Gaby Brouns

1.9k citations
17 papers · 1.5k · h-index 13

Impact in

  • Immunology top 5%
    • T-cell and B-cell Immunology
    • Immune Cell Function and Interaction
    • Immunodeficiency and Autoimmune Disorders
  • Genetics top 5%
    • Virus-based gene therapy research
    • Chronic Lymphocytic Leukemia Research

Papers in

    • Virus-based gene therapy research 6
    • Blood disorders and treatments 2
    • T-cell and B-cell Immunology 7
    • Immune Cell Function and Interaction 5
    • Immunodeficiency and Autoimmune Disorders 3

Gaby Brouns

17 papers receiving 1.5k citations

Peers

Gaby Brouns
Comparison fields: 5 of 73
  • Immunology 555
  • Genetics 671
  • Genetics 185
  • Oncology 346
  • Molecular Biology 851
Replace Yasuji Ueda with:
Yasuji Ueda Japan
Dina Markowitz United States
Marina Radrizzani Italy
Klaus Kühlcke Germany
Olga Kustikova Germany
Kathryn L. Parsley United Kingdom
Jennifer E. Adair United States
Chantal Lagresle‐Peyrou France
Harry W. Snyder United States
David W. Emery United States
Gaby Brouns relative to Yasuji Ueda Japan Yasuji Ueda's profile →
Citations per field
00.5×1.5×2.4×
Yasuji Ueda · 1×
Citations per year

Countries citing papers authored by Gaby Brouns

Since Specialization
Citations

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

Fields of papers citing papers by Gaby Brouns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 2004476
2 2002409
3 1994163
4 199079
5 199861
6 199658
7 199352
8 199251
9 199640
10 199340
11 199538
12 200026
13 199717
14 199912
15 19988
16 19987
17 20046

About Gaby Brouns

Gaby Brouns is a scholar working on Genetics, Immunology, Oncology, Molecular Biology and Radiology, Nuclear Medicine and Imaging, having authored 17 papers that have together received 1.5k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (7 papers), Virus-based gene therapy research (6 papers), CAR-T cell therapy research (6 papers), Immune Cell Function and Interaction (5 papers), Immunodeficiency and Autoimmune Disorders (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), CRISPR and Genetic Engineering (3 papers) and Blood disorders and treatments (2 papers). The work is most often cited by research in Immunology (555 citations), Genetics (671 citations), Genetics (185 citations), Oncology (346 citations) and Molecular Biology (851 citations). Gaby Brouns has collaborated with scholars based in Netherlands, Germany and United Kingdom. Frequent co-authors include Christine Kinnon, Jannie Borst, Adrian J. Thrasher, Kathryn L. Parsley, Manuel Grez, Christophe Demaison, Karin Battmer, Michaela Scherr, Evert de Vries and Ruud K. B. Schuurman. Their work appears in journals such as Blood, Human Gene Therapy, Journal of Biological Chemistry, The Journal of Gene Medicine and Current Opinion in Immunology.

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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