Philippe Vayer

29 papers receiving 1.5k citations

Philippe Vayer's Hit Papers

Drug discovery and development: introduction to the general public and patient groups 2023 · 125 citations
1250+1+2Years since publication4080120

Peers

Philippe Vayer
Comparison fields: 5 of 123
  • Toxicology 300
  • Computational Theory and Mathematics 482
  • Cellular and Molecular Neuroscience 461
  • Biological Psychiatry 32
  • Pharmacology 116
Replace Joaquín M. Campos Rosa with:
Joaquín M. Campos Rosa Spain
Patrick Dallemagne France
Anabella Villalobos United States
Angeliki P. Kourounakis Greece
Zhe‐Shan Quan China
Izet M. Kapetanović United States
Henryk Marona Poland
Péter Mátyus Hungary
Katarina Nikolić Serbia
Gerd Dannhardt Germany
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Citations per year

Countries citing papers authored by Philippe Vayer

Since Specialization
Citations

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

Fields of papers citing papers by Philippe Vayer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011247
2 2008170
3 1987158
4 1990134
5
Drug discovery and development: introduction to the general public and patient groups
Hit paper breakdown →
2023125
6 201773
7 198572
8 198864
9 198562
10 201356
11 201549
12 198944
13 201236
14 201233
15 198733
16 201530
17 201528
18 201226
19 198524
20 198718

About Philippe Vayer

Philippe Vayer is a scholar working on Computational Theory and Mathematics, Molecular Biology, Spectroscopy, Cellular and Molecular Neuroscience and Pharmacology, having authored 29 papers that have together received 1.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (11 papers), Analytical Chemistry and Chromatography (8 papers), Neuroscience and Neuropharmacology Research (7 papers), Pharmacogenetics and Drug Metabolism (6 papers), Metabolomics and Mass Spectrometry Studies (5 papers), Biochemical effects in animals (5 papers), Neurotransmitter Receptor Influence on Behavior (3 papers) and GABA and Rice Research (2 papers). The work is most often cited by research in Toxicology (300 citations), Computational Theory and Mathematics (482 citations), Cellular and Molecular Neuroscience (461 citations), Biological Psychiatry (32 citations) and Pharmacology (116 citations). Philippe Vayer has collaborated with scholars based in France, United States and Italy. Frequent co-authors include Michel Maître, Paul Mandel, Bruno O. Villoutreix, Maria A. Miteva, Gautier Moroy, Virginie Martiny, Serge Gobaille, Alban Arrault, Gilles Marcou and Alexandre Varnek. Their work appears in journals such as Molecular Informatics, Journal of Neurochemistry, Life Sciences, Bioinformatics and Metabolomics.

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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