Daniel Mona
Impact in
- Neurology top 2%
- Parkinson's Disease Mechanisms and Treatments
- Neurological disorders and treatments
- Neurological diseases and metabolism
- Botulinum Toxin and Related Neurological Disorders
- Physiology top 5%
- Alzheimer's disease research and treatments
Papers in
-
- Parkinson's Disease Mechanisms and Treatments 5
- Botulinum Toxin and Related Neurological Disorders 3
- Neurological disorders and treatments 3
- Co-authors
- Markus Britschgi (4 shared papers)Ricardo Guerrero-Ferreira (2 shared papers)Matthias E. Lauer (2 shared papers)Philippe Ringler (2 shared papers)Roland Riek (2 shared papers)Nicholas Michael Ian Taylor (2 shared papers)Henning Stahlberg (2 shared papers)Anja Böckmann (1 shared paper)
- Journals
- eLife (2 papers)Nature Communications (1 paper)Acta Neuropathologica Communications (1 paper)Acta Neuropathologica (1 paper)Advances in experimental medicine and biology (1 paper)
- Partner nations
- SwitzerlandNetherlandsUnited States
In The Last Decade
Daniel Mona
7 papers receiving 861 citations
Daniel Mona's Hit Papers
Peers
Comparison fields: 5 of 65
- Neurology 546
- Physiology 466
- Neurology 92
- Cellular and Molecular Neuroscience 134
- Biomaterials 64
Countries citing papers authored by Daniel Mona
This map shows the geographic impact of Daniel Mona'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 Mona with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Mona more than expected).
Fields of papers citing papers by Daniel Mona
This network shows the impact of papers produced by Daniel Mona. 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 Mona. The network helps show where Daniel Mona may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Mona, 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 | Cryo-EM structure of alpha-synuclein fibrils Hit paper breakdown → | 2018 | 478 |
| 2 | 2019 | 247 | |
| 3 | 2021 | 96 | |
| 4 | 2008 | 20 | |
| 5 | 1998 | 18 | |
| 6 | 2022 | 13 | |
| 7 | 2025 | 4 |
About Daniel Mona
Daniel Mona is a scholar working on Neurology, Pharmaceutical Science, Physiology, Cell Biology and Computational Theory and Mathematics, having authored 7 papers that have together received 876 indexed citations. Recurring topics across this work include Parkinson's Disease Mechanisms and Treatments (5 papers), Botulinum Toxin and Related Neurological Disorders (3 papers), Neurological disorders and treatments (3 papers), Alzheimer's disease research and treatments (2 papers), Computational Drug Discovery Methods (1 paper), Click Chemistry and Applications (1 paper), Malaria Research and Control (1 paper) and Diverse Scientific Research Studies (1 paper). The work is most often cited by research in Neurology (546 citations), Physiology (466 citations), Neurology (92 citations), Cellular and Molecular Neuroscience (134 citations) and Biomaterials (64 citations). Daniel Mona has collaborated with scholars based in Switzerland, Netherlands and United States. Frequent co-authors include Markus Britschgi, Ricardo Guerrero-Ferreira, Matthias E. Lauer, Philippe Ringler, Roland Riek, Nicholas Michael Ian Taylor, Henning Stahlberg, Anja Böckmann, Ronald Melki and Luc Bousset. Their work appears in journals such as eLife, Nature Communications, Acta Neuropathologica Communications, Acta Neuropathologica and Advances in experimental medicine and 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.