Jan Brauner
Impact in
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies
- Immunology top 10%
- Neutrophil, Myeloperoxidase and Oxidative Mechanisms
- Immune cells in cancer
Papers in ⓘ
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- Lipid Membrane Structure and Behavior 2
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- COVID-19 epidemiological studies 6
- Co-authors
- Martin Herrmann (3 shared papers)Mona Biermann (3 shared papers)Sören Mindermann (6 shared papers)Mrinank Sharma (6 shared papers)Yi Zhao (2 shared papers)Hang Yang (1 shared paper)Joshua Teperowski Monrad (4 shared papers)Yi Liu (1 shared paper)
- Journals
- Depression and Anxiety (2 papers)Proceedings of the National Academy of Sciences (2 papers)Journal of Antimicrobial Chemotherapy (2 papers)BMJ Global Health (1 paper)Nature Communications (1 paper)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Jan Brauner
20 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 151
- Modeling and Simulation 551
- Immunology 288
- Infectious Diseases 251
- Health 97
- Economics and Econometrics 241
Countries citing papers authored by Jan Brauner
This map shows the geographic impact of Jan Brauner'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 Jan Brauner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Brauner more than expected).
Fields of papers citing papers by Jan Brauner
This network shows the impact of papers produced by Jan Brauner. 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 Jan Brauner. The network helps show where Jan Brauner may publish in the future.
Co-authors
The 25 scholars most cited alongside Jan Brauner, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Inferring the effectiveness of government interventions against COVID-19 Hit paper breakdown → | 2020 | 630 |
| 2 | 2016 | 250 | |
| 3 | 2016 | 114 | |
| 4 | 2022 | 57 | |
| 5 | 2021 | 54 | |
| 6 | 2023 | 34 | |
| 7 | 2022 | 33 | |
| 8 | 2013 | 32 | |
| 9 | 2014 | 18 | |
| 10 | 2022 | 13 | |
| 11 | 2013 | 12 | |
| 12 | 2022 | 11 | |
| 13 | 2023 | 9 | |
| 14 | 2014 | 9 | |
| 15 | 2022 | 8 | |
| 16 | 2021 | 8 | |
| 17 | 2022 | 5 | |
| 18 | 2018 | 4 | |
| 19 | 2025 | 3 | |
| 20 | 2014 | 3 |
About Jan Brauner
Jan Brauner is a scholar working on Molecular Biology, Modeling and Simulation, Infectious Diseases, Cellular and Molecular Neuroscience and Clinical Psychology, having authored 21 papers that have together received 1.3k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (6 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (2 papers), Neuroscience and Neural Engineering (2 papers), Lipid Membrane Structure and Behavior (2 papers), HIV Research and Treatment (2 papers), HIV/AIDS Research and Interventions (2 papers), COVID-19 Pandemic Impacts (2 papers) and Digital Mental Health Interventions (2 papers). The work is most often cited by research in Modeling and Simulation (551 citations), Immunology (288 citations), Infectious Diseases (251 citations), Health (97 citations) and Economics and Econometrics (241 citations). Jan Brauner has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Martin Herrmann, Mona Biermann, Sören Mindermann, Mrinank Sharma, Yi Zhao, Hang Yang, Joshua Teperowski Monrad, Yi Liu, Gavin Leech and Jan Kulveit. Their work appears in journals such as Depression and Anxiety, Proceedings of the National Academy of Sciences, Journal of Antimicrobial Chemotherapy, BMJ Global Health and Nature Communications.
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.