Florence Oury-Donat
- Cellular and Molecular Neuroscience top 2%
- Molecular Biology top 10%
- Pharmacology top 1%
- Physiology top 5%
- Endocrinology, Diabetes and Metabolism top 5%
- Co-authors
- Philippe SoubriéG. Le FurMagali Gary‐BoboM. BensaïdJ.P. MaffrandGérard Le FurB. ScattonR. Steinberg
- Topics
- Receptor Mechanisms and Signaling (16 papers)Neuropeptides and Animal Physiology (11 papers)Neuroscience and Neuropharmacology Research (8 papers)
- Journals
- HepatologyFEBS LettersNeuroscience
- Partner nations
- FranceUnited StatesGermany
In The Last Decade
Florence Oury-Donat
25 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 81
- Cellular and Molecular Neuroscience 973
- Molecular Biology 841
- Pharmacology 835
- Physiology 426
- Endocrinology, Diabetes and Metabolism 412
Countries citing papers authored by Florence Oury-Donat
This map shows the geographic impact of Florence Oury-Donat'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 Florence Oury-Donat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Florence Oury-Donat more than expected).
Fields of papers citing papers by Florence Oury-Donat
This network shows the impact of papers produced by Florence Oury-Donat. 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 Florence Oury-Donat. The network helps show where Florence Oury-Donat may publish in the future.
Co-authorship network of co-authors of Florence Oury-Donat
This figure shows the co-authorship network connecting the top 25 collaborators of Florence Oury-Donat. A scholar is included among the top collaborators of Florence Oury-Donat 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 Florence Oury-Donat. Florence Oury-Donat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 33 | |
| 2 | 49 | |
| 3 | 243 | |
| 4 | 11 | |
| 5 | 207 | |
| 6 | 135 | |
| 7 | 18 | |
| 8 | 499 | |
| 9 | 26 | |
| 10 | 16 | |
| 11 | 13 | |
| 12 | 26 | |
| 13 | 35 | |
| 14 | 112 | |
| 15 | 36 | |
| 16 | 93 | |
| 17 | 24 | |
| 18 | 27 | |
| 19 | 27 | |
| 20 | 8 |
About Florence Oury-Donat
Florence Oury-Donat is a scholar working on Cellular and Molecular Neuroscience, Behavioral Neuroscience and Endocrine and Autonomic Systems, having authored 25 papers that have together received 2.0k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (16 papers), Neuropeptides and Animal Physiology (11 papers) and Neuroscience and Neuropharmacology Research (8 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (973 citations), Pharmacology (835 citations) and Endocrine and Autonomic Systems (211 citations). Florence Oury-Donat has collaborated with scholars based in France, United States and Germany. Frequent co-authors include Philippe Soubrié, G. Le Fur, Magali Gary‐Bobo, M. Bensaïd, J.P. Maffrand, Gérard Le Fur, B. Scatton, R. Steinberg, Mohammed Bensaïd and Jean Pierre Maffrand. Their work appears in journals such as Hepatology, FEBS Letters and Neuroscience.
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.