Carolin Loos
Impact in
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Modeling and Simulation top 10%
Papers in
-
- Gene Regulatory Network Analysis 5
- Single-cell and spatial transcriptomics 2
-
- T-cell and B-cell Immunology 3
- Co-authors
- Jan Hasenauer (8 shared papers)Douglas A. Lauffenburger (8 shared papers)Galit Alter (9 shared papers)Caroline Atyeo (3 shared papers)Sabrina Krause (2 shared papers)Fabian Fröhlich (2 shared papers)Richelle C. Charles (2 shared papers)Edward T. Ryan (2 shared papers)
- Journals
- Bioinformatics (4 papers)Scientific Reports (2 papers)Cell Systems (2 papers)Nature Communications (1 paper)The Journal of Infectious Diseases (1 paper)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Carolin Loos
19 papers receiving 559 citations
Peers
Comparison fields: 5 of 87
- Infectious Diseases 208
- Modeling and Simulation 33
- Virology 23
- Immunology 74
- Molecular Biology 230
Countries citing papers authored by Carolin Loos
This map shows the geographic impact of Carolin Loos'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 Carolin Loos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carolin Loos more than expected).
Fields of papers citing papers by Carolin Loos
This network shows the impact of papers produced by Carolin Loos. 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 Carolin Loos. The network helps show where Carolin Loos may publish in the future.
Co-authors
The 25 scholars most cited alongside Carolin Loos, 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 | 2020 | 160 | |
| 2 | 2017 | 63 | |
| 3 | 2019 | 54 | |
| 4 | 2020 | 52 | |
| 5 | 2022 | 39 | |
| 6 | 2016 | 28 | |
| 7 | 2020 | 26 | |
| 8 | 2018 | 26 | |
| 9 | 2021 | 21 | |
| 10 | 2018 | 19 | |
| 11 | 2019 | 18 | |
| 12 | 2023 | 16 | |
| 13 | 2021 | 13 | |
| 14 | 2020 | 8 | |
| 15 | 2022 | 6 | |
| 16 | 2020 | 5 | |
| 17 | 2024 | 4 | |
| 18 | 2019 | 2 | |
| 19 | Analysis of Single-Cell Data. ODE Constrained Mixture Modeling and Approximate Bayesian Computation. | 2016 | 1 |
| 20 | [RCVS: case-study and role of substance abuse, Covid and psychotropic drugs]. | 2024 | 0 |
About Carolin Loos
Carolin Loos is a scholar working on Molecular Biology, Immunology, Infectious Diseases, Virology and Radiology, Nuclear Medicine and Imaging, having authored 20 papers that have together received 561 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (5 papers), T-cell and B-cell Immunology (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), HIV Research and Treatment (3 papers), Single-cell and spatial transcriptomics (2 papers), Evolution and Genetic Dynamics (2 papers) and Cell Image Analysis Techniques (2 papers). The work is most often cited by research in Infectious Diseases (208 citations), Modeling and Simulation (33 citations), Virology (23 citations), Immunology (74 citations) and Molecular Biology (230 citations). Carolin Loos has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Jan Hasenauer, Douglas A. Lauffenburger, Galit Alter, Caroline Atyeo, Sabrina Krause, Fabian Fröhlich, Richelle C. Charles, Edward T. Ryan, Matthew D. Slein and Hendrik Streeck. Their work appears in journals such as Bioinformatics, Scientific Reports, Cell Systems, Nature Communications and The Journal of Infectious Diseases.
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.