 2020 | 8 | |
| 11 | 2020 | 110 | |
| 12 | 2020 | 32 | |
| 13 | 2019 | 44 | |
| 14 | 2018 | 2 | |
| 15 | 2015 | 11 | |
| 16 | 2015 | 70 | |
| 17 | Structure of the CCR5 Chemokine Receptor–HIV Entry Inhibitor Maraviroc Complexbreakdown → | 2013 | 552 |
| 18 | Structures of the CXCR4 Chemokine GPCR with Small-Molecule and Cyclic Peptide Antagonistsbreakdown → | 2010 | 1462 |
| 19 | 2006 | 47 | |
| 20 | Comparative molecular dynamics simulations: Glutamate receptors and periplasmic binding proteins | 2004 | 1 |
About Beili Wu
Beili Wu is a scholar working on Virology, Cellular and Molecular Neuroscience, Physiology, Molecular Biology and Animal Science and Zoology, having authored 62 papers that have together received 5.0k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (32 papers), Neuropeptides and Animal Physiology (18 papers), Monoclonal and Polyclonal Antibodies Research (9 papers), Chemokine receptors and signaling (8 papers), Mass Spectrometry Techniques and Applications (6 papers), HIV Research and Treatment (6 papers), Signaling Pathways in Disease (6 papers) and Immune Cell Function and Interaction (5 papers). The work is most often cited by research in Physiology (471 citations), Cellular and Molecular Neuroscience (1.5k citations), Virology (327 citations), Molecular Biology (3.6k citations) and Immunology (814 citations). Beili Wu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Raymond C. Stevens, Qiang Zhao, Vadim Cherezov, Vsevolod Katritch, Gustavo Fenalti, Ruben Abagyan, Tracy M. Handel, Damon J. Hamel, Peter G. Wells and Clifford D. Mol. Their work appears in journals such as Nature Communications, Nature, Science, Proceedings of the National Academy of Sciences and Science Advances.
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.