Philippe Chavatte

3.0k citations
85 papers · 2.5k indexed · h-index 26

Impact in

Papers in

Philippe Chavatte

85 papers receiving 2.5k citations

Peers

Philippe Chavatte
Comparison fields: 5 of 121
  • Pharmacology 504
  • Endocrine and Autonomic Systems 197
  • Organic Chemistry 707
  • Molecular Biology 1.2k
  • Cellular and Molecular Neuroscience 280
Replace William J. Greenlee with:
William J. Greenlee United States
Valeria Pittalà Italy
Michael A. Patane United States
Emidio Camaioni Italy
Heinz H. Pertz Germany
Giuseppe Romeo Italy
Loredana Salerno Italy
Paolo Grieco Italy
Simona Bertoni Italy
Vikramdeep Monga India
Philippe Chavatte relative to William J. Greenlee United States William J. Greenlee's profile →
Citations per field
00.5×1.7×
William J. Greenlee · 1×
Citations per year

Countries citing papers authored by Philippe Chavatte

Since Specialization
Citations

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

Fields of papers citing papers by Philippe Chavatte

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Philippe Chavatte, 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 Philippe Chavatte Line = papers co-authored together Philippe Chavatte links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20217
2 201816
3 20167
4 201521
5 201428
6 201219
7 201231
8 201117
9 201138
10 201113
11 2010161
12 201023
13 200922
14 200842
15 200815
16 200612
17 200616
18 20057
19 200114
20 200014

About Philippe Chavatte

Philippe Chavatte is a scholar working on Pharmacology, Biological Psychiatry, Endocrine and Autonomic Systems, Physiology and Cellular and Molecular Neuroscience, having authored 85 papers that have together received 2.5k indexed citations. Recurring topics across this work include Pharmacological Receptor Mechanisms and Effects (15 papers), Cannabis and Cannabinoid Research (14 papers), Receptor Mechanisms and Signaling (14 papers), Inflammatory mediators and NSAID effects (10 papers), Computational Drug Discovery Methods (9 papers), Synthesis and biological activity (8 papers), Circadian rhythm and melatonin (8 papers) and Neurotransmitter Receptor Influence on Behavior (7 papers). The work is most often cited by research in Pharmacology (504 citations), Endocrine and Autonomic Systems (197 citations), Organic Chemistry (707 citations), Molecular Biology (1.2k citations) and Cellular and Molecular Neuroscience (280 citations). Philippe Chavatte has collaborated with scholars based in France, Belgium and United Kingdom. Frequent co-authors include Amaury Farce, Pierre Desreumaux, Régis Millet, Nicolas Renault, Saı̈d Yous, Daniel Lesieur, Christophe Marot, Pascal Berthelot, Béatrice Desvergne and Natascha Leleu‐Chavain. Their work appears in journals such as Journal of Medicinal Chemistry, Journal of Enzyme Inhibition and Medicinal Chemistry, European Journal of Medicinal Chemistry, Bioorganic & Medicinal Chemistry Letters and Bioorganic & Medicinal Chemistry.

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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