Simon Syga
Impact in
- Cell Biology top 10%
- Cellular Mechanics and Interactions
- Microtubule and mitosis dynamics
- Modeling and Simulation top 10%
- Mathematical Biology Tumor Growth
Papers in
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- Mathematical Biology Tumor Growth 3
- COVID-19 epidemiological studies 1
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- Cellular Mechanics and Interactions 6
- Co-authors
- Andreas Deutsch (9 shared papers)Peter Friedl (2 shared papers)Jürgen Lippoldt (1 shared paper)Pavlo G. Gritsenko (1 shared paper)Steffen Grosser (1 shared paper)Josef Alfons Käs (1 shared paper)Oleksandr Chepizhko (1 shared paper)Manon Vullings (1 shared paper)
- Journals
- PLoS Computational Biology (3 papers)Journal of Cell Science (1 paper)Nature Cell Biology (1 paper)Scientific Reports (1 paper)ChesterRep (University of Chester) (1 paper)
- Partner nations
- GermanyUnited Arab EmiratesNetherlands
In The Last Decade
Simon Syga
9 papers receiving 315 citations
Peers
Comparison fields: 5 of 59
- Cell Biology 184
- Modeling and Simulation 36
- Oncology 98
- Biomedical Engineering 135
- Immunology and Allergy 16
Countries citing papers authored by Simon Syga
This map shows the geographic impact of Simon Syga'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 Simon Syga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Syga more than expected).
Fields of papers citing papers by Simon Syga
This network shows the impact of papers produced by Simon Syga. 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 Simon Syga. The network helps show where Simon Syga may publish in the future.
Co-authors
The 25 scholars most cited alongside Simon Syga, 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 | 267 | |
| 2 | 2021 | 21 | |
| 3 | 2020 | 6 | |
| 4 | 2019 | 6 | |
| 5 | 2020 | 6 | |
| 6 | 2023 | 5 | |
| 7 | 2024 | 3 | |
| 8 | 2023 | 2 | |
| 9 | 2021 | 1 | |
| 10 | 2022 | 0 |
About Simon Syga
Simon Syga is a scholar working on Modeling and Simulation, Cell Biology, Statistical and Nonlinear Physics, Immunology and Allergy and Oncology, having authored 10 papers that have together received 317 indexed citations. Recurring topics across this work include Cellular Mechanics and Interactions (6 papers), Mathematical Biology Tumor Growth (3 papers), Cancer Cells and Metastasis (2 papers), Gene Regulatory Network Analysis (2 papers), 3D Printing in Biomedical Research (2 papers), Cell Adhesion Molecules Research (1 paper), COVID-19 epidemiological studies (1 paper) and Heat shock proteins research (1 paper). The work is most often cited by research in Cell Biology (184 citations), Modeling and Simulation (36 citations), Oncology (98 citations), Biomedical Engineering (135 citations) and Immunology and Allergy (16 citations). Simon Syga has collaborated with scholars based in Germany, United Arab Emirates and Netherlands. Frequent co-authors include Andreas Deutsch, Peter Friedl, Jürgen Lippoldt, Pavlo G. Gritsenko, Steffen Grosser, Josef Alfons Käs, Oleksandr Chepizhko, Manon Vullings, Stefano Zapperi and Gert‐Jan Bakker. Their work appears in journals such as PLoS Computational Biology, Journal of Cell Science, Nature Cell Biology, Scientific Reports and ChesterRep (University of Chester).
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.