Jan Hasenauer
Impact in
- Modeling and Simulation top 1%
- Mathematical Biology Tumor Growth
- Biophysics top 2%
- Cell Image Analysis Techniques
Papers in
-
- Mathematical Biology Tumor Growth 12
- Biophysics 11
- Cell Image Analysis Techniques 11
- Co-authors
- Fabian J. TheisFabian FröhlichFrank AllgöwerJulio R. BangaDaniel WeindlCarolin LoosSteffen WaldherrAlejandro F. Villaverde
- Journals
- Bioinformatics (24 papers)PLoS Computational Biology (6 papers)Journal of Process Control (4 papers)Journal of Mathematical Biology (4 papers)Investigative Ophthalmology & Visual Science (4 papers)
- Partner nations
- GermanyUnited StatesAustria
In The Last Decade
Jan Hasenauer
132 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 164
- Modeling and Simulation 231
- Biophysics 193
- Molecular Biology 1.7k
- Statistics, Probability and Uncertainty 134
- Statistics and Probability 104
Countries citing papers authored by Jan Hasenauer
This map shows the geographic impact of Jan Hasenauer'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 Hasenauer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Hasenauer more than expected).
Fields of papers citing papers by Jan Hasenauer
This network shows the impact of papers produced by Jan Hasenauer. 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 Hasenauer. The network helps show where Jan Hasenauer may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jan Hasenauer, 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 | 2025 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 8 | |
| 5 | 2023 | 9 | |
| 6 | 2023 | 6 | |
| 7 | 2023 | 21 | |
| 8 | 2023 | 0 | |
| 9 | 2022 | 18 | |
| 10 | 2021 | 6 | |
| 11 | 2020 | 15 | |
| 12 | 2019 | 51 | |
| 13 | 2019 | 23 | |
| 14 | 2019 | 14 | |
| 15 | 2018 | 1 | |
| 16 | 2018 | 55 | |
| 17 | 2018 | 18 | |
| 18 | 2018 | 20 | |
| 19 | 2018 | 91 | |
| 20 | 2018 | 37 |
About Jan Hasenauer
Jan Hasenauer is a scholar working on Modeling and Simulation, Biophysics, Statistics and Probability, Statistics, Probability and Uncertainty and Molecular Biology, having authored 144 papers that have together received 2.7k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (69 papers), Microbial Metabolic Engineering and Bioproduction (20 papers), Single-cell and spatial transcriptomics (12 papers), Mathematical Biology Tumor Growth (12 papers), Bioinformatics and Genomic Networks (12 papers), Cell Image Analysis Techniques (11 papers), Gaussian Processes and Bayesian Inference (11 papers) and Advanced Control Systems Optimization (10 papers). The work is most often cited by research in Modeling and Simulation (231 citations), Biophysics (193 citations), Molecular Biology (1.7k citations), Statistics, Probability and Uncertainty (134 citations) and Statistics and Probability (104 citations). Jan Hasenauer has collaborated with scholars based in Germany, United States and Austria. Frequent co-authors include Fabian J. Theis, Fabian Fröhlich, Frank Allgöwer, Julio R. Banga, Daniel Weindl, Carolin Loos, Steffen Waldherr, Alejandro F. Villaverde, Nicole Radde and Yannik Schälte. Their work appears in journals such as Bioinformatics, PLoS Computational Biology, Journal of Process Control, Journal of Mathematical Biology and Investigative Ophthalmology & Visual Science.
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.