Julien Royet

7.4k total citations · 3 hit papers
64 papers, 5.7k citations indexed

About

Julien Royet is a scholar working on Immunology, Insect Science and Cellular and Molecular Neuroscience. According to data from OpenAlex, Julien Royet has authored 64 papers receiving a total of 5.7k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Immunology, 39 papers in Insect Science and 23 papers in Cellular and Molecular Neuroscience. Recurrent topics in Julien Royet's work include Invertebrate Immune Response Mechanisms (43 papers), Insect symbiosis and bacterial influences (35 papers) and Neurobiology and Insect Physiology Research (21 papers). Julien Royet is often cited by papers focused on Invertebrate Immune Response Mechanisms (43 papers), Insect symbiosis and bacterial influences (35 papers) and Neurobiology and Insect Physiology Research (21 papers). Julien Royet collaborates with scholars based in France, United States and United Kingdom. Julien Royet's co-authors include Jules A. Hoffmann, Tatiana Michel, Roman Dziarski, Bernard Charroux, Jean‐Marc Reichhart, François Leulier, Robert Finkelstein, Dominique Ferrandon, Arnaud Defaye and Berra Erkoşar and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Julien Royet

64 papers receiving 5.6k citations

Hit Papers

Drosophila Toll is activated by Gram-positive bacteria th... 2001 2026 2009 2017 2001 2011 2002 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Julien Royet France 34 3.8k 3.0k 1.4k 1.4k 645 64 5.7k
Dominique Ferrandon France 31 4.5k 1.2× 3.6k 1.2× 2.1k 1.4× 1.4k 1.0× 743 1.2× 66 6.7k
François Leulier France 38 3.0k 0.8× 2.7k 0.9× 2.3k 1.6× 828 0.6× 439 0.7× 64 6.3k
Mika Rämet Finland 40 3.7k 1.0× 2.3k 0.8× 1.7k 1.2× 1.1k 0.8× 390 0.6× 121 6.7k
Marie Meister France 30 3.6k 0.9× 2.4k 0.8× 1.2k 0.8× 1.6k 1.2× 668 1.0× 43 4.6k
Shoichiro Kurata Japan 37 2.4k 0.6× 1.8k 0.6× 1.7k 1.2× 907 0.6× 627 1.0× 121 4.5k
Mickaël Poidevin France 29 2.3k 0.6× 2.0k 0.7× 1.7k 1.2× 1.1k 0.8× 213 0.3× 46 4.4k
Neal Silverman United States 50 5.3k 1.4× 3.2k 1.1× 3.8k 2.6× 1.4k 1.0× 745 1.2× 92 9.4k
Nicolas Buchon United States 35 3.5k 0.9× 3.5k 1.2× 1.6k 1.1× 1.4k 1.0× 148 0.2× 65 6.0k
Marie Lagueux France 29 2.1k 0.6× 2.0k 0.7× 1.1k 0.7× 1.6k 1.1× 703 1.1× 41 3.9k
Jean‐Marc Reichhart France 47 7.9k 2.1× 5.4k 1.8× 3.0k 2.1× 2.2k 1.6× 2.6k 4.0× 76 10.5k

Countries citing papers authored by Julien Royet

Since Specialization
Citations

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

Fields of papers citing papers by Julien Royet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julien Royet

