Ágnes Kenessey
- Molecular Biology top 10%
- Physiology top 5%
- Cellular and Molecular Neuroscience top 5%
- Endocrinology, Diabetes and Metabolism top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Co-authors
- Kaie OjamaaShu-Hui YenIrwin KleinShu‐Hui YenÁbel LajthaMiriam Banay‐SchwartzLi‐wen KoParimala Nacharaju
- Topics
- Neuropeptides and Animal Physiology (8 papers)Receptor Mechanisms and Signaling (8 papers)Neuroscience and Neuropharmacology Research (6 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryJournal of the American College of Cardiology
- Partner nations
- United StatesHungaryCanada
In The Last Decade
Ágnes Kenessey
43 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 96
- Molecular Biology 875
- Physiology 502
- Cellular and Molecular Neuroscience 456
- Endocrinology, Diabetes and Metabolism 305
- Cardiology and Cardiovascular Medicine 234
Countries citing papers authored by Ágnes Kenessey
This map shows the geographic impact of Ágnes Kenessey'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 Ágnes Kenessey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ágnes Kenessey more than expected).
Fields of papers citing papers by Ágnes Kenessey
This network shows the impact of papers produced by Ágnes Kenessey. 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 Ágnes Kenessey. The network helps show where Ágnes Kenessey may publish in the future.
Co-authorship network of co-authors of Ágnes Kenessey
This figure shows the co-authorship network connecting the top 25 collaborators of Ágnes Kenessey. A scholar is included among the top collaborators of Ágnes Kenessey 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 Ágnes Kenessey. Ágnes Kenessey 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 | 104 | |
| 3 | 8 | |
| 4 | 26 | |
| 5 | 173 | |
| 6 | 20 | |
| 7 | 70 | |
| 8 | 20 | |
| 9 | 57 | |
| 10 | 150 | |
| 11 | 34 | |
| 12 | 136 | |
| 13 | 57 | |
| 14 | 7 | |
| 15 | 26 | |
| 16 | 12 | |
| 17 | 56 | |
| 18 | Neuropharmacology of a new psychotropic 2,3-benzodiazepine. | 13 |
| 19 | 19 | |
| 20 | 34 |
About Ágnes Kenessey
Ágnes Kenessey is a scholar working on Cellular and Molecular Neuroscience, Animal Science and Zoology and Physiology, having authored 43 papers that have together received 1.7k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (8 papers), Receptor Mechanisms and Signaling (8 papers) and Neuroscience and Neuropharmacology Research (6 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (456 citations), Physiology (502 citations) and Endocrinology, Diabetes and Metabolism (305 citations). Ágnes Kenessey has collaborated with scholars based in United States, Hungary and Canada. Frequent co-authors include Kaie Ojamaa, Shu-Hui Yen, Irwin Klein, Shu‐Hui Yen, Ábel Lajtha, Miriam Banay‐Schwartz, Li‐wen Ko, Parimala Nacharaju, László Gráf and Rajesh Shenoy. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of the American College of Cardiology.
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.