Tom Scheidt
Impact in
- Physiology top 10%
- Alzheimer's disease research and treatments
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- Supramolecular Self-Assembly in Materials
Papers in
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- Protein Structure and Dynamics 6
- RNA Research and Splicing 4
- Heat shock proteins research 2
- S100 Proteins and Annexins 2
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- Alzheimer's disease research and treatments 3
- Co-authors
- Tuomas P. J. Knowles (7 shared papers)Christopher M. Dobson (5 shared papers)Michele Vendruscolo (4 shared papers)Samuel I. A. Cohen (2 shared papers)Sara Linse (2 shared papers)Georg Meisl (4 shared papers)Paolo Arosio (2 shared papers)Catherine K. Xu (3 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (3 papers)Biomacromolecules (2 papers)Essays in Biochemistry (1 paper)Biosensors and Bioelectronics (1 paper)Molecular Cell (1 paper)
- Partner nations
- United KingdomGermanySweden
In The Last Decade
Tom Scheidt
15 papers receiving 512 citations
Peers
Comparison fields: 5 of 64
- Physiology 261
- Biomaterials 59
- Biological Psychiatry 10
- Molecular Biology 298
- Pharmacology 48
Countries citing papers authored by Tom Scheidt
This map shows the geographic impact of Tom Scheidt'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 Tom Scheidt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Scheidt more than expected).
Fields of papers citing papers by Tom Scheidt
This network shows the impact of papers produced by Tom Scheidt. 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 Tom Scheidt. The network helps show where Tom Scheidt may publish in the future.
Co-authors
The 25 scholars most cited alongside Tom Scheidt, 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 | 158 | |
| 2 | 2019 | 128 | |
| 3 | 2020 | 73 | |
| 4 | 2018 | 28 | |
| 5 | 2020 | 25 | |
| 6 | 2021 | 19 | |
| 7 | 2021 | 18 | |
| 8 | 2016 | 17 | |
| 9 | 2021 | 12 | |
| 10 | 2023 | 9 | |
| 11 | 2021 | 9 | |
| 12 | 2020 | 7 | |
| 13 | 2024 | 5 | |
| 14 | 2024 | 5 | |
| 15 | 2023 | 1 | |
| 16 | 2026 | 0 |
About Tom Scheidt
Tom Scheidt is a scholar working on Molecular Biology, Physiology, Radiology, Nuclear Medicine and Imaging, Ecology and Computational Theory and Mathematics, having authored 16 papers that have together received 514 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), RNA Research and Splicing (4 papers), Alzheimer's disease research and treatments (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Heat shock proteins research (2 papers), S100 Proteins and Annexins (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Physiology (261 citations), Biomaterials (59 citations), Biological Psychiatry (10 citations), Molecular Biology (298 citations) and Pharmacology (48 citations). Tom Scheidt has collaborated with scholars based in United Kingdom, Germany and Sweden. Frequent co-authors include Tuomas P. J. Knowles, Christopher M. Dobson, Michele Vendruscolo, Samuel I. A. Cohen, Sara Linse, Georg Meisl, Paolo Arosio, Catherine K. Xu, Daniel R. Whiten and David Klenerman. Their work appears in journals such as Proceedings of the National Academy of Sciences, Biomacromolecules, Essays in Biochemistry, Biosensors and Bioelectronics and Molecular 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.