Stephan Eismann

1.7k total citations · 1 hit paper
12 papers, 824 citations indexed

About

Stephan Eismann is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Stephan Eismann has authored 12 papers receiving a total of 824 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 5 papers in Computational Theory and Mathematics and 5 papers in Materials Chemistry. Recurrent topics in Stephan Eismann's work include Protein Structure and Dynamics (5 papers), Machine Learning in Materials Science (5 papers) and Computational Drug Discovery Methods (4 papers). Stephan Eismann is often cited by papers focused on Protein Structure and Dynamics (5 papers), Machine Learning in Materials Science (5 papers) and Computational Drug Discovery Methods (4 papers). Stephan Eismann collaborates with scholars based in United States, Germany and United Kingdom. Stephan Eismann's co-authors include Ron O. Dror, Yanping Zhang, Benjamin F. Grewe, Cheng Huang, Jin Zhong Li, Yiyang Gong, Mark J. Schnitzer, Raphael J.L. Townshend, Rhiju Das and Masha Karelina and has published in prestigious journals such as Science, Biophysical Journal and Proteins Structure Function and Bioinformatics.

In The Last Decade

Stephan Eismann

12 papers receiving 809 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Geometric deep learning of RNA structure

2021 235 citations Raphael J.L. Townshend, Stephan Eismann et al. Science profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Stephan Eismann United States	7	480	324	124	111	77	12	824
Onur Dağliyan United States	20	821 1.7×	262 0.8×	38 0.3×	89 0.8×	64 0.8×	28	1.1k
Joel R. Stiles United States	17	718 1.5×	414 1.3×	153 1.2×	114 1.0×	58 0.8×	26	1.1k
Markus Dittrich United States	20	756 1.6×	381 1.2×	53 0.4×	69 0.6×	12 0.2×	29	1.1k
Srisairam Achuthan United States	14	299 0.6×	99 0.3×	176 1.4×	39 0.4×	21 0.3×	26	685
Gezhi Weng United States	12	657 1.4×	244 0.8×	51 0.4×	35 0.3×	39 0.5×	19	974
Nir Kalisman Israel	16	747 1.6×	155 0.5×	171 1.4×	46 0.4×	44 0.6×	30	1.3k
Abba E. Leffler United States	8	560 1.2×	278 0.9×	61 0.5×	13 0.1×	64 0.8×	15	841
Takefumi Morizumi Canada	24	1.6k 3.2×	1.3k 4.0×	67 0.5×	84 0.8×	60 0.8×	38	1.9k
Midori Murakami Japan	16	819 1.7×	930 2.9×	86 0.7×	20 0.2×	43 0.6×	23	1.2k

Countries citing papers authored by Stephan Eismann

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Stephan Eismann

This figure shows the co-authorship network connecting the top 25 collaborators of Stephan Eismann. A scholar is included among the top collaborators of Stephan Eismann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stephan Eismann. Stephan Eismann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

1.

Eismann, Stephan, et al.. (2023). Protein model quality assessment using rotation‐equivariant transformations on point clouds. Proteins Structure Function and Bioinformatics. 91(8). 1089–1096. 2 indexed citations

2.

Townshend, Raphael J.L., Stephan Eismann, Andrew M. Watkins, et al.. (2021). Geometric deep learning of RNA structure. Science. 373(6558). 1047–1051. 235 indexed citations breakdown →

3.

Eismann, Stephan, et al.. (2021). Learning from Protein Structure with Geometric Vector Perceptrons. arXiv (Cornell University). 1 indexed citations

4.

Suomivuori, Carl‐Mikael, Naomi R. Latorraca, Laura M. Wingler, et al.. (2020). Molecular mechanism of biased signaling in a prototypical G protein–coupled receptor. Science. 367(6480). 881–887. 167 indexed citations

5.

Eismann, Stephan, et al.. (2020). Hierarchical, rotation-equivariant neural networks to predict the structure of protein complexes. arXiv (Cornell University). 2 indexed citations

6.

Suomivuori, Carl‐Mikael, Naomi R. Latorraca, Laura M. Wingler, et al.. (2020). Molecular Mechanism of Biased Signaling in a Prototypical G-protein-coupled Receptor. Biophysical Journal. 118(3). 162a–162a. 17 indexed citations

7.

Eismann, Stephan, et al.. (2020). Hierarchical, rotation‐equivariant neural networks to select structural models of protein complexes. Proteins Structure Function and Bioinformatics. 89(5). 493–501. 35 indexed citations

8.

Hsieh, Jun-Ting, Shengjia Zhao, Stephan Eismann, Lucia Mirabella, & Stefano Ermon. (2019). Learning Neural PDE Solvers with Convergence Guarantees. arXiv (Cornell University). 20 indexed citations

9.

Eismann, Stephan, Daniel Lévy, Rui Shu, & Stefano Ermon. (2018). Bayesian optimization and attribute adjustment. PuSH - Publication Server of Helmholtz Zentrum München. 1042–1052. 2 indexed citations

10.

Bartzsch, Stefan, Craig Cummings, Stephan Eismann, & Uwe Oelfke. (2016). A preclinical microbeam facility with a conventional x‐ray tube. Medical Physics. 43(12). 6301–6308. 19 indexed citations

11.

Eismann, Stephan & Robert G. Endres. (2015). Protein Connectivity in Chemotaxis Receptor Complexes. PLoS Computational Biology. 11(12). e1004650–e1004650. 4 indexed citations

12.

Gong, Yiyang, Cheng Huang, Jin Zhong Li, et al.. (2015). High-speed recording of neural spikes in awake mice and flies with a fluorescent voltage sensor. Science. 350(6266). 1361–1366. 320 indexed citations

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.

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