Kun Bi
Impact in
- Immunology top 5%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Immune Response and Inflammation
- Aging top 10%
Papers in
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- DNA and Biological Computing 10
- Advanced biosensing and bioanalysis techniques 6
-
- Immune Cell Function and Interaction 6
- T-cell and B-cell Immunology 6
- Co-authors
- Amnon Altman (6 shared papers)Yoshihiko Tanaka (3 shared papers)Nicholas T. Ktistakis (4 shared papers)Michael G. Roth (4 shared papers)Martín Villalba (3 shared papers)Sooji Hong (2 shared papers)Nolwenn Coudronnière (1 shared paper)Katsuji Sugie (1 shared paper)
- Journals
- SLAS DISCOVERY (5 papers)Assay and Drug Development Technologies (4 papers)Molecular BioSystems (3 papers)Expert Opinion on Drug Discovery (2 papers)The Journal of Cell Biology (2 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Kun Bi
49 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 105
- Immunology 575
- Aging 33
- Cell Biology 290
- Immunology and Allergy 84
- Cancer Research 185
Countries citing papers authored by Kun Bi
This map shows the geographic impact of Kun Bi'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 Kun Bi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Bi more than expected).
Fields of papers citing papers by Kun Bi
This network shows the impact of papers produced by Kun Bi. 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 Kun Bi. The network helps show where Kun Bi may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Bi, 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 52 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 276 | |
| 2 | 2001 | 200 | |
| 3 | 1997 | 163 | |
| 4 | 2000 | 163 | |
| 5 | 2002 | 125 | |
| 6 | 2003 | 71 | |
| 7 | 2005 | 67 | |
| 8 | 1999 | 59 | |
| 9 | 2001 | 56 | |
| 10 | 2008 | 40 | |
| 11 | 2021 | 36 | |
| 12 | 2012 | 36 | |
| 13 | 2001 | 31 | |
| 14 | 2009 | 29 | |
| 15 | 2011 | 28 | |
| 16 | 2021 | 27 | |
| 17 | 2020 | 26 | |
| 18 | 2008 | 20 | |
| 19 | 2013 | 19 | |
| 20 | 2008 | 17 |
About Kun Bi
Kun Bi is a scholar working on Molecular Biology, Immunology, Oncology, Cell Biology and Computational Theory and Mathematics, having authored 52 papers that have together received 1.7k indexed citations. Recurring topics across this work include DNA and Biological Computing (10 papers), Immune Cell Function and Interaction (6 papers), T-cell and B-cell Immunology (6 papers), Advanced biosensing and bioanalysis techniques (6 papers), Cytokine Signaling Pathways and Interactions (5 papers), Modular Robots and Swarm Intelligence (4 papers), Algorithms and Data Compression (4 papers) and Monoclonal and Polyclonal Antibodies Research (4 papers). The work is most often cited by research in Immunology (575 citations), Aging (33 citations), Cell Biology (290 citations), Immunology and Allergy (84 citations) and Cancer Research (185 citations). Kun Bi has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Amnon Altman, Yoshihiko Tanaka, Nicholas T. Ktistakis, Michael G. Roth, Martín Villalba, Sooji Hong, Nolwenn Coudronnière, Katsuji Sugie, Marianne J.B. van Stipdonk and Fernando A. Rodriguez. Their work appears in journals such as SLAS DISCOVERY, Assay and Drug Development Technologies, Molecular BioSystems, Expert Opinion on Drug Discovery and The Journal of Cell 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.