Peter Haebel
Impact in
- Molecular Biology top 10%
- RNA and protein synthesis mechanisms
- Protein Structure and Dynamics
- RNA modifications and cancer
- Redox biology and oxidative stress
- Viral Infectious Diseases and Gene Expression in Insects
- Cell Biology top 10%
- Endoplasmic Reticulum Stress and Disease
Papers in
-
- RNA modifications and cancer 3
- Viral Infectious Diseases and Gene Expression in Insects 3
- Signaling Pathways in Disease 2
-
- Neuropeptides and Animal Physiology 4
- Co-authors
- Peter Metcalf (7 shared papers)Sascha Gutmann (5 shared papers)Nenad Ban (3 shared papers)Edward N. Baker (2 shared papers)Vladimir Rybin (1 shared paper)Anneli Törrönen (1 shared paper)Andrew A. McCarthy (1 shared paper)Keiko Ikeda (3 shared papers)
- Journals
- Molecular Metabolism (3 papers)Nature (2 papers)Journal of Chemical Information and Modeling (2 papers)Proceedings of the National Academy of Sciences (2 papers)European Journal of Medicinal Chemistry (1 paper)
- Partner nations
- GermanyNew ZealandSwitzerland
In The Last Decade
Peter Haebel
23 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 95
- Molecular Biology 832
- Cell Biology 191
- Genetics 164
- Materials Chemistry 236
- Structural Biology 7
Countries citing papers authored by Peter Haebel
This map shows the geographic impact of Peter Haebel'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 Haebel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Haebel more than expected).
Fields of papers citing papers by Peter Haebel
This network shows the impact of papers produced by Peter Haebel. 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 Haebel. The network helps show where Peter Haebel may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Haebel, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2000 | 206 | |
| 2 | 2007 | 161 | |
| 3 | 2003 | 103 | |
| 4 | 2004 | 101 | |
| 5 | 2002 | 101 | |
| 6 | 2022 | 81 | |
| 7 | 2009 | 62 | |
| 8 | 2012 | 43 | |
| 9 | 2004 | 42 | |
| 10 | 2005 | 33 | |
| 11 | 2001 | 30 | |
| 12 | 2008 | 28 | |
| 13 | 2007 | 21 | |
| 14 | 2001 | 17 | |
| 15 | 2004 | 15 | |
| 16 | 2004 | 15 | |
| 17 | 2006 | 14 | |
| 18 | 2001 | 11 | |
| 19 | 2021 | 10 | |
| 20 | 2022 | 10 |
About Peter Haebel
Peter Haebel is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Endocrinology, Diabetes and Metabolism, Cell Biology and Genetics, having authored 24 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (4 papers), Endoplasmic Reticulum Stress and Disease (4 papers), Diabetes Treatment and Management (4 papers), Enzyme Structure and Function (4 papers), RNA modifications and cancer (3 papers), Viral Infectious Diseases and Gene Expression in Insects (3 papers), Signaling Pathways in Disease (2 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Molecular Biology (832 citations), Cell Biology (191 citations), Genetics (164 citations), Materials Chemistry (236 citations) and Structural Biology (7 citations). Peter Haebel has collaborated with scholars based in Germany, New Zealand and Switzerland. Frequent co-authors include Peter Metcalf, Sascha Gutmann, Nenad Ban, Edward N. Baker, Vladimir Rybin, Anneli Törrönen, Andrew A. McCarthy, Keiko Ikeda, Fasséli Coulibaly and Hajime Mori. Their work appears in journals such as Molecular Metabolism, Nature, Journal of Chemical Information and Modeling, Proceedings of the National Academy of Sciences and European Journal of Medicinal Chemistry.
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.