Gerd Müller

2.0k citations
28 papers · 1.6k · h-index 20

Impact in

  • Immunology top 2%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Immunotherapy and Immune Responses
  • Oncology top 5%
    • Chemokine receptors and signaling
    • CAR-T cell therapy research

Papers in

    • T-cell and B-cell Immunology 13
    • Immune Cell Function and Interaction 10
    • Immunotherapy and Immune Responses 10
    • Chemokine receptors and signaling 8
    • CAR-T cell therapy research 2
    • Polyomavirus and related diseases 1

Gerd Müller

28 papers receiving 1.6k citations

Peers

Gerd Müller
Comparison fields: 5 of 86
  • Immunology 955
  • Oncology 444
  • Hematology 161
  • Genetics 116
  • Pathology and Forensic Medicine 183
Replace Stephen B. Gauld with:
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Gerd Müller relative to Stephen B. Gauld United States Stephen B. Gauld's profile →
Citations per field
00.5×1.5×2.0×
Stephen B. Gauld · 1×
Citations per year

Countries citing papers authored by Gerd Müller

Since Specialization
Citations

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

Fields of papers citing papers by Gerd Müller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006261
2 2003199
3 2014131
4 1990122
5 1999115
6 2012104
7 200277
8 200359
9 199946
10 200345
11 199942
12 199439
13 201738
14 201636
15 200336
16 201533
17 200433
18 200130
19 201524
20 200020

About Gerd Müller

Gerd Müller is a scholar working on Immunology, Oncology, Physiology, Molecular Biology and Radiology, Nuclear Medicine and Imaging, having authored 28 papers that have together received 1.6k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (13 papers), Immune Cell Function and Interaction (10 papers), Immunotherapy and Immune Responses (10 papers), Chemokine receptors and signaling (8 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), CAR-T cell therapy research (2 papers), Lymphoma Diagnosis and Treatment (2 papers) and Polyomavirus and related diseases (1 paper). The work is most often cited by research in Immunology (955 citations), Oncology (444 citations), Hematology (161 citations), Genetics (116 citations) and Pathology and Forensic Medicine (183 citations). Gerd Müller has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Martin Lipp, Uta E. Höpken, Federica Sallusto, Hans-Peter Rahn, Friederike Berberich‐Siebelt, Edgar Serfling, Martin Vaeth, Harald Stein, Ingolf Berberich and Stefan Klein‐Hessling. Their work appears in journals such as Blood, Journal of Leukocyte Biology, Microcirculation, Journal of Clinical Oncology and Nature Communications.

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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