Marc‐Thorsten Hütt

2.8k total citations
108 papers, 1.6k citations indexed

About

Marc‐Thorsten Hütt is a scholar working on Molecular Biology, Statistical and Nonlinear Physics and Computer Networks and Communications. According to data from OpenAlex, Marc‐Thorsten Hütt has authored 108 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Molecular Biology, 28 papers in Statistical and Nonlinear Physics and 16 papers in Computer Networks and Communications. Recurrent topics in Marc‐Thorsten Hütt's work include Gene Regulatory Network Analysis (31 papers), Bioinformatics and Genomic Networks (24 papers) and Complex Network Analysis Techniques (18 papers). Marc‐Thorsten Hütt is often cited by papers focused on Gene Regulatory Network Analysis (31 papers), Bioinformatics and Genomic Networks (24 papers) and Complex Network Analysis Techniques (18 papers). Marc‐Thorsten Hütt collaborates with scholars based in Germany, United States and France. Marc‐Thorsten Hütt's co-authors include Claus C. Hilgetag, Carsten Marr, Mark Müller‐Linow, Georgi Muskhelishvili, Yılmaz Uygun, Marcel Geertz, Nikolaus Sonnenschein, Julia Bendul, Annick Lesne and Atilla Özgür and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.

In The Last Decade

Marc‐Thorsten Hütt

103 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marc‐Thorsten Hütt Germany 22 601 285 277 173 166 108 1.6k
Baruch Barzel Israel 17 502 0.8× 241 0.8× 985 3.6× 105 0.6× 327 2.0× 44 2.2k
Fernando J. Pineda United States 18 826 1.4× 175 0.6× 136 0.5× 63 0.4× 103 0.6× 40 2.2k
José F. Fontanari Brazil 21 214 0.4× 336 1.2× 305 1.1× 427 2.5× 66 0.4× 154 1.5k
Peter Dittrich Germany 25 1.2k 2.0× 102 0.4× 95 0.3× 178 1.0× 129 0.8× 102 2.0k
David C. Wood United States 22 593 1.0× 43 0.2× 82 0.3× 78 0.5× 157 0.9× 64 1.4k
Michael A. Langston United States 33 1.5k 2.5× 90 0.3× 155 0.6× 549 3.2× 609 3.7× 182 4.2k
Juan Carlos Nuño Spain 15 556 0.9× 238 0.8× 500 1.8× 138 0.8× 169 1.0× 44 1.9k
Minping Qian China 18 571 1.0× 86 0.3× 341 1.2× 147 0.8× 51 0.3× 77 1.1k
Zi‐Gang Huang China 22 139 0.2× 188 0.7× 477 1.7× 351 2.0× 272 1.6× 87 1.7k
Daniel Marbach Switzerland 17 2.9k 4.9× 91 0.3× 116 0.4× 389 2.2× 52 0.3× 29 3.6k

Countries citing papers authored by Marc‐Thorsten Hütt

Since Specialization
Citations

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

Fields of papers citing papers by Marc‐Thorsten Hütt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marc‐Thorsten Hütt. 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 Marc‐Thorsten Hütt. The network helps show where Marc‐Thorsten Hütt may publish in the future.

