Jon M. Huibregtse
- Oncology top 0.2%
- Cancer-related Molecular Pathways 29
- Epidemiology top 0.2%
- Cervical Cancer and HPV Research 16
- Molecular Biology top 0.5%
- Ubiquitin and proteasome pathways 38
- Genomics and Chromatin Dynamics 7
- RNA modifications and cancer 7
- Immunology top 0.5%
- interferon and immune responses 12
- Cell Biology top 0.5%
- Endoplasmic Reticulum Stress and Disease 7
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- Virus-based gene therapy research 11
- Co-authors
- Martin ScheffnerPeter M. HowleyBruce A. WernessArnold J. LevineRichard D. VierstraSylvie BeaudenonUlrike A. NuberShunsuke Nakagawa
- Journals
- Molecular and Cellular Biology (13 papers)Journal of Biological Chemistry (10 papers)Proceedings of the National Academy of Sciences (6 papers)
- Partner nations
- United StatesGermanyJapan
In The Last Decade
Jon M. Huibregtse
84 papers receiving 14.5k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Oncology 5.7k
- Epidemiology 4.8k
- Molecular Biology 8.9k
- Immunology 2.5k
- Cell Biology 1.5k
Countries citing papers authored by Jon M. Huibregtse
This map shows the geographic impact of Jon M. Huibregtse'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 Jon M. Huibregtse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jon M. Huibregtse more than expected).
Fields of papers citing papers by Jon M. Huibregtse
This network shows the impact of papers produced by Jon M. Huibregtse. 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 Jon M. Huibregtse. The network helps show where Jon M. Huibregtse may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jon M. Huibregtse, 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 | 2024 | 3 | |
| 2 | 2024 | 5 | |
| 3 | 2021 | 33 | |
| 4 | 2020 | 55 | |
| 5 | 2020 | 62 | |
| 6 | 2018 | 9 | |
| 7 | 2014 | 23 | |
| 8 | 2013 | 133 | |
| 9 | 2010 | 274 | |
| 10 | 2007 | 115 | |
| 11 | 2005 | 128 | |
| 12 | 2004 | 87 | |
| 13 | 2001 | 46 | |
| 14 | 1999 | 149 | |
| 15 | 1998 | 213 | |
| 16 | 1997 | 100 | |
| 17 | Protein ubiquitination involving an E1–E2–E3 enzyme ubiquitin thioester cascadebreakdown → | 1995 | 814 |
| 18 | 1993 | 179 | |
| 19 | 1991 | 37 | |
| 20 | 1987 | 16 |
About Jon M. Huibregtse
Jon M. Huibregtse is a scholar working on Oncology, Molecular Biology and Genetics, having authored 85 papers that have together received 14.7k indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (38 papers), Cancer-related Molecular Pathways (29 papers), Cervical Cancer and HPV Research (16 papers), interferon and immune responses (12 papers), Virus-based gene therapy research (11 papers), Genomics and Chromatin Dynamics (7 papers), Endoplasmic Reticulum Stress and Disease (7 papers) and RNA modifications and cancer (7 papers). The work is most often cited by research in Oncology (5.7k citations), Epidemiology (4.8k citations) and Molecular Biology (8.9k citations). Jon M. Huibregtse has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Martin Scheffner, Peter M. Howley, Bruce A. Werness, Arnold J. Levine, Richard D. Vierstra, Sylvie Beaudenon, Ulrike A. Nuber, Shunsuke Nakagawa, Guangli Wang and Robert M. Krug. Their work appears in journals such as Molecular and Cellular Biology, Journal of Biological Chemistry, Proceedings of the National Academy of Sciences, Methods in enzymology on CD-ROM/Methods in enzymology and Molecular Cell.
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.