Stephan Heyse

1.1k total citations
23 papers, 849 citations indexed

About

Stephan Heyse is a scholar working on Molecular Biology, Computational Theory and Mathematics and Biophysics. According to data from OpenAlex, Stephan Heyse has authored 23 papers receiving a total of 849 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 6 papers in Computational Theory and Mathematics and 6 papers in Biophysics. Recurrent topics in Stephan Heyse's work include Computational Drug Discovery Methods (6 papers), Cell Image Analysis Techniques (6 papers) and Lipid Membrane Structure and Behavior (3 papers). Stephan Heyse is often cited by papers focused on Computational Drug Discovery Methods (6 papers), Cell Image Analysis Techniques (6 papers) and Lipid Membrane Structure and Behavior (3 papers). Stephan Heyse collaborates with scholars based in Switzerland, Germany and United Kingdom. Stephan Heyse's co-authors include Horst Vogel, Oliver P. Ernst, Klaus Peter Hofmann, W. Stürmer, Hans‐Jürgen Apell, Jeremy H. Lakey, Thierry Storà, E Schmid, Michael J. Sanger and Hans Sigrist and has published in prestigious journals such as Journal of Biological Chemistry, Nature Biotechnology and Biochemistry.

In The Last Decade

Stephan Heyse

20 papers receiving 823 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephan Heyse Switzerland 9 657 176 125 124 114 23 849
Raik Grünberg Saudi Arabia 15 930 1.4× 295 1.7× 97 0.8× 72 0.6× 191 1.7× 34 1.3k
Amanda Kussrow United States 15 428 0.7× 201 1.1× 93 0.7× 89 0.7× 127 1.1× 30 709
N. H. Fontaine United States 8 277 0.4× 165 0.9× 91 0.7× 155 1.3× 207 1.8× 10 604
Rongfu Zhang China 16 307 0.5× 129 0.7× 60 0.5× 118 1.0× 107 0.9× 55 827
Max Sonnleitner Austria 14 586 0.9× 172 1.0× 30 0.2× 102 0.8× 73 0.6× 28 822
Tsutomu Mikawa Japan 22 1.1k 1.6× 197 1.1× 55 0.4× 19 0.2× 163 1.4× 58 1.5k
Radek Macháň Czechia 14 519 0.8× 156 0.9× 47 0.4× 147 1.2× 43 0.4× 25 797
Ekaterina Zaitseva Germany 12 605 0.9× 78 0.4× 57 0.5× 94 0.8× 59 0.5× 26 793
Wan‐Chen Lin United States 22 941 1.4× 260 1.5× 52 0.4× 254 2.0× 38 0.3× 37 1.4k
Ewa Heyduk United States 22 1.3k 1.9× 224 1.3× 70 0.6× 22 0.2× 65 0.6× 39 1.5k

Countries citing papers authored by Stephan Heyse

Since Specialization
Citations

This map shows the geographic impact of Stephan Heyse'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 Heyse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephan Heyse more than expected).

Fields of papers citing papers by Stephan Heyse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephan Heyse. 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 Heyse. The network helps show where Stephan Heyse may publish in the future.

