Modular Gene Dynamics and Network Theory at Mesoscopic Scale
Zoran Levnaji\'c

TL;DR
This paper investigates the stability and emergent dynamics of gene regulatory networks modeled as coupled chaotic maps, focusing on mesoscale motifs like 4-star subgraphs to understand large-scale cooperativity.
Contribution
It introduces a novel analysis of mesoscale network motifs, specifically 4-star subgraphs, in the context of coupled chaotic maps with time delay, linking mesoscale patterns to global network behavior.
Findings
Mesoscale motifs influence overall network stability.
Time delay affects the emergence of cooperative dynamics.
Large-scale network behavior can be predicted from mesoscale patterns.
Abstract
Complex dynamical systems are often modeled as networks, with nodes representing dynamical units which interact through the network's links. Gene regulatory networks, responsible for the production of proteins inside a cell, are an example of system that can be described as a network of interacting genes. The behavior of a complex dynamical system is characterized by cooperativity of its units at various scales, leading to emergent dynamics which is related to the system's function. Among the key problems concerning complex systems is the issue of stability of their functioning, in relation to different internal and external interaction parameters. In this Thesis we study two-dimensional chaotic maps coupled through non-directed networks with different topologies. We use a non-symplectic coupling which involves a time delay in the interaction among the maps. We test the stability of…
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Taxonomy
TopicsGene Regulatory Network Analysis · Bioinformatics and Genomic Networks · Evolution and Genetic Dynamics
