Fabrice Benchetrit

683 total citations
10 papers, 556 citations indexed

About

Fabrice Benchetrit is a scholar working on Immunology, Oncology and Molecular Biology. According to data from OpenAlex, Fabrice Benchetrit has authored 10 papers receiving a total of 556 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Immunology, 4 papers in Oncology and 2 papers in Molecular Biology. Recurrent topics in Fabrice Benchetrit's work include Immunotherapy and Immune Responses (9 papers), Immune Cell Function and Interaction (6 papers) and Virus-based gene therapy research (2 papers). Fabrice Benchetrit is often cited by papers focused on Immunotherapy and Immune Responses (9 papers), Immune Cell Function and Interaction (6 papers) and Virus-based gene therapy research (2 papers). Fabrice Benchetrit collaborates with scholars based in Israel, France and United States. Fabrice Benchetrit's co-authors include Éric Tartour, Wolf H. Fridman, Nacilla Haicheur, Alain Gey, Catherine Sautès‐Fridman, Virginie Vives, François Fossiez, Guy Warnier, Hans J. Stauss and Yael Elbaz‐Alon and has published in prestigious journals such as Blood, The Journal of Immunology and PLoS ONE.

In The Last Decade

Fabrice Benchetrit

10 papers receiving 545 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fabrice Benchetrit Israel 8 409 288 101 45 44 10 556
Mathilde Allard Switzerland 16 536 1.3× 322 1.1× 146 1.4× 30 0.7× 61 1.4× 21 705
Andrew Medvec United States 8 455 1.1× 326 1.1× 134 1.3× 24 0.5× 87 2.0× 8 736
Flavia E. Popescu United States 8 536 1.3× 201 0.7× 173 1.7× 16 0.4× 55 1.3× 10 773
Anna K. Murray United Kingdom 14 226 0.6× 162 0.6× 171 1.7× 32 0.7× 50 1.1× 23 446
Erika J. Crosby United States 13 314 0.8× 256 0.9× 161 1.6× 61 1.4× 53 1.2× 24 573
Mara Valentini Italy 5 450 1.1× 379 1.3× 125 1.2× 10 0.2× 44 1.0× 5 643
Janelle A. Olson United States 6 753 1.8× 406 1.4× 96 1.0× 25 0.6× 57 1.3× 14 883
Renee Wu United States 9 726 1.8× 383 1.3× 194 1.9× 17 0.4× 43 1.0× 13 930
Deeksha Deep United States 7 464 1.1× 138 0.5× 204 2.0× 51 1.1× 40 0.9× 9 713
Mirjam E. Hoekstra Netherlands 9 726 1.8× 217 0.8× 135 1.3× 19 0.4× 103 2.3× 9 884

Countries citing papers authored by Fabrice Benchetrit

Since Specialization
Citations

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

Fields of papers citing papers by Fabrice Benchetrit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fabrice Benchetrit

This figure shows the co-authorship network connecting the top 25 collaborators of Fabrice Benchetrit. A scholar is included among the top collaborators of Fabrice Benchetrit 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 Fabrice Benchetrit. Fabrice Benchetrit is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
Thomas, Sharyn, Dan Blat, Galit Denkberg, et al.. (2014). Functional Comparison of Engineered T Cells Carrying a Native TCR versus TCR-like Antibody–Based Chimeric Antigen Receptors Indicates Affinity/Avidity Thresholds. The Journal of Immunology. 193(11). 5733–5743. 103 indexed citations
2.
Voronov, Elena, Shahar Dotan, Rosalyn M. White, et al.. (2010). IL-1-induced inflammation promotes development of leishmaniasis in susceptible BALB/c mice. International Immunology. 22(4). 245–257. 53 indexed citations
3.
Arnon, Tal I., Gal Markel, Ahuva Bar-Ilan, et al.. (2008). Harnessing Soluble NK Cell Killer Receptors for the Generation of Novel Cancer Immune Therapy. PLoS ONE. 3(5). e2150–e2150. 27 indexed citations
4.
Arnon, Tal I., Gal Markel, Ahuva Bar-Ilan, et al.. (2008). Correction: Harnessing Soluble NK Cell Killer Receptors for the Generation of Novel Cancer Immune Therapy. PLoS ONE. 3(5). 3 indexed citations
5.
Zilka, Alon, Guy Landau, Oren Hershkovitz, et al.. (2005). Characterization of the Heparin/Heparan Sulfate Binding Site of the Natural Cytotoxicity Receptor NKp46. Biochemistry. 44(44). 14477–14485. 39 indexed citations
6.
Benchetrit, Fabrice, Olivier Adotévi, Nacilla Haicheur, et al.. (2003). Les lymphocytes T‐CD8 : rôle dans l‘immunosurveillance et l‘immunothérapie antitumorale. Bulletin du Cancer. 90(8). 677–685. 6 indexed citations
7.
Benchetrit, Fabrice, Olivier Adotévi, Nacilla Haicheur, et al.. (2003). [Cytotoxic T lymphocytes: role in immunosurveillance and in immunotherapy].. PubMed. 90(8-9). 677–85. 18 indexed citations
8.
Tartour, Éric, Fabrice Benchetrit, Nacilla Haicheur, Olivier Adotévi, & Wolf H. Fridman. (2002). Synthetic and natural non-live vectors: rationale for their clinical development in cancer vaccine protocols. Vaccine. 20. A32–A39. 11 indexed citations
9.
Benchetrit, Fabrice, Virginie Vives, Guy Warnier, et al.. (2002). Interleukin-17 inhibits tumor cell growth by means of a T-cell–dependent mechanism. Blood. 99(6). 2114–2121. 276 indexed citations
10.

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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