Co-authorship network of co-authors of Stephan Heyse

This figure shows the co-authorship network connecting the top 25 collaborators of Stephan Heyse. A scholar is included among the top collaborators of Stephan Heyse 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 Heyse. Stephan Heyse is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Heyse, Stephan, et al.. (2025). PCIM: Learning pixel attributions via pixel-wise channel isolation mixing in high content imaging. SLAS DISCOVERY. 37. 100287–100287.
3.
Heyse, Stephan, et al.. (2024). A robust CETSA data analysis automation workflow for routine screening. SLAS DISCOVERY. 29(5). 100172–100172.
4.
Srinivasan, Bharath, Xiang Zhai, Guillaume Lemercier, et al.. (2022). High-throughput mechanistic screening of non-equilibrium inhibitors by a fully automated data analysis pipeline in early drug-discovery. SLAS DISCOVERY. 27(8). 460–470. 3 indexed citations
5.
Li, Tianbo, et al.. (2022). An efficient and scalable data analysis solution for automated electrophysiology platforms. SLAS DISCOVERY. 27(4). 278–285. 1 indexed citations
6.
Heyse, Stephan, et al.. (2022). Benchmarking feature selection methods for compressing image information in high-content screening. SLAS TECHNOLOGY. 27(1). 85–93. 6 indexed citations
7.
Steigele, Stephan, et al.. (2020). Deep Learning-Based HCS Image Analysis for the Enterprise. SLAS DISCOVERY. 25(7). 812–821. 7 indexed citations
8.
Li, Tianbo, Martin Ginkel, Renee Emkey, et al.. (2020). Efficient and Highly Scalable Mechanistic Characterization of Ion Channel Function in Drug Discovery. Biophysical Journal. 118(3). 579a–579a. 1 indexed citations
9.
Heyse, Stephan, et al.. (2020). Uncertainty with deep learning: a practical view on out of distribution detection. 65–66. 2 indexed citations
10.
Heyse, Stephan, et al.. (2018). Developing Deep Learning Applications for Life Science and Pharma Industry. Drug Research. 68(6). 305–310. 7 indexed citations
11.
Dahl, Göran, Stephan Steigele, Alexander Mehrle, et al.. (2016). Unified Software Solution for Efficient SPR Data Analysis in Drug Research. SLAS DISCOVERY. 22(2). 203–211. 4 indexed citations
12.
Sterling, John, Dejan Bojanic, Richard M. Eglen, Stephan Heyse, & Berta Strulovici. (2008). Current Trends in High-Throughput Screening. Assay and Drug Development Technologies. 6(4). 491–504. 3 indexed citations
13.
Dürr, Oliver, et al.. (2007). Robust Hit Identification by Quality Assurance and Multivariate Data Analysis of a High-Content, Cell-Based Assay. SLAS DISCOVERY. 12(8). 1042–1049. 31 indexed citations
14.
Heyse, Stephan, Tobe Freeman, T. Jung, et al.. (2005). Quantifying Bioactivity on a Large Scale: Quality Assurance and Analysis of Multiparametric Ultra-HTS Data. JALA Journal of the Association for Laboratory Automation. 10(4). 207–212. 5 indexed citations
15.
Heyse, Stephan. (2002). <title>Comprehensive analysis of high-throughput screening data</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4626. 535–547. 13 indexed citations
16.
Ernst, Oliver P., et al.. (1999). Micropatterned immobilization of a G protein–coupled receptor and direct detection of G protein activation. Nature Biotechnology. 17(11). 1105–1108. 226 indexed citations
17.
Heyse, Stephan, Thierry Storà, E Schmid, Jeremy H. Lakey, & Horst Vogel. (1998). Emerging techniques for investigating molecular interactions at lipid membranes. Biochimica et Biophysica Acta (BBA) - Reviews on Biomembranes. 1376(3). 319–338. 110 indexed citations
18.
Heyse, Stephan, Horst Vogel, I. W. Marison, et al.. (1996). Antigen Binding Properties of Purified Immunoglobulin A and Reconstituted Secretory Immunoglobulin A Antibodies. Journal of Biological Chemistry. 271(27). 16300–16309. 56 indexed citations
19.
Heyse, Stephan, Horst Vogel, Michael J. Sanger, & Hans Sigrist. (1995). Covalent attachment of functionalized lipid bilayers to planar waveguides for measuring protein binding to biomimetic membranes. Protein Science. 4(12). 2532–2544. 75 indexed citations
20.
Heyse, Stephan, et al.. (1994). Partial reactions of the Na,K-ATPase: determination of rate constants.. The Journal of General Physiology. 104(2). 197–240. 137 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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