Markus Tusche
Impact in
- Physiology top 2%
- Alzheimer's disease research and treatments
- Biomaterials top 5%
- Supramolecular Self-Assembly in Materials
Papers in ⓘ
- Physiology 15
- Alzheimer's disease research and treatments 15
-
- Protein Structure and Dynamics 4
- Co-authors
- Dieter Willbold (18 shared papers)Lothar Gremer (8 shared papers)Wolfgang Hoyer (4 shared papers)Elke Reinartz (4 shared papers)Henrike Heise (3 shared papers)Jörg Labahn (2 shared papers)Raimond B. G. Ravelli (2 shared papers)C. Schenk (2 shared papers)
- Journals
- ACS Chemical Neuroscience (3 papers)Scientific Reports (3 papers)European Journal of Pharmaceutical Sciences (2 papers)PLoS ONE (2 papers)Neuropeptides (1 paper)
- Partner nations
- GermanyUnited StatesAustralia
In The Last Decade
Markus Tusche
19 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Physiology 788
- Biomaterials 196
- Computational Theory and Mathematics 193
- Structural Biology 15
- Biological Psychiatry 24
Countries citing papers authored by Markus Tusche
This map shows the geographic impact of Markus Tusche'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 Markus Tusche with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Tusche more than expected).
Fields of papers citing papers by Markus Tusche
This network shows the impact of papers produced by Markus Tusche. 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 Markus Tusche. The network helps show where Markus Tusche may publish in the future.
Co-authors
The 25 scholars most cited alongside Markus Tusche, 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 | Fibril structure of amyloid-β(1–42) by cryo–electron microscopy Hit paper breakdown → | 2017 | 802 |
| 2 | 2017 | 47 | |
| 3 | 2021 | 30 | |
| 4 | 2017 | 29 | |
| 5 | 2016 | 26 | |
| 6 | 2019 | 23 | |
| 7 | 2017 | 23 | |
| 8 | 2016 | 19 | |
| 9 | 2016 | 13 | |
| 10 | 2017 | 12 | |
| 11 | 2022 | 12 | |
| 12 | 2017 | 11 | |
| 13 | 2018 | 10 | |
| 14 | 2017 | 8 | |
| 15 | 2021 | 8 | |
| 16 | 2023 | 6 | |
| 17 | 2020 | 4 | |
| 18 | 2017 | 3 | |
| 19 | 2024 | 1 |
About Markus Tusche
Markus Tusche is a scholar working on Physiology, Molecular Biology, Oncology, Biomaterials and Computational Theory and Mathematics, having authored 19 papers that have together received 1.1k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (15 papers), Protein Structure and Dynamics (4 papers), Computational Drug Discovery Methods (3 papers), Supramolecular Self-Assembly in Materials (3 papers), Amino Acid Enzymes and Metabolism (3 papers), Drug Transport and Resistance Mechanisms (3 papers), Advanced NMR Techniques and Applications (2 papers) and Cholinesterase and Neurodegenerative Diseases (2 papers). The work is most often cited by research in Physiology (788 citations), Biomaterials (196 citations), Computational Theory and Mathematics (193 citations), Structural Biology (15 citations) and Biological Psychiatry (24 citations). Markus Tusche has collaborated with scholars based in Germany, United States and Australia. Frequent co-authors include Dieter Willbold, Lothar Gremer, Wolfgang Hoyer, Elke Reinartz, Henrike Heise, Jörg Labahn, Raimond B. G. Ravelli, C. Schenk, Gunnar F. Schröder and Carmen López‐Iglesias. Their work appears in journals such as ACS Chemical Neuroscience, Scientific Reports, European Journal of Pharmaceutical Sciences, PLoS ONE and Neuropeptides.
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.