Y. Gevaert

1.8k total citations
9 papers, 1.4k citations indexed

About

Y. Gevaert is a scholar working on Immunology, Endocrinology, Diabetes and Metabolism and Molecular Biology. According to data from OpenAlex, Y. Gevaert has authored 9 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Immunology, 3 papers in Endocrinology, Diabetes and Metabolism and 2 papers in Molecular Biology. Recurrent topics in Y. Gevaert's work include Immune Cell Function and Interaction (5 papers), Immune Response and Inflammation (5 papers) and T-cell and B-cell Immunology (2 papers). Y. Gevaert is often cited by papers focused on Immune Cell Function and Interaction (5 papers), Immune Response and Inflammation (5 papers) and T-cell and B-cell Immunology (2 papers). Y. Gevaert collaborates with scholars based in Belgium and France. Y. Gevaert's co-authors include P Franchimont, Donat De Groote, Nicole Schaaf‐Lafontaine, Renaud Louis, Jacques Bélaïche, Édouard Louis, S. Roland, P Mahieu, Anthony Piron and Michel Malaise and has published in prestigious journals such as Transplantation, Journal of Immunological Methods and Clinical & Experimental Immunology.

In The Last Decade

Y. Gevaert

9 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Y. Gevaert Belgium	8	600	278	188	141	134	9	1.4k
Maarten Helle Netherlands	12	657 1.1×	239 0.9×	333 1.8×	113 0.8×	237 1.8×	12	1.7k
Philip Scuderi United States	26	653 1.1×	261 0.9×	407 2.2×	134 1.0×	225 1.7×	69	2.1k
Talia Hahn Israel	24	705 1.2×	403 1.4×	420 2.2×	111 0.8×	180 1.3×	70	1.7k
J Corberand France	20	657 1.1×	358 1.3×	312 1.7×	137 1.0×	166 1.2×	70	1.9k
H Tchórzewski Poland	26	981 1.6×	233 0.8×	307 1.6×	113 0.8×	169 1.3×	159	2.1k
Salvatore Milano Italy	25	470 0.8×	406 1.5×	285 1.5×	97 0.7×	123 0.9×	61	1.7k
M. Baudrihaye France	6	464 0.8×	170 0.6×	167 0.9×	109 0.8×	103 0.8×	7	1.0k
Morten Bagge Hansen Denmark	25	584 1.0×	234 0.8×	241 1.3×	125 0.9×	132 1.0×	62	1.6k
Peter Juel Thiis Knudsen Denmark	18	496 0.8×	123 0.4×	352 1.9×	106 0.8×	124 0.9×	54	1.4k
Yoshio Wakatsuki Japan	25	865 1.4×	206 0.7×	344 1.8×	162 1.1×	150 1.1×	58	1.7k

Countries citing papers authored by Y. Gevaert

Since Specialization

Citations

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

Fields of papers citing papers by Y. Gevaert

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Y. Gevaert

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

All Works

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9 of 9 papers shown

1.

Louis, Édouard, Denis Franchimont, Anthony Piron, et al.. (1998). Tumour necrosis factor (TNF) gene polymorphism influences TNF-α production in lipopolysaccharide (LPS)-stimulated whole blood cell culture in healthy humans. Clinical & Experimental Immunology. 113(3). 401–406. 496 indexed citations

2.

Groote, Donat De, Michel Jadoul, I. Dehart, et al.. (1994). An ELISA for the measurement of human leukemia inhibitory factor in biological fluids and culture supernatants. Journal of Immunological Methods. 167(1-2). 253–261. 12 indexed citations

3.

Groote, Donat De, Arnaud Marchant, Michel Jadoul, et al.. (1994). Characterisation of monoclonal antibodies against human interleukin-10 and their use in an ELISA for the measurement of this cytokine. Journal of Immunological Methods. 177(1-2). 225–234. 20 indexed citations

4.

Groote, Donat De, Y. Gevaert, M. Lopez, et al.. (1993). Novel method for the measurement of cytokine production by a one-stage procedure. Journal of Immunological Methods. 163(2). 259–267. 58 indexed citations

5.

Groote, D De, P.F. Zangerle, Y. Gevaert, et al.. (1992). Direct stimulation of cytokines (IL-1β, TNF-α, IL-6, IL-2, IFN-γ and GM-CSF) in whole blood. I. Comparison with isolated PBMC stimulation. Cytokine. 4(3). 239–248. 433 indexed citations

6.

Chatenoud, Lucienne, Christiane Ferran, Christophe Legendre, et al.. (1990). IN VIVO CELL ACTIVATION FOLLOWING OKT3 ADMINISTRATION. Transplantation. 49(4). 697–702. 250 indexed citations

7.

Gevaert, Y., et al.. (1976). [Radioimmunoassay of thyroid stimulating hormone by sequential saturation].. PubMed. 34(3). 191–5. 1 indexed citations

8.

Reuter, A., et al.. (1976). Homologous radioimmunoassay for human prolactin. International Journal of Nuclear Medicine and Biology. 3(1). 21–28. 76 indexed citations

9.

Gevaert, Y., et al.. (1975). [Radioimmunoassay of human prolactin].. PubMed. 23(10). 761–7. 19 indexed citations

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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