BinQing Wei
Impact in
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- Computational Drug Discovery Methods
- Pharmacology top 2%
- Cannabis and Cannabinoid Research
Papers in
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- PI3K/AKT/mTOR signaling in cancer 2
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- Carbon Nanotubes in Composites 11
- Graphene research and applications 10
- Co-authors
- Brian K. Shoichet (5 shared papers)John J. Irwin (1 shared paper)Susan L. McGovern (1 shared paper)Benjamin F. Cravatt (2 shared papers)P. M. Ajayan (3 shared papers)Brian W. Matthews (2 shared papers)L.H. Weaver (2 shared papers)Ganapathiraman Ramanath (2 shared papers)
- Journals
- Journal of Medicinal Chemistry (4 papers)Bioconjugate Chemistry (3 papers)Bioorganic & Medicinal Chemistry Letters (3 papers)Materials Letters (2 papers)Journal of Molecular Biology (2 papers)
- Partner nations
- United StatesChinaFrance
In The Last Decade
BinQing Wei
34 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 134
- Computational Theory and Mathematics 529
- Pharmacology 358
- Materials Chemistry 793
- Toxicology 54
- Molecular Biology 1.0k
Countries citing papers authored by BinQing Wei
This map shows the geographic impact of BinQing Wei'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 BinQing Wei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites BinQing Wei more than expected).
Fields of papers citing papers by BinQing Wei
This network shows the impact of papers produced by BinQing Wei. 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 BinQing Wei. The network helps show where BinQing Wei may publish in the future.
Co-authors
The 25 scholars most cited alongside BinQing Wei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 392 | |
| 2 | 2002 | 367 | |
| 3 | 2006 | 277 | |
| 4 | 2005 | 203 | |
| 5 | 2002 | 178 | |
| 6 | 2004 | 177 | |
| 7 | 2004 | 131 | |
| 8 | 2001 | 83 | |
| 9 | 2001 | 76 | |
| 10 | 2018 | 75 | |
| 11 | 2003 | 67 | |
| 12 | 2012 | 50 | |
| 13 | 2001 | 50 | |
| 14 | 2001 | 47 | |
| 15 | 2001 | 38 | |
| 16 | 2018 | 32 | |
| 17 | 2017 | 28 | |
| 18 | 2017 | 28 | |
| 19 | 1997 | 26 | |
| 20 | 2013 | 25 |
About BinQing Wei
BinQing Wei is a scholar working on Molecular Biology, Materials Chemistry, Organic Chemistry, Oncology and Computational Theory and Mathematics, having authored 34 papers that have together received 2.5k indexed citations. Recurring topics across this work include Carbon Nanotubes in Composites (11 papers), Graphene research and applications (10 papers), Computational Drug Discovery Methods (6 papers), HER2/EGFR in Cancer Research (6 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), Peptidase Inhibition and Analysis (3 papers), PI3K/AKT/mTOR signaling in cancer (2 papers) and Cancer Treatment and Pharmacology (2 papers). The work is most often cited by research in Computational Theory and Mathematics (529 citations), Pharmacology (358 citations), Materials Chemistry (793 citations), Toxicology (54 citations) and Molecular Biology (1.0k citations). BinQing Wei has collaborated with scholars based in United States, China and France. Frequent co-authors include Brian K. Shoichet, John J. Irwin, Susan L. McGovern, Benjamin F. Cravatt, P. M. Ajayan, Brian W. Matthews, L.H. Weaver, Ganapathiraman Ramanath, Róbert Vajtai and Yung Joon Jung. Their work appears in journals such as Journal of Medicinal Chemistry, Bioconjugate Chemistry, Bioorganic & Medicinal Chemistry Letters, Materials Letters and Journal of Molecular Biology.
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.