Kunbin Qu
Impact in
- Virology top 10%
- Poxvirus research and outbreaks
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- Biomedical Text Mining and Ontologies
- Bioinformatics and Genomic Networks
- Ubiquitin and proteasome pathways
- Machine Learning in Bioinformatics
Papers in
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- Biomedical Text Mining and Ontologies 4
- Ubiquitin and proteasome pathways 2
- Gene expression and cancer classification 2
- Bioinformatics and Genomic Networks 2
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- Data Mining Algorithms and Applications 2
- Co-authors
- Donald G. Payan (9 shared papers)Xiaoyan Zhu (3 shared papers)Ming Li (2 shared papers)Yu Hao (1 shared paper)Minlie Huang (1 shared paper)Jianing Huang (2 shared papers)Mary Shen (2 shared papers)Simon Yu (2 shared papers)
- Journals
- Bioinformatics (1 paper)IEEE Intelligent Systems (1 paper)Journal of Biology (1 paper)Current Medicinal Chemistry (1 paper)Journal of Biological Chemistry (1 paper)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Kunbin Qu
10 papers receiving 367 citations
Peers
Comparison fields: 5 of 57
- Virology 37
- Molecular Biology 297
- Artificial Intelligence 105
- Immunology 52
- Parasitology 11
Countries citing papers authored by Kunbin Qu
This map shows the geographic impact of Kunbin Qu'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 Kunbin Qu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kunbin Qu more than expected).
Fields of papers citing papers by Kunbin Qu
This network shows the impact of papers produced by Kunbin Qu. 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 Kunbin Qu. The network helps show where Kunbin Qu may publish in the future.
Co-authors
The 25 scholars most cited alongside Kunbin Qu, 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 | 2004 | 171 | |
| 2 | 2004 | 63 | |
| 3 | 2003 | 60 | |
| 4 | 2003 | 52 | |
| 5 | PathwayFinder: paving the way towards automatic pathway extraction | 2004 | 15 |
| 6 | 2004 | 13 | |
| 7 | 2004 | 5 | |
| 8 | 2007 | 5 | |
| 9 | 2002 | 3 | |
| 10 | 2002 | 2 |
About Kunbin Qu
Kunbin Qu is a scholar working on Molecular Biology, Information Systems, Artificial Intelligence, Organic Chemistry and Pathology and Forensic Medicine, having authored 10 papers that have together received 389 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (4 papers), Ubiquitin and proteasome pathways (2 papers), Gene expression and cancer classification (2 papers), Data Mining Algorithms and Applications (2 papers), Bioinformatics and Genomic Networks (2 papers), Semantic Web and Ontologies (2 papers), Cancer Mechanisms and Therapy (1 paper) and Click Chemistry and Applications (1 paper). The work is most often cited by research in Virology (37 citations), Molecular Biology (297 citations), Artificial Intelligence (105 citations), Immunology (52 citations) and Parasitology (11 citations). Kunbin Qu has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Donald G. Payan, Xiaoyan Zhu, Ming Li, Yu Hao, Minlie Huang, Jianing Huang, Mary Shen, Simon Yu, Mark K. Bennett and Susan D. Demo. Their work appears in journals such as Bioinformatics, IEEE Intelligent Systems, Journal of Biology, Current Medicinal Chemistry and Journal of Biological Chemistry.
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.