Wim Maes

1.4k citations
26 papers · 1.1k · h-index 17

Impact in

  • Genetics top 5%
    • Glioma Diagnosis and Treatment
  • Immunology top 5%
    • Immunotherapy and Immune Responses
    • Immune cells in cancer
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology

Papers in

    • Immunotherapy and Immune Responses 9
    • T-cell and B-cell Immunology 5
    • Immune Cell Function and Interaction 5
    • Galectins and Cancer Biology 2
    • Cancer Immunotherapy and Biomarkers 4

Wim Maes

25 papers receiving 1.1k citations

Peers

Wim Maes
Comparison fields: 5 of 90
  • Genetics 309
  • Immunology 575
  • Oncology 437
  • Neurology 48
  • Molecular Biology 352
Replace Chalid Assaf with:
Chalid Assaf Germany
Hélène Gary‐Gouy France
Valerie I. Brown United States
Eva Sahakian United States
Shu Cheng China
Fengdong Cheng United States
Tonny Lagerweij Netherlands
Yulia Vugmeyster United States
Susan Togher United States
Roland Grenningloh United States
Wim Maes relative to Chalid Assaf Germany Chalid Assaf's profile →
Citations per field
00.5×1.5×
Chalid Assaf · 1×
Citations per year

Countries citing papers authored by Wim Maes

Since Specialization
Citations

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

Fields of papers citing papers by Wim Maes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012124
2 2010115
3 2020104
4 200985
5 200484
6 201083
7 201372
8 200966
9 202245
10 201741
11 201335
12 200833
13 200932
14 201725
15 200825
16 201325
17 200923
18 201814
19 201213
20 200911

About Wim Maes

Wim Maes is a scholar working on Immunology, Oncology, Molecular Biology, Infectious Diseases and Genetics, having authored 26 papers that have together received 1.1k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (9 papers), T-cell and B-cell Immunology (5 papers), Immune Cell Function and Interaction (5 papers), Cancer Immunotherapy and Biomarkers (4 papers), COVID-19 Clinical Research Studies (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Glioma Diagnosis and Treatment (3 papers) and Galectins and Cancer Biology (2 papers). The work is most often cited by research in Genetics (309 citations), Immunology (575 citations), Oncology (437 citations), Neurology (48 citations) and Molecular Biology (352 citations). Wim Maes has collaborated with scholars based in Belgium, United States and Netherlands. Frequent co-authors include Stefaan Van Gool, Steven De Vleeschouwer, Hilko Ardon, Tina Verschuere, Louis Boon, Bert Verbinnen, Jan Ceuppens, Stefaan W. Van Gool, Raf Sciot and Jan Goffin. Their work appears in journals such as Journal of Neuro-Oncology, Cancer Immunology Immunotherapy, European Journal of Immunology, Molecular Therapy and Transfusion.

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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