The role of modularity in self-organisation dynamics in biological networks

Abstract

Interconnected ensembles of biological entities are perhaps some of the most complex systems that modern science has encountered so far. In particular, scientists have concentrated on understanding how the complexity of the interacting structure between different neurons, proteins or species influences the functioning of their respective systems. It is well-established that many biological networks are constructed in a highly hierarchical way with two main properties: short average paths that join two apparently distant nodes (neuronal, species, or protein patches) and a high proportion of nodes in modular aggregations. Although several hypotheses have been proposed so far, still little is known about the relation of the modules with the dynamical activity in such biological systems. Here we show that network modularity is a key ingredient for the formation of self-organising patterns of functional activity, independently of the topological peculiarities of the structure of the modules. In particular, we propose a self-organising mechanism which explains the formation of macroscopic spatial patterns, which are homogeneous within modules. This may explain how spontaneous order in biological networks follows their modular structural organisation. We test our results on real-world networks to confirm the important role of modularity in creating macro-scale patterns.

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Cited by in corpus (7)

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• Emergence of geometric Turing patterns in complex networks
• Symmetry-breaking mechanism for the formation of cluster chimera patterns
• Non-reciprocal interactions enhance heterogeneity
• Persistence of chimera states and the challenge for synchronization in real-world networks
• Effect of clustering on Turing instability in complex networks
• Finite propagation enhances Turing patterns in reaction-diffusion networked systems