Gaël Barthet

1.0k citations
25 papers · 748 · h-index 16

Impact in

Papers in

Gaël Barthet

24 papers receiving 745 citations

Peers

Gaël Barthet
Comparison fields: 5 of 71
  • Cellular and Molecular Neuroscience 381
  • Cell Biology 135
  • Neurology 68
  • Physiology 209
  • Molecular Biology 467
Replace Akio Sumioka with:
Akio Sumioka Japan
Guilian Tian United States
Heming Zhu United States
Karin Schmuck Switzerland
Alexander Wirth Germany
José Aguilera Spain
Petar Marinković Germany
Kristel M. Vennekens Belgium
Yu‐Fung Lin United States
Yilin Tai China
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Citations per field
00.5×1.6×
Akio Sumioka · 1×
Citations per year

Countries citing papers authored by Gaël Barthet

Since Specialization
Citations

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

Fields of papers citing papers by Gaël Barthet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Gaël Barthet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gaël Barthet Line = papers co-authored together Gaël Barthet links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004118
2 200766
3 201161
4 200960
5 200546
6 200545
7 202045
8 201840
9 201235
10 201233
11 201127
12 200825
13 202224
14 201623
15 201921
16 201121
17 202115
18 201910
19 20229
20 20209

About Gaël Barthet

Gaël Barthet is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Physiology, Cell Biology and Cognitive Neuroscience, having authored 25 papers that have together received 748 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (15 papers), Alzheimer's disease research and treatments (11 papers), Receptor Mechanisms and Signaling (6 papers), Hippo pathway signaling and YAP/TAZ (4 papers), Cellular transport and secretion (4 papers), Memory and Neural Mechanisms (3 papers), Biochemical Analysis and Sensing Techniques (2 papers) and Wnt/β-catenin signaling in development and cancer (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (381 citations), Cell Biology (135 citations), Neurology (68 citations), Physiology (209 citations) and Molecular Biology (467 citations). Gaël Barthet has collaborated with scholars based in France, United States and Sweden. Frequent co-authors include Aline Dumuis, Christophe Mulle, Sylvie Claeysen, Florence Gaven, Anastasios Georgakopoulos, Nikolaos K. Robakis, Joël Bockaert, Lucie P. Pellissier, Michèle Sebben and Philippe Marin. Their work appears in journals such as Journal of Biological Chemistry, Progress in Neurobiology, Neurobiology of Aging, The FASEB Journal and ACS Chemical 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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