Rolf Schwarzer
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Clinical Biochemistry top 5%
- Metabolism and Genetic Disorders
Papers in
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- Mitochondrial Function and Pathology 3
- Bone Metabolism and Diseases 3
- Ubiquitin and proteasome pathways 3
- Histone Deacetylase Inhibitors Research 2
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- Multiple Myeloma Research and Treatments 2
- Co-authors
- Daniel Tondera (4 shared papers)Franziska Jundt (9 shared papers)Jörg Kaufmann (3 shared papers)Anke Klippel (3 shared papers)Ansgar Santel (2 shared papers)Bernd Dörken (5 shared papers)G. Peters (1 shared paper)Klaus Giese (2 shared papers)
In The Last Decade
Rolf Schwarzer
27 papers receiving 1.3k citations
Rolf Schwarzer's Hit Papers
Peers
Comparison fields: 5 of 111
- Modeling and Simulation 74
- Clinical Biochemistry 79
- Infectious Diseases 205
- Cancer Research 138
- Hematology 107
Countries citing papers authored by Rolf Schwarzer
This map shows the geographic impact of Rolf Schwarzer'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 Rolf Schwarzer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rolf Schwarzer more than expected).
Fields of papers citing papers by Rolf Schwarzer
This network shows the impact of papers produced by Rolf Schwarzer. 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 Rolf Schwarzer. The network helps show where Rolf Schwarzer may publish in the future.
Co-authors
The 25 scholars most cited alongside Rolf Schwarzer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Estimating infectiousness throughout SARS-CoV-2 infection course Hit paper breakdown → | 2021 | 298 |
| 2 | 2005 | 188 | |
| 3 | 2004 | 123 | |
| 4 | 2004 | 116 | |
| 5 | 1985 | 88 | |
| 6 | 2005 | 87 | |
| 7 | 2011 | 73 | |
| 8 | 2008 | 67 | |
| 9 | 2012 | 62 | |
| 10 | 2000 | 48 | |
| 11 | 2008 | 42 | |
| 12 | 2014 | 37 | |
| 13 | 2008 | 31 | |
| 14 | 2011 | 25 | |
| 15 | 2022 | 17 | |
| 16 | 2021 | 14 | |
| 17 | 2021 | 13 | |
| 18 | 2021 | 12 | |
| 19 | 2023 | 7 | |
| 20 | 2011 | 4 |
About Rolf Schwarzer
Rolf Schwarzer is a scholar working on Molecular Biology, Hematology, Cancer Research, Urology and Oncology, having authored 28 papers that have together received 1.4k indexed citations. Recurring topics across this work include Mitochondrial Function and Pathology (3 papers), Bone Metabolism and Diseases (3 papers), Ubiquitin and proteasome pathways (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Bone health and treatments (2 papers), SARS-CoV-2 detection and testing (2 papers), Histone Deacetylase Inhibitors Research (2 papers) and Multiple Myeloma Research and Treatments (2 papers). The work is most often cited by research in Modeling and Simulation (74 citations), Clinical Biochemistry (79 citations), Infectious Diseases (205 citations), Cancer Research (138 citations) and Hematology (107 citations). Rolf Schwarzer has collaborated with scholars based in Germany, Norway and Bulgaria. Frequent co-authors include Daniel Tondera, Franziska Jundt, Jörg Kaufmann, Anke Klippel, Ansgar Santel, Bernd Dörken, G. Peters, Klaus Giese, Frank Czauderna and Katharina Paulick. Their work appears in journals such as Leukemia, Blood, Current Molecular Medicine, BMC Oral Health and European Journal of Dermatology.
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.