David Vermijlen

4.1k citations
63 papers · 3.0k · h-index 28

Impact in

  • Immunology top 1%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Immunotherapy and Immune Responses
    • Immune Response and Inflammation
    • Reproductive System and Pregnancy
  • Oncology top 2%
    • CAR-T cell therapy research
    • Cancer Immunotherapy and Biomarkers

Papers in

    • Immune Cell Function and Interaction 44
    • T-cell and B-cell Immunology 33
    • Immunotherapy and Immune Responses 12
    • Reproductive System and Pregnancy 5
    • Cell death mechanisms and regulation 4
    • Single-cell and spatial transcriptomics 3

David Vermijlen

62 papers receiving 2.9k citations

Peers

David Vermijlen
Comparison fields: 5 of 106
  • Immunology 2.1k
  • Oncology 860
  • Hepatology 87
  • Epidemiology 372
  • Hematology 118
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Citations per field
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Citations per year

Countries citing papers authored by David Vermijlen

Since Specialization
Citations

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

Fields of papers citing papers by David Vermijlen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007406
2 2010256
3 2015176
4 2010170
5 2013150
6 2017138
7 2007120
8 201888
9 200286
10 201979
11 201171
12 201968
13 201568
14 201464
15 200563
16 200461
17 201957
18 202057
19 202053
20 201751

About David Vermijlen

David Vermijlen is a scholar working on Immunology, Molecular Biology, Epidemiology, Oncology and Genetics, having authored 63 papers that have together received 3.0k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (44 papers), T-cell and B-cell Immunology (33 papers), Immunotherapy and Immune Responses (12 papers), Cytomegalovirus and herpesvirus research (9 papers), CAR-T cell therapy research (6 papers), Reproductive System and Pregnancy (5 papers), Cell death mechanisms and regulation (4 papers) and Single-cell and spatial transcriptomics (3 papers). The work is most often cited by research in Immunology (2.1k citations), Oncology (860 citations), Hepatology (87 citations), Epidemiology (372 citations) and Hematology (118 citations). David Vermijlen has collaborated with scholars based in Belgium, Netherlands and United States. Frequent co-authors include Matthias Eberl, Adrian Hayday, Francesco Dieli, Arnaud Marchant, Catherine Donner, Eddie Wisse, Margreet Brouwer, Serena Meraviglia, Simona Buccheri and Nadia Caccamo. Their work appears in journals such as Frontiers in Immunology, Proceedings of the National Academy of Sciences, European Journal of Immunology, The Journal of Immunology and The Journal of Experimental Medicine.

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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