Georg Meisl
- Physiology top 0.5%
- Alzheimer's disease research and treatments 74
- Biomaterials top 0.5%
- Supramolecular Self-Assembly in Materials 15
- Neurology top 1%
- Parkinson's Disease Mechanisms and Treatments 18
- Neurological diseases and metabolism 5
- Molecular Biology top 2%
- Protein Structure and Dynamics 39
- Prion Diseases and Protein Misfolding 30
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- Computational Drug Discovery Methods 10
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- SARS-CoV-2 and COVID-19 Research 5
- Co-authors
- Tuomas P. J. KnowlesChristopher M. DobsonSara LinseThomas C. T. MichaelsMichele VendruscoloAlexander K. BuellCéline GalvagnionXiaoting Yang
- Cited by
- PhysiologyBiomaterialsNeurology
- Journals
- Proceedings of the National Academy of Sciences (13 papers)Chemical Science (11 papers)ACS Chemical Neuroscience (9 papers)
- Partner nations
- United KingdomSwedenUnited States
In The Last Decade
Georg Meisl
100 papers receiving 5.8k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Physiology 3.6k
- Biomaterials 1.2k
- Neurology 1.1k
- Molecular Biology 3.4k
- Computational Theory and Mathematics 552
Countries citing papers authored by Georg Meisl
This map shows the geographic impact of Georg Meisl'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 Georg Meisl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Georg Meisl more than expected).
Fields of papers citing papers by Georg Meisl
This network shows the impact of papers produced by Georg Meisl. 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 Georg Meisl. The network helps show where Georg Meisl may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Georg Meisl, 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 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 8 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 21 | |
| 7 | 2023 | 9 | |
| 8 | 2022 | 44 | |
| 9 | 2022 | 9 | |
| 10 | 2021 | 74 | |
| 11 | 2021 | 15 | |
| 12 | 2020 | 10 | |
| 13 | 2020 | 92 | |
| 14 | 2020 | 154 | |
| 15 | 2020 | 41 | |
| 16 | 2018 | 9 | |
| 17 | 2018 | 31 | |
| 18 | 2018 | 17 | |
| 19 | 2018 | 80 | |
| 20 | 2017 | 71 |
About Georg Meisl
Georg Meisl is a scholar working on Physiology, Biomaterials and Neurology, having authored 104 papers that have together received 5.9k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (74 papers), Protein Structure and Dynamics (39 papers), Prion Diseases and Protein Misfolding (30 papers), Parkinson's Disease Mechanisms and Treatments (18 papers), Supramolecular Self-Assembly in Materials (15 papers), Computational Drug Discovery Methods (10 papers), SARS-CoV-2 and COVID-19 Research (5 papers) and Neurological diseases and metabolism (5 papers). The work is most often cited by research in Physiology (3.6k citations), Biomaterials (1.2k citations) and Neurology (1.1k citations). Georg Meisl has collaborated with scholars based in United Kingdom, Sweden and United States. Frequent co-authors include Tuomas P. J. Knowles, Christopher M. Dobson, Sara Linse, Thomas C. T. Michaels, Michele Vendruscolo, Alexander K. Buell, Céline Galvagnion, Xiaoting Yang, Samuel I. A. Cohen and Julius B. Kirkegaard. Their work appears in journals such as Proceedings of the National Academy of Sciences, Chemical Science, ACS Chemical Neuroscience, Scientific Reports and Biophysical Journal.
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.