This figure shows the co-authorship network connecting the top 25 collaborators of Julien Royet. A scholar is included among the top collaborators of Julien Royet 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 Julien Royet. Julien Royet 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
1.
Rifflet, Aline, et al.. (2024). Bacterial peptidoglycan serves as a critical modulator of the gut-immune-brain axis in Drosophila. Brain Behavior and Immunity. 119. 878–897. 5 indexed citations
2.
Manière, Gérard, Martine Berthelot‐Grosjean, Benjamin Gillet, et al.. (2024). Larval microbiota primes the Drosophila adult gustatory response. Nature Communications. 15(1). 1341–1341. 3 indexed citations
4.
Charroux, Bernard & Julien Royet. (2022). Gut-derived peptidoglycan remotely inhibits bacteria dependent activation of SREBP by Drosophila adipocytes. PLoS Genetics. 18(3). e1010098–e1010098. 10 indexed citations
6.
Charroux, Bernard, et al.. (2016). Bacteria sensing mechanisms in Drosophila gut: Local and systemic consequences. Developmental & Comparative Immunology. 64. 11–21. 30 indexed citations
7.
Costechareyre, Denis, et al.. (2015). Tissue-Specific Regulation of <b><i>Drosophila</i></b> NF-&#954;B Pathway Activation by Peptidoglycan Recognition Protein SC. Journal of Innate Immunity. 8(1). 67–80. 38 indexed citations
8.
Wayland, Matthew T., Arnaud Defaye, João Batista Teixeira da Rocha, et al.. (2014). Spotting the differences: Probing host/microbiota interactions with a dedicated software tool for the analysis of faecal outputs in Drosophila. Journal of Insect Physiology. 69. 126–135. 23 indexed citations
9.
Charroux, Bernard & Julien Royet. (2012). Gut-microbiota interactions in non-mammals: What can we learn from Drosophila?. Seminars in Immunology. 24(1). 17–24. 57 indexed citations
10.
Fabre, Alexandre, Bernard Charroux, Christine Martinez‐Vinson, et al.. (2012). SKIV2L Mutations Cause Syndromic Diarrhea, or Trichohepatoenteric Syndrome. The American Journal of Human Genetics. 90(4). 689–692. 106 indexed citations
11.
Tufi, Roberta, et al.. (2012). The Drosophila inner-membrane protein PMI controls cristae biogenesis and mitochondrial diameter. Journal of Cell Science. 126(Pt 3). 814–24. 18 indexed citations
12.
Storelli, Gilles, Arnaud Defaye, Berra Erkoşar, et al.. (2011). Lactobacillus plantarum Promotes Drosophila Systemic Growth by Modulating Hormonal Signals through TOR-Dependent Nutrient Sensing. Cell Metabolism. 14(3). 403–414. 586 indexed citations breakdown →
13.
Royet, Julien, Dipika Gupta, & Roman Dziarski. (2011). Peptidoglycan recognition proteins: modulators of the microbiome and inflammation. Nature reviews. Immunology. 11(12). 837–851. 293 indexed citations
14.
Vignal, Cécile, et al.. (2008). The Drosophila Peptidoglycan Recognition Protein PGRP-LF Blocks PGRP-LC and IMD/JNK Pathway Activation. Cell Host & Microbe. 3(5). 293–303. 131 indexed citations
15.
Royet, Julien & Roman Dziarski. (2007). Peptidoglycan recognition proteins: pleiotropic sensors and effectors of antimicrobial defences. Nature Reviews Microbiology. 5(4). 264–277. 311 indexed citations
16.
Vignal, Cécile, et al.. (2006). Downregulation of the Drosophila Immune Response by Peptidoglycan-Recognition Proteins SC1 and SC2. PLoS Pathogens. 2(2). e14–e14. 273 indexed citations
17.
Imler, Jean‐Luc, Dominique Ferrandon, Julien Royet, et al.. (2004). Toll-dependent and Toll-independent immune responses in <I>Drosophila</I>. Journal of Endotoxin Research. 10(4). 241–246. 27 indexed citations
18.
Royet, Julien. (2004). Drosophila melanogaster innate immunity: an emerging role for peptidoglycan recognition proteins in bacteria detection. Cellular and Molecular Life Sciences. 61(5). 537–546. 18 indexed citations
19.
Duvic, Bernard, et al.. (2002). Notch Signaling Controls Lineage Specification during Drosophila Larval Hematopoiesis. Current Biology. 12(22). 1923–1927. 110 indexed citations
20.
Michel, Tatiana, Jean‐Marc Reichhart, Jules A. Hoffmann, & Julien Royet. (2001). Drosophila Toll is activated by Gram-positive bacteria through a circulating peptidoglycan recognition protein. Nature. 414(6865). 756–759. 647 indexed citations breakdown →

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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