Co-authorship network of co-authors of Marc‐Thorsten Hütt

This figure shows the co-authorship network connecting the top 25 collaborators of Marc‐Thorsten Hütt. A scholar is included among the top collaborators of Marc‐Thorsten Hütt 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 Marc‐Thorsten Hütt. Marc‐Thorsten Hütt 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.
Messé, Arnaud, Marc‐Thorsten Hütt, & Claus C. Hilgetag. (2025). Excitable dynamics simplify neural connectomes. Cell Reports Physical Science. 6(4). 102510–102510.
2.
Uygun, Yılmaz, et al.. (2024). Machine learning misclassification networks reveal a citation advantage of interdisciplinary publications only in high-impact journals. Scientific Reports. 14(1). 21906–21906. 6 indexed citations
3.
Hütt, Marc‐Thorsten, et al.. (2023). The attractor structure of functional connectivity in coupled logistic maps. Chaos An Interdisciplinary Journal of Nonlinear Science. 33(8). 1 indexed citations
4.
Windt, Katja, et al.. (2023). STRUCTURAL INSULATORS AND PROMOTORS IN NETWORKS UNDER GENERIC PROBLEM-SOLVING DYNAMICS. Advances in Complex Systems. 26(07n08).
5.
Zimmermann, Heike, Kathleen R. Stoof‐Leichsenring, Lars Harms, et al.. (2023). Marine ecosystem shifts with deglacial sea-ice loss inferred from ancient DNA shotgun sequencing. Nature Communications. 14(1). 1650–1650. 18 indexed citations
6.
Hütt, Marc‐Thorsten, et al.. (2022). Inferring missing edges in a graph from observed collective patterns. Physical review. E. 105(6). 64610–64610. 2 indexed citations
7.
Hütt, Marc‐Thorsten, Dieter Armbruster, & Annick Lesne. (2022). Predictable topological sensitivity of Turing patterns on graphs. Physical review. E. 105(1). 10 indexed citations
8.
Ullrich, Matthias S., et al.. (2022). Exploring cocoa bean fermentation mechanisms by kinetic modelling. Royal Society Open Science. 9(2). 210274–210274. 5 indexed citations
9.
Dsouza, Roy N., et al.. (2022). Cocoa bean fingerprinting via correlation networks. npj Science of Food. 6(1). 5–5. 5 indexed citations
10.
Lesne, Annick, et al.. (2021). The economy of chromosomal distances in bacterial gene regulation. npj Systems Biology and Applications. 7(1). 49–49. 3 indexed citations
11.
Nyczka, Piotr & Marc‐Thorsten Hütt. (2020). Generative network model of transcriptome patterns in disease cohorts with tunable signal strength. Physical Review Research. 2(3). 2 indexed citations
12.
Bornholdt, Stefan, et al.. (2019). A system-wide network reconstruction of gene regulation and metabolism in Escherichia coli. PLoS Computational Biology. 15(5). e1006962–e1006962. 11 indexed citations
13.
Hütt, Marc‐Thorsten, et al.. (2019). Economy-on-demand and the fairness of algorithms. European Labour Law Journal. 10(1). 3–16. 4 indexed citations
14.
Enders, Martin, Marc‐Thorsten Hütt, & Jonathan M. Jeschke. (2018). Drawing a map of invasion biology based on a network of hypotheses. Ecosphere. 9(3). 44 indexed citations
15.
Ullrich, Matthias S., et al.. (2018). A mathematical model of cocoa bean fermentation. Royal Society Open Science. 5(10). 180964–180964. 22 indexed citations
16.
Lesne, Annick, et al.. (2017). Topological determinants of self-sustained activity in a simple model of excitable dynamics on graphs. Scientific Reports. 7(1). 42340–42340. 10 indexed citations
17.
Häsler, Robert, Raheleh Sheibani‐Tezerji, Anupam Sinha, et al.. (2016). Uncoupling of mucosal gene regulation, mRNA splicing and adherent microbiota signatures in inflammatory bowel disease. Gut. 66(12). 2087–2097. 54 indexed citations
18.
Hütt, Marc‐Thorsten, et al.. (2015). The elementary flux modes of a manufacturing system: a novel approach to explore the relationship of network structure and function. International Journal of Production Research. 54(14). 4145–4160. 6 indexed citations
19.
Hilgetag, Claus C. & Marc‐Thorsten Hütt. (2013). Hierarchical modular brain connectivity is a stretch for criticality. Trends in Cognitive Sciences. 18(3). 114–115. 34 indexed citations
20.
Marr, Carsten, Marcel Geertz, Marc‐Thorsten Hütt, & Georgi Muskhelishvili. (2008). Dissecting the logical types of network control in gene expression profiles. BMC Systems Biology. 2(1). 18–18. 71 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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