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Organisms persist by matching process networks to environmental constraints. Optimal reliability in unreliable networks emerges when modular structures align with constraint hierarchies, maximizing organism survival.

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Area of Science:

  • Systems biology
  • Theoretical biology
  • Network science

Background:

  • Organisms must meet internal and external constraints to persist.
  • Networks of processes within organisms manage these constraints.
  • A common principle is matching: process coupling patterns mirror constraint correlations.

Purpose of the Study:

  • To investigate if an optimality criterion predicts the matching principle in biological networks.
  • To explore the reliability of modular versus non-modular networks under unreliable process conditions.

Main Methods:

  • Simulated an ensemble of networks with unreliable component processes.
  • Analyzed network reliability based on modularity and constraint matching.
  • Examined the relationship between process success probability and network reliability.

Main Results:

  • Networks achieving the highest reliability adhered to the matching principle.
  • The reliability difference between modular and non-modular networks depends on process success probability.
  • This reliability difference peaks at a specific process success probability.

Conclusions:

  • Optimality principles, specifically reliability, predict the matching of network structure to constraints.
  • Modular network design enhances reliability, particularly when individual processes are prone to failure.
  • The optimal degree of modularity is influenced by the number of processes and their individual success rates.