Peter Thorn
Impact in
- Physiology top 0.5%
- Calcium signaling and nucleotide metabolism
- Sensory Systems top 1%
- Ion Channels and Receptors
Papers in ⓘ
- Physiology 11
- Erythrocyte Function and Pathophysiology 10
- Co-authors
- Ole H. Petersen (12 shared papers)D.V. Gallacher (6 shared papers)Alison M. Lawrie (5 shared papers)Peter Smith (4 shared papers)J. F. Kidd (8 shared papers)Kevin E. Fogarty (8 shared papers)Herbert Y. Gaisano (10 shared papers)Chengzhong Yu (4 shared papers)
- Journals
- The Journal of Physiology (12 papers)Journal of Biological Chemistry (10 papers)Pflügers Archiv - European Journal of Physiology (7 papers)Diabetologia (6 papers)Cell Calcium (6 papers)
- Partner nations
- AustraliaUnited KingdomUnited States
In The Last Decade
Peter Thorn
110 papers receiving 3.8k citations
Peers
Comparison fields: 5 of 130
- Physiology 434
- Sensory Systems 398
- Cell Biology 863
- Cellular and Molecular Neuroscience 716
- Molecular Biology 2.2k
Countries citing papers authored by Peter Thorn
This map shows the geographic impact of Peter Thorn'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 Thorn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Thorn more than expected).
Fields of papers citing papers by Peter Thorn
This network shows the impact of papers produced by Peter Thorn. 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 Thorn. The network helps show where Peter Thorn may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Thorn, 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 110 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1993 | 432 | |
| 2 | 2012 | 287 | |
| 3 | 1994 | 182 | |
| 4 | 2002 | 163 | |
| 5 | 2004 | 93 | |
| 6 | 2000 | 87 | |
| 7 | 1992 | 80 | |
| 8 | 2014 | 75 | |
| 9 | 2016 | 74 | |
| 10 | 2012 | 74 | |
| 11 | 2001 | 73 | |
| 12 | 1992 | 66 | |
| 13 | 2011 | 64 | |
| 14 | 2018 | 63 | |
| 15 | 1998 | 53 | |
| 16 | 2019 | 52 | |
| 17 | 2007 | 52 | |
| 18 | 2004 | 50 | |
| 19 | 2018 | 49 | |
| 20 | 1996 | 49 |
About Peter Thorn
Peter Thorn is a scholar working on Physiology, Sensory Systems, Cell Biology, Cellular and Molecular Neuroscience and Surgery, having authored 110 papers that have together received 3.8k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (48 papers), Ion channel regulation and function (35 papers), Cellular transport and secretion (24 papers), Diabetes and associated disorders (21 papers), Metabolism, Diabetes, and Cancer (14 papers), Neuroscience and Neuropharmacology Research (13 papers), Lipid Membrane Structure and Behavior (11 papers) and Erythrocyte Function and Pathophysiology (10 papers). The work is most often cited by research in Physiology (434 citations), Sensory Systems (398 citations), Cell Biology (863 citations), Cellular and Molecular Neuroscience (716 citations) and Molecular Biology (2.2k citations). Peter Thorn has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Ole H. Petersen, D.V. Gallacher, Alison M. Lawrie, Peter Smith, J. F. Kidd, Kevin E. Fogarty, Herbert Y. Gaisano, Chengzhong Yu, Meihua Yu and Wenyi Gu. Their work appears in journals such as The Journal of Physiology, Journal of Biological Chemistry, Pflügers Archiv - European Journal of Physiology, Diabetologia and Cell Calcium.
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.