Hans‐Georg Güllner
- Molecular Biology
- Cellular and Molecular Neuroscience
- Pharmacology
- Endocrinology, Diabetes and Metabolism
- Physiology
- Co-authors
- Frederic C. BartterJohn R. GillRainer DüsingWilliam A. PettingerWendell E. NicholsonMarian S. KafkaDavid N. OrthHaruaki Yajima
- Topics
- Receptor Mechanisms and Signaling (8 papers)Neuropeptides and Animal Physiology (7 papers)Electrolyte and hormonal disorders (6 papers)
- Journals
- NatureThe Journal of Clinical Endocrinology & MetabolismBiochemical and Biophysical Research Communications
- Partner nations
- United StatesJapan
In The Last Decade
Hans‐Georg Güllner
23 papers receiving 258 citations
Peers
Comparison fields: 5 of 54
- Molecular Biology 106
- Cellular and Molecular Neuroscience 73
- Pharmacology 64
- Endocrinology, Diabetes and Metabolism 64
- Physiology 55
Countries citing papers authored by Hans‐Georg Güllner
This map shows the geographic impact of Hans‐Georg Güllner'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 Hans‐Georg Güllner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hans‐Georg Güllner more than expected).
Fields of papers citing papers by Hans‐Georg Güllner
This network shows the impact of papers produced by Hans‐Georg Güllner. 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 Hans‐Georg Güllner. The network helps show where Hans‐Georg Güllner may publish in the future.
Co-authorship network of co-authors of Hans‐Georg Güllner
This figure shows the co-authorship network connecting the top 25 collaborators of Hans‐Georg Güllner. A scholar is included among the top collaborators of Hans‐Georg Güllner based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hans‐Georg Güllner. Hans‐Georg Güllner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 0 | |
| 3 | 8 | |
| 4 | 9 | |
| 5 | 20 | |
| 6 | 25 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 5 | |
| 10 | 7 | |
| 11 | 8 | |
| 12 | 20 | |
| 13 | 15 | |
| 14 | 36 | |
| 15 | 9 | |
| 16 | 11 | |
| 17 | 11 | |
| 18 | 3 | |
| 19 | 25 | |
| 20 | 2 |
About Hans‐Georg Güllner
Hans‐Georg Güllner is a scholar working on Cellular and Molecular Neuroscience, Nephrology and Endocrinology, Diabetes and Metabolism, having authored 24 papers that have together received 288 indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (8 papers), Neuropeptides and Animal Physiology (7 papers) and Electrolyte and hormonal disorders (6 papers). The work is most often cited by research in Biochemistry (42 citations), Behavioral Neuroscience (17 citations) and Cellular and Molecular Neuroscience (73 citations). Hans‐Georg Güllner has collaborated with scholars based in United States and Japan. Frequent co-authors include Frederic C. Bartter, John R. Gill, Rainer Düsing, William A. Pettinger, Wendell E. Nicholson, Marian S. Kafka, David N. Orth, Haruaki Yajima, Charles Lake and John F. Tallman. Their work appears in journals such as Nature, The Journal of Clinical Endocrinology & Metabolism and Biochemical and Biophysical Research 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.