Stephan Eismann
Impact in
- Biophysics top 5%
- Advanced Fluorescence Microscopy Techniques
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- Photoreceptor and optogenetics research
- Neuroscience and Neural Engineering
Papers in
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- Computational Drug Discovery Methods 3
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- Protein Structure and Dynamics 3
- RNA modifications and cancer 2
- RNA and protein synthesis mechanisms 2
- Receptor Mechanisms and Signaling 2
- Genomics and Phylogenetic Studies 1
- Co-authors
- Ron O. Dror (5 shared papers)Jin Zhong Li (1 shared paper)Mark J. Schnitzer (1 shared paper)Cheng C. Huang (1 shared paper)Yanping Zhang (1 shared paper)Benjamin F. Grewe (1 shared paper)Yiyang Gong (1 shared paper)Raphael J.L. Townshend (3 shared papers)
- Journals
- Science (3 papers)Proteins Structure Function and Bioinformatics (2 papers)Biophysical Journal (1 paper)Nature Methods (1 paper)PLoS Computational Biology (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Stephan Eismann
10 papers receiving 921 citations
Stephan Eismann's Hit Papers
Peers
Comparison fields: 5 of 100
- Biophysics 118
- Cellular and Molecular Neuroscience 351
- Molecular Biology 560
- Cognitive Neuroscience 132
- Structural Biology 7
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 | 359 | |
| 2 | Geometric deep learning of RNA structure Hit paper breakdown → | 2021 | 270 |
| 3 | 2020 | 190 | |
| 4 | 2020 | 37 | |
| 5 | 2024 | 36 | |
| 6 | 2020 | 21 | |
| 7 | 2016 | 20 | |
| 8 | 2015 | 5 | |
| 9 | 2023 | 3 | |
| 10 | Bayesian optimization and attribute adjustment | 2018 | 2 |
About Stephan Eismann
Stephan Eismann is a scholar working on Computational Theory and Mathematics, Molecular Biology, Spectroscopy, Cellular and Molecular Neuroscience and Materials Chemistry, having authored 10 papers that have together received 943 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (3 papers), Protein Structure and Dynamics (3 papers), Computational Drug Discovery Methods (3 papers), RNA modifications and cancer (2 papers), Mass Spectrometry Techniques and Applications (2 papers), RNA and protein synthesis mechanisms (2 papers), Receptor Mechanisms and Signaling (2 papers) and Genomics and Phylogenetic Studies (1 paper). The work is most often cited by research in Biophysics (118 citations), Cellular and Molecular Neuroscience (351 citations), Molecular Biology (560 citations), Cognitive Neuroscience (132 citations) and Structural Biology (7 citations). Stephan Eismann has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Ron O. Dror, Jin Zhong Li, Mark J. Schnitzer, Cheng C. Huang, Yanping Zhang, Benjamin F. Grewe, Yiyang Gong, Raphael J.L. Townshend, Masha Karelina and Ramya Rangan. Their work appears in journals such as Science, Proteins Structure Function and Bioinformatics, Biophysical Journal, Nature Methods 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.