Kun Bi
Impact in
- Immunology top 5%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Immune Response and Inflammation
- Cell Biology top 5%
- Cellular transport and secretion
Papers in
-
- DNA and Biological Computing 9
- Advanced biosensing and bioanalysis techniques 6
- Oncology 10
- Cytokine Signaling Pathways and Interactions 5
- 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)Marianne J.B. van Stipdonk (1 shared paper)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 StatesChinaNorway
In The Last Decade
Kun Bi
47 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 105
- Immunology 579
- Cell Biology 289
- Aging 30
- Immunology and Allergy 82
- Molecular Biology 889
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 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 267 | |
| 2 | 2001 | 192 | |
| 3 | 1997 | 160 | |
| 4 | 2000 | 157 | |
| 5 | 2002 | 123 | |
| 6 | 2003 | 67 | |
| 7 | 2005 | 62 | |
| 8 | 1999 | 57 | |
| 9 | 2001 | 56 | |
| 10 | 2008 | 39 | |
| 11 | 2012 | 32 | |
| 12 | 2001 | 31 | |
| 13 | 2021 | 28 | |
| 14 | 2009 | 27 | |
| 15 | 2011 | 25 | |
| 16 | 2021 | 25 | |
| 17 | 2020 | 23 | |
| 18 | 2008 | 18 | |
| 19 | 2013 | 17 | |
| 20 | 2008 | 16 |
About Kun Bi
Kun Bi is a scholar working on Molecular Biology, Oncology, Immunology, Cell Biology and Organic Chemistry, having authored 51 papers that have together received 1.6k indexed citations. Recurring topics across this work include DNA and Biological Computing (9 papers), T-cell and B-cell Immunology (6 papers), Immune Cell Function and Interaction (6 papers), Advanced biosensing and bioanalysis techniques (6 papers), Cytokine Signaling Pathways and Interactions (5 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Cellular transport and secretion (4 papers) and Algorithms and Data Compression (4 papers). The work is most often cited by research in Immunology (579 citations), Cell Biology (289 citations), Aging (30 citations), Immunology and Allergy (82 citations) and Molecular Biology (889 citations). Kun Bi has collaborated with scholars based in United States, China and Norway. Frequent co-authors include Amnon Altman, Yoshihiko Tanaka, Nicholas T. Ktistakis, Michael G. Roth, Martín Villalba, Marianne J.B. van Stipdonk, Nolwenn Coudronnière, Katsuji Sugie, Fernando Rodrı́guez and Stephen P. Schoenberger. 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.