Matthias Becker

1.8k citations
14 papers · 307 indexed · h-index 7
Topics
SARS-CoV-2 and COVID-19 Research (6 papers)COVID-19 Clinical Research Studies (4 papers)Tissue Engineering and Regenerative Medicine (2 papers)
Partner nations
GermanySwitzerlandCanada

In The Last Decade

Matthias Becker

14 papers receiving 295 citations

Peers

Matthias Becker
Comparison fields: 5 of 70
  • Pharmacology 142
  • Infectious Diseases 88
  • Food Science 73
  • Analytical Chemistry 65
  • Molecular Biology 49
Replace Rixt A. Wijma with:
Rixt A. Wijma Netherlands
C. Solans Spain
Itaru Furuta Japan
K. Küng Switzerland
M. Petsch Austria
William A. Randall United States
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Melvin Weinstein United States
Kai van Hateren Netherlands
Astrid Buxbaum Austria
Matthias Becker relative to Rixt A. Wijma Netherlands Rixt A. Wijma's profile →
Citations per field
00.5×4.6×
Rixt A. Wijma · 1×
Citations per year

Countries citing papers authored by Matthias Becker

Since Specialization
Citations

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

Fields of papers citing papers by Matthias Becker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthias Becker

This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Becker. A scholar is included among the top collaborators of Matthias Becker based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthias Becker. Matthias Becker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
#WorkIndexed citations
1 2
2 3
3 11
4 5
5 13
6 1
7 2
8 44
9 18
10 26
11 2
12 158
13 20
14
Rapid, simple, and reliable doctor's office test for antibodies to human immunodeficiency virus 1 in serum.
2

About Matthias Becker

Matthias Becker is a scholar working on Infectious Diseases, Health and Modeling and Simulation, having authored 14 papers that have together received 307 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (6 papers), COVID-19 Clinical Research Studies (4 papers) and Tissue Engineering and Regenerative Medicine (2 papers). The work is most often cited by research in Pharmacology (142 citations), Analytical Chemistry (65 citations) and Molecular Medicine (32 citations). Matthias Becker has collaborated with scholars based in Germany, Switzerland and Canada. Frequent co-authors include Michael Petz, Nicole Schneiderhan‐Marra, Jens Göpfert, Ulrich Rothbauer, Philipp D. Kaiser, Thomas Joos, Bjoern Traenkle, Gérard Krause, Anne Cossmann and Eike Wrenger. Their work appears in journals such as Advanced Functional Materials, Frontiers in Immunology and Emerging infectious diseases.

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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