Marc-Thorsten Hütt

Phone: +49 421 200 3238
Mail: m.huett (at) jacobs-university.de
Position: Professor

CV

Marc Hütt studied physics in Göttingen and Paris and received his PhD in Göttingen in 1997. Following longer research stays in Novosibirsk, Paris, Warsaw and Darmstadt, he became an Assistant Professor of Theoretical Biology and Bioinformatics in 2001 at Darmstadt University of Technology. In 2006 he moved to Jacobs University in Bremen, accepting a Professorship in Computational Systems Biology.

From 2000 to 2005 he was a member of “Die Junge Akademie” (an institution founded by Berlin-Brandenburgische Akademie der Wissenschaften and Deutschen Akademie der Naturforscher Leopoldina). Since 2019 he is a member of the European Academy of Sciences and Arts.

Research

Among his research interests is the development of mathematical tools for analyzing biological pattern formation, the analysis and modeling of large-scale statistical properties of genomes, as well as studying the link between topology and dynamics in biological networks.

He uses methods from nonlinear dynamics, the theory of complex networks and information theory, in order to analyze biological systems.

In particular, he has developed and applied network-based data analysis methods to metabolomics, proteomics and transcriptomics data.

Recent Publications

A network analysis of decision strategies of human experts in steel manufacturing
Daniel Christopher Merten , Marc-Thorsten Hütt , Yilmaz Uygun
Computers & Industrial Engineering, 2022.
Cite

Cite

                    @article{merten2022effect,
 author = {Merten, Daniel Christopher and Hütt, Marc-Thorsten and Uygun, Yilmaz},
 journal = {Computers & Industrial Engineering},
 pages = {108--120},
 title = {A network analysis of decision strategies of human experts in steel manufacturing},
 year = {2022}
}


                
Inferring missing edges in a graph from observed collective patterns
Selim Haj Ali , Marc-Thorsten Hütt
Physical Review E, 2022.
Cite

Cite

                    @article{hajaliInferringMissingEdges2022,
 abstract = {Many real-life networks are incomplete. Dynamical observations can allow estimating missing edges. Such procedures, often summarized under the term ‘network inference’, typically evaluate the statistical correlations among pairs of nodes to determine connectivity. Here, we offer an alternative approach: completing an incomplete network by observing its collective behavior. We illustrate this approach for the case of patterns emerging in reaction-diffusion systems on graphs, where collective behaviors can be associated with eigenvectors of the network's Laplacian matrix. Our method combines a partial spectral decomposition of the network's Laplacian matrix with eigenvalue assignment by matching the patterns to the eigenvectors of the incomplete graph. We show that knowledge of a few collective patterns can allow the prediction of missing edges and that this result holds across a range of network architectures. We present a numerical case study using activator-inhibitor dynamics and we illustrate that the main requirement for the observed patterns is that they are not confined to subsets of nodes, but involve the whole network.},
 author = {Haj Ali, Selim and Hütt, Marc-Thorsten},
 doi = {10.1103/PhysRevE.105.064610},
 file = {APS Snapshot:/home/johannes/.mozilla/firefox/5ah0aj87.default/zotero/storage/HS5VIBKF/PhysRevE.105.html:text/html;Full Text PDF:/home/johannes/.mozilla/firefox/5ah0aj87.default/zotero/storage/I3PDVLD8/Haj Ali und Hütt - 2022 - Inferring missing edges in a graph from observed c.pdf:application/pdf},
 journal = {Physical Review E},
 month = {June},
 note = {Publisher: American Physical Society},
 number = {6},
 pages = {064610},
 title = {Inferring missing edges in a graph from observed collective patterns},
 url = {https://link.aps.org/doi/10.1103/PhysRevE.105.064610},
 urldate = {2022-09-09},
 volume = {105},
 year = {2022}
}


                
Local topological features of robust supply networks
Alexey Lyutov , Yilmaz Uygun , Marc-Thorsten Hütt
Applied Network Science, 2022.
Cite

Cite

                    @article{lyutov2021local,
 author = {Lyutov, Alexey and Uygun, Yilmaz and Hütt, Marc-Thorsten},
 journal = {Applied Network Science},
 title = {Local topological features of robust supply networks},
 year = {2022}
}


                
Collective patterns and stable misunderstandings in networks striving for consensus without a common value system
Johannes Falk , Edwin Eichler , Katja Windt , Marc-Thorsten Hütt
Scientific Reports, 2022.
Cite

