Peter Kühn
- Cellular and Molecular Neuroscience top 0.5%
- Molecular Biology top 0.5%
- Single-cell and spatial transcriptomics 19
- Protein Structure and Dynamics 13
- Oncology top 0.5%
- Cancer Cells and Metastasis 54
- Cancer Research top 0.5%
- Cancer Genomics and Diagnostics 65
- Infectious Diseases top 0.5%
- SARS-CoV-2 and COVID-19 Research 14
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- Ocular Oncology and Treatments 18
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- Enzyme Structure and Function 18
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- Prostate Cancer Treatment and Research 17
- Co-authors
- Raymond C. StevensVadim CherezovMichael A. HansonHee‐Jung ChoiBrian K. KobilkaSøren G. F. RasmussenWilliam I. WeisFoon Sun Thian
- Journals
- Journal of Clinical Oncology (20 papers)Journal of Virology (13 papers)Cancer Research (11 papers)
- Partner nations
- United StatesUnited KingdomFrance
In The Last Decade
Peter Kühn
233 papers receiving 15.6k citations
Hit Papers
Peers
Comparison fields: 5 of 195
- Cellular and Molecular Neuroscience 2.8k
- Molecular Biology 9.5k
- Oncology 3.5k
- Cancer Research 1.8k
- Infectious Diseases 1.7k
Countries citing papers authored by Peter Kühn
This map shows the geographic impact of Peter Kühn'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 Peter Kühn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Kühn more than expected).
Fields of papers citing papers by Peter Kühn
This network shows the impact of papers produced by Peter Kühn. 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 Peter Kühn. The network helps show where Peter Kühn may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Peter Kühn, 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 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 8 | |
| 4 | 2023 | 14 | |
| 5 | 2023 | 9 | |
| 6 | 2023 | 6 | |
| 7 | 2022 | 22 | |
| 8 | 2022 | 5 | |
| 9 | 2022 | 2 | |
| 10 | 2021 | 16 | |
| 11 | 2021 | 42 | |
| 12 | 2020 | 61 | |
| 13 | 2020 | 39 | |
| 14 | 2018 | 85 | |
| 15 | 2015 | 100 | |
| 16 | 2013 | 66 | |
| 17 | Crystal Structure of a Lipid G Protein–Coupled Receptorbreakdown → | 2012 | 544 |
| 18 | 2012 | 53 | |
| 19 | Structures of the CXCR4 Chemokine GPCR with Small-Molecule and Cyclic Peptide Antagonistsbreakdown → | 2010 | 1462 |
| 20 | High-Resolution Crystal Structure of an Engineered Human β 2 -Adrenergic G Protein–Coupled Receptorbreakdown → | 2007 | 2663 |
About Peter Kühn
Peter Kühn is a scholar working on Cancer Research, Oncology, Ophthalmology, Molecular Biology and Pulmonary and Respiratory Medicine, having authored 247 papers that have together received 16.0k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (65 papers), Cancer Cells and Metastasis (54 papers), Single-cell and spatial transcriptomics (19 papers), Ocular Oncology and Treatments (18 papers), Enzyme Structure and Function (18 papers), Prostate Cancer Treatment and Research (17 papers), SARS-CoV-2 and COVID-19 Research (14 papers) and Protein Structure and Dynamics (13 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (2.8k citations), Molecular Biology (9.5k citations), Oncology (3.5k citations), Cancer Research (1.8k citations) and Infectious Diseases (1.7k citations). Peter Kühn has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Raymond C. Stevens, Vadim Cherezov, Michael A. Hanson, Hee‐Jung Choi, Brian K. Kobilka, Søren G. F. Rasmussen, William I. Weis, Foon Sun Thian, Tong Sun Kobilka and Daniel M. Rosenbaum. Their work appears in journals such as Journal of Clinical Oncology, Journal of Virology, Cancer Research, Cancers 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.