7 results match your criteria: "Germany. M.Huett@jacobs-university.de.[Affiliation]"

Cocoa bean fingerprinting via correlation networks.

NPJ Sci Food

January 2022

Department of Life Sciences and Chemistry, Jacobs University Bremen, Campus Ring 1, 28759, Bremen, Germany.

Cocoa products have a remarkable chemical and sensory complexity. However, in contrast to other fermentation processes in the food industry, cocoa bean fermentation is left essentially uncontrolled and is devoid of standardization. Questions of food authenticity and food quality are hence particularly challenging for cocoa.

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Background: Genome-wide association studies have identified statistical associations between various diseases, including cancers, and a large number of single-nucleotide polymorphisms (SNPs). However, they provide no direct explanation of the mechanisms underlying the association. Based on the recent discovery that changes in three-dimensional genome organization may have functional consequences on gene regulation favoring diseases, we investigated systematically the genome-wide distribution of disease-associated SNPs with respect to a specific feature of 3D genome organization: topologically associating domains (TADs) and their borders.

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The economy of chromosomal distances in bacterial gene regulation.

NPJ Syst Biol Appl

December 2021

Department of Life Sciences and Chemistry, Jacobs University, D-28759, Bremen, Germany.

In the transcriptional regulatory network (TRN) of a bacterium, the nodes are genes and a directed edge represents the action of a transcription factor (TF), encoded by the source gene, on the target gene. It is a condensed representation of a large number of biological observations and facts. Nonrandom features of the network are structural evidence of requirements for a reliable systemic function.

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For a long time it has been hypothesized that bacterial gene regulation involves an intricate interplay of the transcriptional regulatory network (TRN) and the spatial organization of genes in the chromosome. Here we explore this hypothesis both on a structural and on a functional level. On the structural level, we study the TRN as a spatially embedded network.

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The interdependent network of gene regulation and metabolism is robust where it needs to be.

Nat Commun

September 2017

Department of Life Sciences and Chemistry, Jacobs University, Campus Ring 1, 28759, Bremen, Germany.

Despite being highly interdependent, the major biochemical networks of the living cell-the networks of interacting genes and of metabolic reactions, respectively-have been approached mostly as separate systems so far. Recently, a framework for interdependent networks has emerged in the context of statistical physics. In a first quantitative application of this framework to systems biology, here we study the interdependent network of gene regulation and metabolism for the model organism Escherichia coli in terms of a biologically motivated percolation model.

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Effect of database drift on network topology and enrichment analyses: a case study for RegulonDB.

Database (Oxford)

October 2016

Department of Life Sciences and Chemistry, Jacobs University, Campus Ring 1, Bremen 28759, Germany and

RegulonDB is a database storing the biological information behind the transcriptional regulatory network (TRN) of the bacterium Escherichia coli. It is one of the key bioinformatics resources for Systems Biology investigations of bacterial gene regulation. Like most biological databases, the content drifts with time, both due to the accumulation of new information and due to refinements in the underlying biological concepts.

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Perspective: network-guided pattern formation of neural dynamics.

Philos Trans R Soc Lond B Biol Sci

October 2014

Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg, Germany Department of Health Sciences, Boston University, Boston, MA, USA.

The understanding of neural activity patterns is fundamentally linked to an understanding of how the brain's network architecture shapes dynamical processes. Established approaches rely mostly on deviations of a given network from certain classes of random graphs. Hypotheses about the supposed role of prominent topological features (for instance, the roles of modularity, network motifs or hierarchical network organization) are derived from these deviations.

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