Nonlinear Dynamical Systems Interacting in Complex Networks
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 44
Special Issue Editor
Special Issue Information
Dear Colleagues,
We stand at a pivotal moment in the study of complex systems, where an unprecedented wealth of data is refining our understanding of real-world network topology and establishing network science as one of the most powerful unifying tools for analyzing complex dynamics. Since the seminal discovery of the ubiquity of scale-free networks, it has become clear that these seemingly static topological patterns are far from arbitrary—they bear the imprint of underlying dynamical processes and the evolutionary histories that shape them, regardless of their respective domains.
Yet, the dynamism of networks extends far beyond their shifting topology. Many of the most complex systems they describe—such as social interactions and gene regulatory networks—operate on principles of preferential connectivity rather than simple physical links, often independent of spatial proximity. More than perhaps any other mathematical framework, networks provide a means to quantitatively study how physical interactions give rise to information processing.
Nowhere is this clearer than in gene regulatory networks, where biophysical processes translate raw molecular interactions into intricate systems of control and adaptation. Similar transformations are now unfolding in fields such as ecology, sociology, and economics, where the growing availability of data is driving a unified, quantitative understanding of their dynamics and evolutionary trajectories. As these disciplines increasingly adopt the common language of network science to integrate dynamical concepts more cohesively, we have an unprecedented opportunity to investigate physical, biological, and social interactions within a truly unified framework.
Dr. Enrico Borriello
Guest Editor
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Keywords
- complex systems
- network science
- topology
- scale-free networks
- dynamical processes
- gene regulatory networks
- information processing
- data science
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