Amélie Perron

1.5k citations
23 papers · 1.2k indexed · h-index 18
Topics
Neuropeptides and Animal Physiology (9 papers)Neuroscience and Neural Engineering (8 papers)Receptor Mechanisms and Signaling (8 papers)
Partner nations
JapanCanadaFrance

In The Last Decade

Amélie Perron

23 papers receiving 1.2k citations

Peers

Amélie Perron
Comparison fields: 5 of 83
  • Cellular and Molecular Neuroscience 957
  • Molecular Biology 589
  • Cognitive Neuroscience 326
  • Biophysics 172
  • Physiology 95
Replace Aaron Marley with:
Aaron Marley United States
Jingheng Zhou United States
Hiroko Bannai Japan
Marie‐Josée Bourque Canada
Gerard Joey Broussard United States
Corey Smith United States
Nikolai M. Soldatov United States
Attila Kaszás Hungary
Hiroki Mutoh Japan
Marco Canepari France
Amélie Perron relative to Aaron Marley United States Aaron Marley's profile →
Citations per field
00.5×1.5×1.8×
Aaron Marley · 1×
Citations per year

Countries citing papers authored by Amélie Perron

Since Specialization
Citations

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

Fields of papers citing papers by Amélie Perron

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amélie Perron

This figure shows the co-authorship network connecting the top 25 collaborators of Amélie Perron. A scholar is included among the top collaborators of Amélie Perron 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 Amélie Perron. Amélie Perron 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 1
2 7
3 24
4 13
5 21
6 41
7 17
8 201
9 52
10 74
11 63
12 60
13 23
14 12
15 27
16 65
17 46
18 99
19 21
20 30

About Amélie Perron

Amélie Perron is a scholar working on Cellular and Molecular Neuroscience, Biophysics and Reproductive Medicine, having authored 23 papers that have together received 1.2k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (9 papers), Neuroscience and Neural Engineering (8 papers) and Receptor Mechanisms and Signaling (8 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (957 citations), Biophysics (172 citations) and Cognitive Neuroscience (326 citations). Amélie Perron has collaborated with scholars based in Japan, Canada and France. Frequent co-authors include Hiroki Mutoh, Thomas Knöpfel, Walther Akemann, Philippe Sarret, Alain Beaudet, Thomas Stroh, Yuka Iwamoto, Jean Rossier, Yun Kyung Park and Thomas Launey. Their work appears in journals such as Journal of the American Chemical Society, 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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