Florence Gaven

1.9k citations
25 papers · 1.5k indexed · h-index 21
Topics
Receptor Mechanisms and Signaling (11 papers)Neuroscience and Neuropharmacology Research (9 papers)Cholinesterase and Neurodegenerative Diseases (6 papers)

In The Last Decade

Florence Gaven

24 papers receiving 1.5k citations

Peers

Florence Gaven
Comparison fields: 5 of 84
  • Cellular and Molecular Neuroscience 836
  • Molecular Biology 835
  • Pharmacology 331
  • Physiology 320
  • Computational Theory and Mathematics 190
Replace François Dauphin with:
François Dauphin France
Margaret M. Racke United States
Zipora Pittel Israel
David O. Calligaro United States
Jan Říčný Czechia
David A. Hosford United States
José Á. Morales-García Spain
Shogo Matsuyama Japan
Michael Rigby United Kingdom
Daniel Auld Canada
Florence Gaven relative to François Dauphin France François Dauphin's profile →
Citations per field
00.5×1.5×2.4×
François Dauphin · 1×
Citations per year

Countries citing papers authored by Florence Gaven

Since Specialization
Citations

This map shows the geographic impact of Florence Gaven'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 Gaven with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Florence Gaven more than expected).

Fields of papers citing papers by Florence Gaven

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Florence Gaven. 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 Gaven. The network helps show where Florence Gaven may publish in the future.

Co-authorship network of co-authors of Florence Gaven

This figure shows the co-authorship network connecting the top 25 collaborators of Florence Gaven. A scholar is included among the top collaborators of Florence Gaven 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 Gaven. Florence Gaven is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 27
3 48
4 53
5 21
6 75
7 1
8 73
9 6
10 134
11 61
12 60
13 52
14 66
15 45
16 46
17 2
18 85
19 33
20 166

About Florence Gaven

Florence Gaven is a scholar working on Cellular and Molecular Neuroscience, Pharmacology and Physiology, having authored 25 papers that have together received 1.5k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (11 papers), Neuroscience and Neuropharmacology Research (9 papers) and Cholinesterase and Neurodegenerative Diseases (6 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (836 citations), Biological Psychiatry (57 citations) and Pharmacology (331 citations). Florence Gaven has collaborated with scholars based in France, United States and Germany. Frequent co-authors include Joël Bockaert, Sylvie Claeysen, Philippe Marin, Aline Dumuis, Jean‐Philippe Pin, Sylvia Pietri, Marcel Culcasi, Mireille Lafon‐Cazal, Francine Acher and Gaël Barthet. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of 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.

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