Michelle Kuhne
- Immunology top 2%
- Molecular Biology top 10%
- Oncology top 5%
- Genetics top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Co-authors
- Arthur WeissGustav E. LienhardDeborah YablonskiTony PawsonTheresa A. KadlecekGuosheng FengAlan J. KormanPina M. Cardarelli
- Topics
- Monoclonal and Polyclonal Antibodies Research (12 papers)Immunotherapy and Immune Responses (10 papers)CAR-T cell therapy research (8 papers)
- Cited by
- ImmunologyOncologyGenetics
- Partner nations
- United StatesNew ZealandGermany
In The Last Decade
Michelle Kuhne
34 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 85
- Immunology 1.1k
- Molecular Biology 933
- Oncology 788
- Genetics 243
- Radiology, Nuclear Medicine and Imaging 213
Countries citing papers authored by Michelle Kuhne
This map shows the geographic impact of Michelle Kuhne'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 Michelle Kuhne with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michelle Kuhne more than expected).
Fields of papers citing papers by Michelle Kuhne
This network shows the impact of papers produced by Michelle Kuhne. 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 Michelle Kuhne. The network helps show where Michelle Kuhne may publish in the future.
Co-authorship network of co-authors of Michelle Kuhne
This figure shows the co-authorship network connecting the top 25 collaborators of Michelle Kuhne. A scholar is included among the top collaborators of Michelle Kuhne based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michelle Kuhne. Michelle Kuhne is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 1 | |
| 3 | 12 | |
| 4 | In Vitro Characterization of the Anti-PD-1 Antibody Nivolumab, BMS-936558, and In Vivo Toxicology in Non-Human Primatesbreakdown → | 472 |
| 5 | 4 | |
| 6 | 6 | |
| 7 | 181 | |
| 8 | 1 | |
| 9 | Abstract #LB-150: A fully human anti-CXCR4 antibody induces apoptosis in vitro and shows anti tumor activity in vivo. | 1 |
| 10 | 39 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 6 | |
| 14 | 92 | |
| 15 | 94 | |
| 16 | 12 | |
| 17 | 70 | |
| 18 | 17 | |
| 19 | 342 | |
| 20 | 94 |
About Michelle Kuhne
Michelle Kuhne is a scholar working on Immunology, Oncology and Genetics, having authored 35 papers that have together received 2.2k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (12 papers), Immunotherapy and Immune Responses (10 papers) and CAR-T cell therapy research (8 papers). The work is most often cited by research in Immunology (1.1k citations), Oncology (788 citations) and Genetics (243 citations). Michelle Kuhne has collaborated with scholars based in United States, New Zealand and Germany. Frequent co-authors include Arthur Weiss, Gustav E. Lienhard, Deborah Yablonski, Tony Pawson, Theresa A. Kadlecek, Guosheng Feng, Alan J. Korman, Pina M. Cardarelli, Gregory Ku and M. S. Srinivasan. Their work appears in journals such as Science, Journal of Biological Chemistry and The Journal of Experimental Medicine.
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.