Daniel Mayer

878 citations
16 papers · 665 · h-index 12

Impact in

    • Viral Infections and Vectors
  • Immunology top 10%
    • interferon and immune responses
    • Immune Cell Function and Interaction
    • Immune Response and Inflammation

Papers in

    • SARS-CoV-2 and COVID-19 Research 4
    • COVID-19 Clinical Research Studies 3
    • Tuberculosis Research and Epidemiology 2
    • Virology and Viral Diseases 6

Daniel Mayer

14 papers receiving 654 citations

Peers

Daniel Mayer
Comparison fields: 5 of 69
  • Infectious Diseases 238
  • Immunology 272
  • Virology 47
  • Epidemiology 272
  • Animal Science and Zoology 67
Replace Ariel Isaacs with:
Ariel Isaacs Australia
Elisabeth Kamphuis Germany
T. S. Carlos United Kingdom
Emily A. Hemann United States
Kristin Bedard United States
Yann Bénureau France
Hélène Valentin France
Cassandra M. James Australia
Masaaki Okamoto Japan
Kate M. Franz United States
Daniel Mayer relative to Ariel Isaacs Australia Ariel Isaacs's profile →
Citations per field
00.5×1.5×1.8×
Ariel Isaacs · 1×
Citations per year

Countries citing papers authored by Daniel Mayer

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Mayer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 2010362
2 201652
3 200535
4 202134
5 200528
6 202226
7 200725
8 200624
9 200824
10 200821
11 200516
12 202113
13 20233
14 20221
15 19511
16 20230

About Daniel Mayer

Daniel Mayer is a scholar working on Infectious Diseases, Epidemiology, Cardiology and Cardiovascular Medicine, Virology and Genetics, having authored 16 papers that have together received 665 indexed citations. Recurring topics across this work include Virology and Viral Diseases (6 papers), Viral Infections and Immunology Research (5 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Rabies epidemiology and control (3 papers), COVID-19 Clinical Research Studies (3 papers), Virus-based gene therapy research (3 papers), Vaccine Coverage and Hesitancy (2 papers) and Tuberculosis Research and Epidemiology (2 papers). The work is most often cited by research in Infectious Diseases (238 citations), Immunology (272 citations), Virology (47 citations), Epidemiology (272 citations) and Animal Science and Zoology (67 citations). Daniel Mayer has collaborated with scholars based in Germany, United States and Japan. Frequent co-authors include Martin Schwemmle, Georg Kochs, Frédéric Sorgeloos, Markus Mordstein, Toni Rieger, Stephan Ehl, Eva Neugebauer, Vanessa Ditt, Birthe Jessen and Valeria Falcone. Their work appears in journals such as Journal of Virology, Open Forum Infectious Diseases, American Journal of Respiratory and Critical Care Medicine, Cancer Discovery and Journal of Clinical 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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