Cite

                    
@article{falkCollectivePatternsStable2022,
  title = {Collective Patterns and Stable Misunderstandings in Networks Striving for Consensus without a Common Value System},
  author = {Falk, Johannes and Eichler, Edwin and Windt, Katja and H{\"u}tt, Marc-Thorsten},
  year = {2022},
  month = feb,
  journal = {Scientific Reports},
  volume = {12},
  number = {1},
  pages = {3028},
  publisher = {{Nature Publishing Group}},
  issn = {2045-2322},
  doi = {10.1038/s41598-022-06880-7}
}




                
Cocoa bean fingerprinting via correlation networks
Santhust Kumar , Roy N D'Souza , Marcello Corno , Matthias S Ullrich , Nikolai Kuhnert , Marc-Thorsten Hütt
npj Science of Food, 2022.
Cite

Cite

                    @article{kumar2022cocoa,
 author = {Kumar, Santhust and D'Souza, Roy N and Corno, Marcello and Ullrich, Matthias S and Kuhnert, Nikolai and Hütt, Marc-Thorsten},
 journal = {npj Science of Food},
 number = {1},
 pages = {1--9},
 publisher = {Nature Publishing Group},
 title = {Cocoa bean fingerprinting via correlation networks},
 volume = {6},
 year = {2022}
}


                
Contribution of 3D genome topological domains to genetic risk of cancers: a genome-wide computational study
Kim Philipp Jablonski , Leopold Carron , Julien Mozziconacci , Thierry Forné , Marc-Thorsten Hütt , Annick Lesne
Human genomics, 2022.
Cite

Cite

                    @article{jablonski2022contribution,
 author = {Jablonski, Kim Philipp and Carron, Leopold and Mozziconacci, Julien and Forné, Thierry and Hütt, Marc-Thorsten and Lesne, Annick},
 date-modified = {2022-02-19 07:45:25 +0100},
 journal = {Human genomics},
 number = {1},
 pages = {1--15},
 publisher = {BioMed Central},
 title = {Contribution of 3D genome topological domains to genetic risk of cancers: a genome-wide computational study},
 volume = {16},
 year = {2022}
}


                
Effect of slab width on choice of appropriate casting speed in steel production
Daniel Christopher Merten , Marc-Thorsten Hütt , Yilmaz Uygun
Journal of Iron and Steel Research International, 2022.
Cite

Cite

                    @article{merten2022effect,
 author = {Merten, Daniel Christopher and Hütt, Marc-Thorsten and Uygun, Yilmaz},
 journal = {Journal of Iron and Steel Research International},
 pages = {1--9},
 publisher = {Springer Singapore},
 title = {Effect of slab width on choice of appropriate casting speed in steel production},
 year = {2022}
}


                
Exploring cocoa bean fermentation mechanisms by kinetic modelling
Mauricio Moreno-Zambrano , Matthias S Ullrich , Marc-Thorsten Hütt
Royal Society Open Science, 2022.
Cite

Cite

                    @article{moreno2022exploring,
 author = {Moreno-Zambrano, Mauricio and Ullrich, Matthias S and Hütt, Marc-Thorsten},
 journal = {Royal Society Open Science},
 publisher = {The Royal Society},
 title = {Exploring cocoa bean fermentation mechanisms by kinetic modelling},
 year = {2022}
}


                
Paleometagenomic network analysis of ancient DNA from Bering Sea sediments to examine past ecological communities
Viktor Dinkel , Stella Zora Buchwald , Kathleen Stoof-Leichsenring , Marc-Thorsten Hütt , Dirk Nürnberg , Ulrike Herzschuh
2022.
Cite

Cite

                    @techreport{dinkel2022paleometagenomic,
 author = {Dinkel, Viktor and Buchwald, Stella Zora and Stoof-Leichsenring, Kathleen and Hütt, Marc-Thorsten and Nürnberg, Dirk and Herzschuh, Ulrike},
 institution = {Copernicus Meetings},
 title = {Paleometagenomic network analysis of ancient DNA from Bering Sea sediments to examine past ecological communities},
 year = {2022}
}


                
Predictable topological sensitivity of Turing patterns on graphs
Marc-Thorsten Hütt , Dieter Armbruster , Annick Lesne
Physical Review E, 2022.
Cite

Cite

                    @article{hutt2022predictable,
 author = {Hütt, Marc-Thorsten and Armbruster, Dieter and Lesne, Annick},
 date-modified = {2022-02-19 07:45:12 +0100},
 journal = {Physical Review E},
 number = {1},
 pages = {014304},
 publisher = {American Physical Society},
 title = {Predictable topological sensitivity of Turing patterns on graphs},
 volume = {105},
 year = {2022}
}