Stéphane Huet

3.3k citations
41 papers · 2.6k · h-index 21

Impact in

Papers in

    • TGF-β signaling in diseases 6
    • Peroxisome Proliferator-Activated Receptors 4
    • T-cell and B-cell Immunology 12
    • Immune Cell Function and Interaction 10

Stéphane Huet

41 papers receiving 2.5k citations

Peers

Stéphane Huet
Comparison fields: 5 of 109
  • Hepatology 453
  • Immunology and Allergy 254
  • Immunology 598
  • Epidemiology 636
  • Molecular Biology 1.1k
Replace Hideji Nakamura with:
Hideji Nakamura Japan
Jean‐François Mosnier France
Véronique Duchatelle France
Naoya Ikeda Japan
Rosie Z. Yu United States
Antonietta D’Errico Italy
Simi Ali United Kingdom
ST Cheung Hong Kong
Laura Amicone Italy
Jun Itakura Japan
Stéphane Huet relative to Hideji Nakamura Japan Hideji Nakamura's profile →
Citations per field
00.5×4.3×
Hideji Nakamura · 1×
Citations per year

Countries citing papers authored by Stéphane Huet

Since Specialization
Citations

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

Fields of papers citing papers by Stéphane Huet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001446
2 1989300
3 1999289
4 2004166
5 1999158
6 2005143
7 2010106
8 198696
9 198993
10 199092
11 200686
12 198975
13 200969
14 200964
15 199255
16 200732
17 199129
18 200828
19 199026
20 200625

About Stéphane Huet

Stéphane Huet is a scholar working on Molecular Biology, Immunology, Oncology, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 41 papers that have together received 2.6k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (12 papers), Immune Cell Function and Interaction (10 papers), TGF-β signaling in diseases (6 papers), Topic Modeling (6 papers), Natural Language Processing Techniques (4 papers), Speech and dialogue systems (4 papers), Peroxisome Proliferator-Activated Receptors (4 papers) and Monoclonal and Polyclonal Antibodies Research (4 papers). The work is most often cited by research in Hepatology (453 citations), Immunology and Allergy (254 citations), Immunology (598 citations), Epidemiology (636 citations) and Molecular Biology (1.1k citations). Stéphane Huet has collaborated with scholars based in France, United Kingdom and United States. Frequent co-authors include Jean‐Michel Gauthier, Hervé Groux, Anne‐Charlotte de Gouville, H. Valentin, Michel Vidaud, Delphine Dargère, Nathalie Bâ, Valérie Paradis, Pierre Bédossa and Anne Bernard. Their work appears in journals such as The Journal of Immunology, Bioorganic & Medicinal Chemistry Letters, Journal of Medicinal Chemistry, Hepatology and Blood.

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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