Daniel Mona
Impact in
- Neurology top 5%
- 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 ⓘ
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- Parkinson's Disease Mechanisms and Treatments 4
- Botulinum Toxin and Related Neurological Disorders 3
- Neurological disorders and treatments 2
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- Fluorine in Organic Chemistry 1
- Co-authors
- Markus Britschgi (4 shared papers)Matthias E. Lauer (2 shared papers)Ricardo Guerrero-Ferreira (2 shared papers)Henning Stahlberg (2 shared papers)Nicholas M. I. Taylor (2 shared papers)Roland Riek (2 shared papers)Philippe Ringler (2 shared papers)Ali Makky (1 shared paper)
- Journals
- eLife (2 papers)Acta Neuropathologica Communications (1 paper)Advances in experimental medicine and biology (1 paper)Nature Communications (1 paper)Journal of Fluorine Chemistry (1 paper)
- Partner nations
- SwitzerlandUnited StatesNetherlands
In The Last Decade
Daniel Mona
6 papers receiving 703 citations
Hit Papers
Peers
Comparison fields: 5 of 59
- Neurology 430
- Physiology 425
- Neurology 83
- Cellular and Molecular Neuroscience 101
- Biomaterials 59
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 | 441 |
| 2 | 2019 | 222 | |
| 3 | 2008 | 19 | |
| 4 | 1998 | 15 | |
| 5 | 2022 | 8 | |
| 6 | 2025 | 2 |
About Daniel Mona
Daniel Mona is a scholar working on Neurology, Pharmaceutical Science, Physiology, Computational Theory and Mathematics and Cellular and Molecular Neuroscience, having authored 6 papers that have together received 707 indexed citations. Recurring topics across this work include Parkinson's Disease Mechanisms and Treatments (4 papers), Botulinum Toxin and Related Neurological Disorders (3 papers), Alzheimer's disease research and treatments (2 papers), Neurological disorders and treatments (2 papers), Fluorine in Organic Chemistry (1 paper), Computational Drug Discovery Methods (1 paper), Malaria Research and Control (1 paper) and Neuroscience and Neuropharmacology Research (1 paper). The work is most often cited by research in Neurology (430 citations), Physiology (425 citations), Neurology (83 citations), Cellular and Molecular Neuroscience (101 citations) and Biomaterials (59 citations). Daniel Mona has collaborated with scholars based in Switzerland, United States and Netherlands. Frequent co-authors include Markus Britschgi, Matthias E. Lauer, Ricardo Guerrero-Ferreira, Henning Stahlberg, Nicholas M. I. Taylor, Roland Riek, Philippe Ringler, Ali Makky, Joeri Verasdonck and Beat H. Meier. Their work appears in journals such as eLife, Acta Neuropathologica Communications, Advances in experimental medicine and biology, Nature Communications and Journal of Fluorine Chemistry.
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.