Sven Eyckerman

3.7k citations
70 papers · 1.9k · h-index 23

Impact in

Papers in

    • Bioinformatics and Genomic Networks 9
    • RNA and protein synthesis mechanisms 8
    • CRISPR and Genetic Engineering 6
    • Cytokine Signaling Pathways and Interactions 10

Sven Eyckerman

68 papers receiving 1.8k citations

Peers

Sven Eyckerman
Comparison fields: 5 of 107
  • Endocrine and Autonomic Systems 308
  • Cell Biology 279
  • Molecular Biology 961
  • Immunology 266
  • Oncology 295
Replace Frank Peelman with:
Frank Peelman Belgium
Alessia David United Kingdom
Kenneth Wu United States
Stéphanie Kermorgant United Kingdom
Nicolas Gévry Canada
Sabine Geisse Switzerland
Hongjun Shu United States
Irma Lemmens Belgium
Julia A. Yaglom United States
Kristoffer Rigbolt Denmark
Sven Eyckerman relative to Frank Peelman Belgium Frank Peelman's profile →
Citations per field
00.5×1.5×
Frank Peelman · 1×
Citations per year

Countries citing papers authored by Sven Eyckerman

Since Specialization
Citations

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

Fields of papers citing papers by Sven Eyckerman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001161
2 2003158
3 2000122
4 2010103
5 200489
6 200978
7 201871
8 201870
9 201269
10 202052
11 201951
12 200650
13 200050
14 200545
15
Comparison of leptin- and interleukin-6-regulated expression of the rPAP gene family: evidence for differential co-regulatory signals.
200241
16 201635
17
Analysis of Tyr to Phe and fa/fa leptin receptor mutations in the PC12 cell line.
199933
18 202130
19 201529
20 201028

About Sven Eyckerman

Sven Eyckerman is a scholar working on Molecular Biology, Oncology, Cell Biology, Immunology and Spectroscopy, having authored 70 papers that have together received 1.9k indexed citations. Recurring topics across this work include Biotin and Related Studies (11 papers), Cytokine Signaling Pathways and Interactions (10 papers), Bioinformatics and Genomic Networks (9 papers), Advanced Proteomics Techniques and Applications (8 papers), RNA and protein synthesis mechanisms (8 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Regulation of Appetite and Obesity (7 papers) and CRISPR and Genetic Engineering (6 papers). The work is most often cited by research in Endocrine and Autonomic Systems (308 citations), Cell Biology (279 citations), Molecular Biology (961 citations), Immunology (266 citations) and Oncology (295 citations). Sven Eyckerman has collaborated with scholars based in Belgium, United Kingdom and Germany. Frequent co-authors include Jan Tavernier, Joël Vandekerckhove, Annick Verhee, Irma Lemmens, Kris Gevaert, Delphine Lavens, Frank Peelman, Lennart Zabeau, D. Broekaert and Delphine De Sutter. Their work appears in journals such as Journal of Proteome Research, Scientific Reports, Biochemical Journal, Mass Spectrometry Reviews and Molecular & Cellular Proteomics.

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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