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Ricard Solé1,2,3,4, Sergi Valverde4,5

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Summary
This summary is machine-generated.

Complex systems networks, from cellular to ecological, often show similar architectures. Reuse and amplification, not just selection, may drive the evolution of these network structures.

Keywords:
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Area of Science:

  • Complex Systems Science
  • Network Theory
  • Evolutionary Biology
  • Systems Biology

Background:

  • Complex systems are characterized by interacting parts organized into networks.
  • Network topology, rather than individual components, often dictates system properties.
  • Biological and artificial networks share common traits like heterogeneity, sparseness, nestedness, modularity, and hierarchy.

Purpose of the Study:

  • To investigate whether the topological organization of complex networks offers insights into their evolutionary origins.
  • To challenge the conventional view that network architectures are solely shaped by selection for functional traits.
  • To explore the role of 'tinkering' (reuse and amplification) in shaping network architecture across different domains.

Main Methods:

  • Analysis of generative network models, including duplication-rewiring rules.
  • Examination of evidence for 'tinkering' in cellular, technological, and ecological networks.
  • Comparative study of network architectures across biological and artificial systems.

Main Results:

  • Generative network models demonstrate that complex patterns (heterogeneity, scale-free, modularity) can emerge from simple rules like duplication and rewiring, independent of explicit functionality.
  • Evidence suggests that 'tinkering' processes, involving reuse and amplification, play a significant role in shaping network topology.
  • Observed network architectures may arise from inherent generative processes rather than solely from adaptive selection.

Conclusions:

  • The study questions the primacy of selection as the sole driver of network topology.
  • Amplification processes associated with reuse are proposed as a key mechanism shaping network graphs.
  • In biological systems, natural selection may act upon, rather than solely create, these emergent network patterns.