The Physics behind Systems Biology

Radde, Nicole; Hütt, Marc‐Thorsten

doi:10.1140/epjnbp/s40366-016-0034-8

Cited by 9 publications

(5 citation statements)

References 148 publications

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“…In general, we expect that our network reconstruction can serve as a relevant data resource for the application of methods from the analysis of multiplex [70] and other multilayer networks [20, 71]. Recently, there has been a growing interest in the properties of these systems, especially in the presence of explicit interdependencies between vertices [70, 72].…”

Section: Discussionmentioning

confidence: 99%

“…The overlap of structural and biological relevance, here, suggests that a careful analysis of such a structural model can guide biological investigations by focusing on a limited number of structurally outstanding components. This network model can also serve as a starting point for a range of topological analyses with methods developed in statistical physics (see, e.g., [19] for a recent review).…”

Section: Enzymementioning

confidence: 99%

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A system-wide network reconstruction of gene regulation and metabolism in Escherichia coli

et al. 2019

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Genome-scale metabolic models have become a fundamental tool for examining metabolic principles. However, metabolism is not solely characterized by the underlying biochemical reactions and catalyzing enzymes, but also affected by regulatory events. Since the pioneering work of Covert and co-workers as well as Shlomi and co-workers it is debated, how regulation and metabolism synergistically characterize a coherent cellular state. The first approaches started from metabolic models, which were extended by the regulation of the encoding genes of the catalyzing enzymes. By now, bioinformatics databases in principle allow addressing the challenge of integrating regulation and metabolism on a system-wide level. Collecting information from several databases we provide a network representation of the integrated gene regulatory and metabolic system for Escherichia coli , including major cellular processes, from metabolic processes via protein modification to a variety of regulatory events. Besides transcriptional regulation, we also take into account regulation of translation, enzyme activities and reactions. Our network model provides novel topological characterizations of system components based on their positions in the network. We show that network characteristics suggest a representation of the integrated system as three network domains (regulatory, metabolic and interface networks) instead of two. This new three-domain representation reveals the structural centrality of components with known high functional relevance. This integrated network can serve as a platform for understanding coherent cellular states as active subnetworks and to elucidate crossover effects between metabolism and gene regulation.

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Section: Discussionmentioning

confidence: 99%

Section: Enzymementioning

confidence: 99%

A system-wide network reconstruction of gene regulation and metabolism in Escherichia coli

et al. 2019

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“…It also bears similarity to random Boolean networks as minimal models of gene-regulatory systems, where discrete time and the reduced state space allow for an analysis of attractors and their robustness 26 , 27 . As such, our model is in the tradition of minimal models (or ’toy models’, ’stylized models’) in statistical physics 28 , 29 .…”

Section: Methodsmentioning

confidence: 99%

“…As with many other examples of minimal models or ’toy models’ in biology (see 28 , 44 , 45 ), the stylized nature of our model allows us to formally represent many features of a real-life system. In the following, we seek to study basic disease characteristics.…”

Section: Methodsmentioning

confidence: 99%

Network location and clustering of genetic mutations determine chronicity in a stylized model of genetic diseases

Nyczka

Falk

Hütt

2022

Sci Rep

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In a highly simplified view, a disease can be seen as the phenotype emerging from the interplay of genetic predisposition and fluctuating environmental stimuli. We formalize this situation in a minimal model, where a network (representing cellular regulation) serves as an interface between an input layer (representing environment) and an output layer (representing functional phenotype). Genetic predisposition for a disease is represented as a loss of function of some network nodes. Reduced, but non-zero, output indicates disease. The simplicity of this genetic disease model and its deep relationship to percolation theory allows us to understand the interplay between disease, network topology and the location and clusters of affected network nodes. We find that our model generates two different characteristics of diseases, which can be interpreted as chronic and acute diseases. In its stylized form, our model provides a new view on the relationship between genetic mutations and the type and severity of a disease.

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“…For two decades, statistical physics has been the core discipline contributing to the development of minimal models of graphs with specific statistical properties, novel characterizations of network topology, and fundamental relationships between network architecture and dynamics ( 1 , 13 – 16 ). This has led to a productive dialogue with a range of disciplines, where network concepts have been instrumental in unraveling some organizational principles of the respective systems.…”

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confidence: 99%

Link-usage asymmetry and collective patterns emerging from rich-club organization of complex networks

Moretti

Hütt

2020

Proc. Natl. Acad. Sci. U.S.A.

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In models of excitable dynamics on graphs, excitations can travel in both directions of an undirected link. However, as a striking interplay of dynamics and network topology, excitations often establish a directional preference. Some of these cases of “link-usage asymmetry” are local in nature and can be mechanistically understood, for instance, from the degree gradient of a link (i.e., the difference in node degrees at both ends of the link). Other contributions to the link-usage asymmetry are instead, as we show, self-organized in nature, and strictly nonlocal. This is the case for excitation waves, where the preferential propagation of excitations along a link depends on its orientation with respect to a hub acting as a source, even if the link in question is several steps away from the hub itself. Here, we identify and quantify the contribution of such self-organized patterns to link-usage asymmetry and show that they extend to ranges significantly longer than those ascribed to local patterns. We introduce a topological characterization, the hub-set-orientation prevalence of a link, which indicates its average orientation with respect to the hubs of a graph. Our numerical results show that the hub-set-orientation prevalence of a link strongly correlates with the preferential usage of the link in the direction of propagation away from the hub core of the graph. Our methodology is embedding-agnostic and allows for the measurement of wave signals and the sizes of the cores from which they originate.

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The Physics behind Systems Biology

Cited by 9 publications

References 148 publications

A system-wide network reconstruction of gene regulation and metabolism in Escherichia coli

A system-wide network reconstruction of gene regulation and metabolism in Escherichia coli

Network location and clustering of genetic mutations determine chronicity in a stylized model of genetic diseases

Link-usage asymmetry and collective patterns emerging from rich-club organization of complex networks

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