Stephan Eismann
Impact in
- Biophysics top 2%
- Advanced Fluorescence Microscopy Techniques
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- Photoreceptor and optogenetics research
- Neuroscience and Neural Engineering
Papers in
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- Protein Structure and Dynamics 5
- Receptor Mechanisms and Signaling 2
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- Computational Drug Discovery Methods 4
- Co-authors
- Ron O. Dror (7 shared papers)Benjamin F. Grewe (1 shared paper)Jin Zhong Li (1 shared paper)Cheng Huang (1 shared paper)Yiyang Gong (1 shared paper)Yanping Zhang (1 shared paper)Mark J. Schnitzer (1 shared paper)Raphael J.L. Townshend (4 shared papers)
- Journals
- Science (3 papers)Proteins Structure Function and Bioinformatics (2 papers)Medical Physics (1 paper)Biophysical Journal (1 paper)PLoS Computational Biology (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Stephan Eismann
12 papers receiving 861 citations
Stephan Eismann's Hit Papers
Peers
Comparison fields: 5 of 107
- Biophysics 115
- Cellular and Molecular Neuroscience 332
- Molecular Biology 495
- Cognitive Neuroscience 127
- Structural Biology 9
Countries citing papers authored by Stephan Eismann
This map shows the geographic impact of Stephan Eismann'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 Stephan Eismann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephan Eismann more than expected).
Fields of papers citing papers by Stephan Eismann
This network shows the impact of papers produced by Stephan Eismann. 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 Stephan Eismann. The network helps show where Stephan Eismann may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephan Eismann, 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 | 2015 | 343 | |
| 2 | Geometric deep learning of RNA structure Hit paper breakdown → | 2021 | 252 |
| 3 | 2020 | 175 | |
| 4 | 2020 | 37 | |
| 5 | 2019 | 22 | |
| 6 | 2016 | 19 | |
| 7 | 2020 | 17 | |
| 8 | 2015 | 5 | |
| 9 | 2023 | 3 | |
| 10 | Hierarchical, rotation-equivariant neural networks to predict the structure of protein complexes | 2020 | 2 |
| 11 | Bayesian optimization and attribute adjustment | 2018 | 2 |
| 12 | Learning from Protein Structure with Geometric Vector Perceptrons | 2021 | 1 |
About Stephan Eismann
Stephan Eismann is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Cellular and Molecular Neuroscience and Spectroscopy, having authored 12 papers that have together received 878 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), Machine Learning in Materials Science (5 papers), Computational Drug Discovery Methods (4 papers), Receptor Mechanisms and Signaling (2 papers), Mass Spectrometry Techniques and Applications (2 papers), Numerical methods for differential equations (1 paper), Neuroscience and Neural Engineering (1 paper) and Enzyme Structure and Function (1 paper). The work is most often cited by research in Biophysics (115 citations), Cellular and Molecular Neuroscience (332 citations), Molecular Biology (495 citations), Cognitive Neuroscience (127 citations) and Structural Biology (9 citations). Stephan Eismann has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Ron O. Dror, Benjamin F. Grewe, Jin Zhong Li, Cheng Huang, Yiyang Gong, Yanping Zhang, Mark J. Schnitzer, Raphael J.L. Townshend, Rhiju Das and Masha Karelina. Their work appears in journals such as Science, Proteins Structure Function and Bioinformatics, Medical Physics, Biophysical Journal and PLoS Computational 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.