Evolution of regulatory networks towards adaptability and stability in a changing environment

Abstract

Diverse biological networks exhibit universal features distinguished from those of random networks, calling much attention to their origins and implications. Here we propose a minimal evolution model of Boolean regulatory networks, which evolve by selectively rewiring links towards enhancing adaptability to a changing environment and stability against dynamical perturbations. We find that sparse and heterogeneous connectivity patterns emerge, which show qualitative agreement with real transcriptional regulatory networks and metabolic networks. The characteristic scaling behavior of stability reflects the balance between robustness and flexibility. The scaling of fluctuation in the perturbation spread shows a dynamic crossover, which is analyzed by investigating separately the stochasticity of internal dynamics and the network structures different depending on the evolution pathways. Our study delineates how the ambivalent pressure of evolution shapes biological networks, which can be helpful for studying general complex systems interacting with environments.

11 pages, 6 Figures

References in corpus (10)

• Power-law distributions in empirical data
• Fluctuation scaling in complex systems: Taylor's law and beyond
• Scaling breakdown in flow fluctuations on complex networks
• Emergent Criticality from Co-evolution in Random Boolean Networks
• Damage Spreading and Criticality in Finite Random Dynamical Networks
• Chaotic Gene Regulatory Networks Can Be Robust Against Mutations and Noise
• Perturbation propagation in random and evolved Boolean networks
• Evolution of a population of random Boolean networks
• Broad edge of chaos in strongly heterogeneous Boolean networks
• Self-organization of heterogeneous topology and symmetry breaking in networks with adaptive thresholds and rewiring

Cited by in corpus (2)

• Skewness of local logarithmic exports
• The emergence of pseudo-stable states in network dynamics