H. Gut
Impact in
- Aging top 5%
- Molecular Biology top 5%
- DNA Repair Mechanisms
- Ubiquitin and proteasome pathways
- Histone Deacetylase Inhibitors Research
- Protein Degradation and Inhibitors
- CRISPR and Genetic Engineering
- RNA Research and Splicing
- Genomics and Chromatin Dynamics
Papers in
-
- DNA Repair Mechanisms 5
- RNA Research and Splicing 5
- Fungal and yeast genetics research 3
- RNA and protein synthesis mechanisms 3
- Glycosylation and Glycoproteins Research 2
- Genetics 4
- Co-authors
- J.J. Keusch (10 shared papers)Daniel Heß (3 shared papers)Guido Capitani (5 shared papers)Markus G. Grütter (5 shared papers)Martin Walsh (3 shared papers)Mahamadou Faty (2 shared papers)Andrea Scrima (2 shared papers)Nicolas H. Thomä (2 shared papers)
- Journals
- The EMBO Journal (4 papers)Molecular Cell (2 papers)Cell (2 papers)Journal of Molecular Biology (2 papers)Nature Communications (1 paper)
- Partner nations
- SwitzerlandUnited StatesGermany
In The Last Decade
H. Gut
26 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 94
- Aging 61
- Molecular Biology 1.3k
- Oncology 243
- Biochemistry 62
- Cell Biology 111
Countries citing papers authored by H. Gut
This map shows the geographic impact of H. Gut'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 H. Gut with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites H. Gut more than expected).
Fields of papers citing papers by H. Gut
This network shows the impact of papers produced by H. Gut. 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 H. Gut. The network helps show where H. Gut may publish in the future.
Co-authors
The 25 scholars most cited alongside H. Gut, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 366 | |
| 2 | 2016 | 240 | |
| 3 | 2014 | 130 | |
| 4 | 2006 | 90 | |
| 5 | 2013 | 79 | |
| 6 | 2009 | 75 | |
| 7 | 2008 | 63 | |
| 8 | 2012 | 58 | |
| 9 | 2014 | 58 | |
| 10 | 2019 | 58 | |
| 11 | 2016 | 51 | |
| 12 | 2012 | 50 | |
| 13 | 2017 | 50 | |
| 14 | 2011 | 50 | |
| 15 | 2002 | 45 | |
| 16 | 2015 | 43 | |
| 17 | 2018 | 36 | |
| 18 | 2016 | 32 | |
| 19 | 2018 | 26 | |
| 20 | 2013 | 23 |
About H. Gut
H. Gut is a scholar working on Molecular Biology, Genetics, Immunology, Materials Chemistry and Epidemiology, having authored 26 papers that have together received 1.7k indexed citations. Recurring topics across this work include DNA Repair Mechanisms (5 papers), RNA Research and Splicing (5 papers), Enzyme Structure and Function (4 papers), Fungal and yeast genetics research (3 papers), RNA and protein synthesis mechanisms (3 papers), Glycosylation and Glycoproteins Research (2 papers), Pneumonia and Respiratory Infections (2 papers) and Genetics, Aging, and Longevity in Model Organisms (2 papers). The work is most often cited by research in Aging (61 citations), Molecular Biology (1.3k citations), Oncology (243 citations), Biochemistry (62 citations) and Cell Biology (111 citations). H. Gut has collaborated with scholars based in Switzerland, United States and Germany. Frequent co-authors include J.J. Keusch, Daniel Heß, Guido Capitani, Markus G. Grütter, Martin Walsh, Mahamadou Faty, Andrea Scrima, Nicolas H. Thomä, Y. Miyake and Kaoru Sugasawa. Their work appears in journals such as The EMBO Journal, Molecular Cell, Cell, Journal of Molecular Biology and Nature Communications.
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.