Daniel C. Angst
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Molecular Medicine top 10%
- Antibiotic Resistance in Bacteria
Papers in
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- Antibiotic Resistance in Bacteria 4
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- COVID-19 epidemiological studies 3
- Co-authors
- Alex R. Hall (4 shared papers)Sebastian Bonhoeffer (6 shared papers)Sonja Lehtinen (1 shared paper)Nicola N Low (1 shared paper)Jinzhou Li (2 shared papers)Jérémie Scire (2 shared papers)Tanja Stadler (2 shared papers)Jana S. Huisman (2 shared papers)
- Journals
- eLife (2 papers)Proceedings of the National Academy of Sciences (2 papers)Applied and Environmental Microbiology (1 paper)BMC Bioinformatics (1 paper)BMC Evolutionary Biology (1 paper)
- Partner nations
- SwitzerlandUnited StatesSpain
In The Last Decade
Daniel C. Angst
10 papers receiving 331 citations
Peers
Comparison fields: 5 of 85
- Modeling and Simulation 87
- Molecular Medicine 67
- Applied Microbiology and Biotechnology 10
- Infectious Diseases 70
- Microbiology 18
Countries citing papers authored by Daniel C. Angst
This map shows the geographic impact of Daniel C. Angst'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 Daniel C. Angst with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel C. Angst more than expected).
Fields of papers citing papers by Daniel C. Angst
This network shows the impact of papers produced by Daniel C. Angst. 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 Daniel C. Angst. The network helps show where Daniel C. Angst may publish in the future.
Co-authors
The 24 scholars most cited alongside Daniel C. Angst, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 57 | |
| 2 | 2022 | 50 | |
| 3 | 2021 | 50 | |
| 4 | 2023 | 40 | |
| 5 | 2013 | 38 | |
| 6 | 2014 | 35 | |
| 7 | 2023 | 27 | |
| 8 | 2017 | 25 | |
| 9 | 2018 | 9 | |
| 10 | 2024 | 3 |
About Daniel C. Angst
Daniel C. Angst is a scholar working on Molecular Medicine, Modeling and Simulation, Genetics, Pharmacology and Clinical Biochemistry, having authored 10 papers that have together received 334 indexed citations. Recurring topics across this work include Evolution and Genetic Dynamics (6 papers), Antibiotic Resistance in Bacteria (4 papers), COVID-19 epidemiological studies (3 papers), Antibiotics Pharmacokinetics and Efficacy (2 papers), Gut microbiota and health (2 papers), COVID-19 Digital Contact Tracing (1 paper), COVID-19 and healthcare impacts (1 paper) and SARS-CoV-2 and COVID-19 Research (1 paper). The work is most often cited by research in Modeling and Simulation (87 citations), Molecular Medicine (67 citations), Applied Microbiology and Biotechnology (10 citations), Infectious Diseases (70 citations) and Microbiology (18 citations). Daniel C. Angst has collaborated with scholars based in Switzerland, United States and Spain. Frequent co-authors include Alex R. Hall, Sebastian Bonhoeffer, Sonja Lehtinen, Nicola N Low, Jinzhou Li, Jérémie Scire, Tanja Stadler, Jana S. Huisman, Peter D. Ashcroft and Marloes H. Maathuis. Their work appears in journals such as eLife, Proceedings of the National Academy of Sciences, Applied and Environmental Microbiology, BMC Bioinformatics and BMC Evolutionary Biology.
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.