Beat W. Schäfer
- Molecular Biology top 0.5%
- Cancer Research top 0.5%
- Pulmonary and Respiratory Medicine top 1%
- Immunology top 2%
- Oncology top 2%
- Co-authors
- Claus W. HeizmannFelix NiggliMarco WachtelEvelyn C. IlgMarie‐Geneviève MattéiRoland WickiFlorence A. SchollDieter Engelkamp
- Topics
- S100 Proteins and Annexins (58 papers)Sarcoma Diagnosis and Treatment (37 papers)RNA Research and Splicing (22 papers)
- Partner nations
- SwitzerlandGermanyUnited States
In The Last Decade
Beat W. Schäfer
173 papers receiving 9.6k citations
Hit Papers
Peers
Comparison fields: 5 of 142
- Molecular Biology 7.7k
- Cancer Research 2.0k
- Pulmonary and Respiratory Medicine 1.6k
- Immunology 1.4k
- Oncology 1.1k
Countries citing papers authored by Beat W. Schäfer
This map shows the geographic impact of Beat W. Schäfer'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 W. Schäfer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beat W. Schäfer more than expected).
Fields of papers citing papers by Beat W. Schäfer
This network shows the impact of papers produced by Beat W. Schäfer. 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 W. Schäfer. The network helps show where Beat W. Schäfer may publish in the future.
Co-authorship network of co-authors of Beat W. Schäfer
This figure shows the co-authorship network connecting the top 25 collaborators of Beat W. Schäfer. A scholar is included among the top collaborators of Beat W. Schäfer 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 Beat W. Schäfer. Beat W. Schäfer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 31 | |
| 4 | 4 | |
| 5 | 9 | |
| 6 | 42 | |
| 7 | 31 | |
| 8 | 30 | |
| 9 | Material characterization and microstructural simulation of hollow spheres and PCM steel foams | 1 |
| 10 | 42 | |
| 11 | 99 | |
| 12 | Understanding and classifying local, distortional and global buckling in open thin-walled members | 10 |
| 13 | 125 | |
| 14 | 38 | |
| 15 | 45 | |
| 16 | 71 | |
| 17 | 111 | |
| 18 | 136 | |
| 19 | The S100 family of EF-hand calcium-binding proteins: functions and pathologybreakdown → | 564 |
| 20 | 21 |
About Beat W. Schäfer
Beat W. Schäfer is a scholar working on Cancer Research, Molecular Biology and Immunology and Allergy, having authored 174 papers that have together received 9.8k indexed citations. Recurring topics across this work include S100 Proteins and Annexins (58 papers), Sarcoma Diagnosis and Treatment (37 papers) and RNA Research and Splicing (22 papers). The work is most often cited by research in Cancer Research (2.0k citations), Molecular Biology (7.7k citations) and Immunology and Allergy (477 citations). Beat W. Schäfer has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Claus W. Heizmann, Felix Niggli, Marco Wachtel, Evelyn C. Ilg, Marie‐Geneviève Mattéi, Roland Wicki, Florence A. Scholl, Dieter Engelkamp, Michele Bernasconi and Paul Erné. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.
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.