Beat Kunz

1.8k citations
33 papers · 1.5k indexed · h-index 21

Impact in

Papers in

Beat Kunz

33 papers receiving 1.4k citations

Peers

Beat Kunz
Comparison fields: 5 of 102
  • Developmental Neuroscience 242
  • Cellular and Molecular Neuroscience 668
  • Immunology and Allergy 208
  • Cell Biology 481
  • Molecular Biology 798
Replace Shuji Wakatsuki with:
Shuji Wakatsuki Japan
Saeko Kawabata Japan
Santiago Quiroga Argentina
Michael Willem Germany
Yukako Yokota United States
Akira Tohgo Japan
Paul S. Amieux United States
Annie Schweitzer France
Lisa M. Moscoso United States
Peter S. Walmod Denmark
Beat Kunz relative to Shuji Wakatsuki Japan Shuji Wakatsuki's profile →
Citations per field
00.5×1.7×
Shuji Wakatsuki · 1×
Citations per year

Countries citing papers authored by Beat Kunz

Since Specialization
Citations

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

Fields of papers citing papers by Beat Kunz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20218
2 201410
3 201312
4 201254
5 201234
6 201025
7 200988
8 200818
9 200248
10 20023
11 20003
12 199938
13 199942
14 199813
15 199729
16 199721
17 199654
18 199377
19 19884
20
The composition of the medial articular nerve to the knee in the dog.
19829

About Beat Kunz

Beat Kunz is a scholar working on Developmental Neuroscience, Immunology and Allergy, Cellular and Molecular Neuroscience, Cell Biology and Neurology, having authored 33 papers that have together received 1.5k indexed citations. Recurring topics across this work include Axon Guidance and Neuronal Signaling (12 papers), Glycosylation and Glycoproteins Research (6 papers), Cellular transport and secretion (6 papers), Cellular Mechanics and Interactions (6 papers), Cell Adhesion Molecules Research (6 papers), Neurogenesis and neuroplasticity mechanisms (5 papers), Neurological diseases and metabolism (3 papers) and Prion Diseases and Protein Misfolding (3 papers). The work is most often cited by research in Developmental Neuroscience (242 citations), Cellular and Molecular Neuroscience (668 citations), Immunology and Allergy (208 citations), Cell Biology (481 citations) and Molecular Biology (798 citations). Beat Kunz has collaborated with scholars based in Switzerland, United States and Japan. Frequent co-authors include P. Sonderegger, Christoph Rader, Urs Ziegler, Stefan Kunz, Andreas Zurlinden, Andrea Buchstaller, Philipp Berger, Esther T. Stoeckli, Rico Sennrich and Marc Bolliger. Their work appears in journals such as The Journal of Cell Biology, The FASEB Journal, FEBS Letters, European Journal of Biochemistry and Biology Open.

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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