Gergő Bohner
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
- Cell Biology top 5%
- Microtubule and mitosis dynamics
- Cellular Mechanics and Interactions
- Cellular transport and secretion
Papers in
-
- Photosynthetic Processes and Mechanisms 2
- Ion channel regulation and function 1
-
- Neural Networks and Applications 2
- Co-authors
- Thomas Surrey (3 shared papers)Sebastian P. Maurer (3 shared papers)Franck J. Fourniol (1 shared paper)Carolyn A. Moores (1 shared paper)Nicholas I. Cade (2 shared papers)Nils Gustafsson (2 shared papers)Emmanuel Boutant (1 shared paper)Sebastian J. Vollmer (2 shared papers)
- Journals
- npj Digital Medicine (1 paper)Current Biology (1 paper)The Journal of General Physiology (1 paper)Journal of Microscopy (1 paper)Cell (1 paper)
- Partner nations
- United KingdomGermanyNetherlands
In The Last Decade
Gergő Bohner
9 papers receiving 756 citations
Peers
Comparison fields: 5 of 123
- Health Informatics 142
- Cell Biology 428
- Structural Biology 18
- Health Information Management 40
- Molecular Biology 384
Countries citing papers authored by Gergő Bohner
This map shows the geographic impact of Gergő Bohner'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 Gergő Bohner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gergő Bohner more than expected).
Fields of papers citing papers by Gergő Bohner
This network shows the impact of papers produced by Gergő Bohner. 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 Gergő Bohner. The network helps show where Gergő Bohner may publish in the future.
Co-authors
The 25 scholars most cited alongside Gergő Bohner, 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 | 307 | |
| 2 | 2012 | 279 | |
| 3 | 2014 | 160 | |
| 4 | 2015 | 13 | |
| 5 | 2017 | 4 | |
| 6 | Unlocking neural population non-stationarities using hierarchical dynamics models | 2015 | 3 |
| 7 | 2024 | 1 | |
| 8 | Unlocking neural population non-stationarity using a hierarchical dynamics model | 2015 | 1 |
| 9 | 2016 | 1 |
About Gergő Bohner
Gergő Bohner is a scholar working on Molecular Biology, Artificial Intelligence, Cell Biology, Statistical and Nonlinear Physics and Cognitive Neuroscience, having authored 9 papers that have together received 769 indexed citations. Recurring topics across this work include Microtubule and mitosis dynamics (3 papers), Neural Networks and Applications (2 papers), Advanced Fluorescence Microscopy Techniques (2 papers), Photosynthetic Processes and Mechanisms (2 papers), stochastic dynamics and bifurcation (2 papers), Neural dynamics and brain function (2 papers), Cardiac electrophysiology and arrhythmias (1 paper) and Ion channel regulation and function (1 paper). The work is most often cited by research in Health Informatics (142 citations), Cell Biology (428 citations), Structural Biology (18 citations), Health Information Management (40 citations) and Molecular Biology (384 citations). Gergő Bohner has collaborated with scholars based in United Kingdom, Germany and Netherlands. Frequent co-authors include Thomas Surrey, Sebastian P. Maurer, Franck J. Fourniol, Carolyn A. Moores, Nicholas I. Cade, Nils Gustafsson, Emmanuel Boutant, Sebastian J. Vollmer, Chris Holmes and Bilal A. Mateen. Their work appears in journals such as npj Digital Medicine, Current Biology, The Journal of General Physiology, Journal of Microscopy and Cell.
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.