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An example 32-bit genome containing three 8-bit genetic motifs. In Experiment 1, fitness of this genome would be the sum of values V of the 3 motifs, i.e. F = V A + V B + V C . In Experiment 2, its fitness would be the sum of interactions between the motifs, i.e. F = V AB + V AC + V BC .
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Recent studies have shown that repeated phase changes in large networks (dual phase evolution -DPE) play a role in the evolution of many kinds of systems. However, the contribution of DPE to the origin of modular adaptations remains to be demonstrated. Despite plausible arguments and suggestive evidence from natural systems, a clear proof of the ad...
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Citations
... The need for both local and global connections is apparent: predominantly global interactions lead to a single, densely connected super-module, whereas predominantly local interactions lead to fragmentation into separate sub-structures with no cross-connections. Further work [160] showed that the temporal separation of phases enhanced functional organization in simulated genomes, demonstrating that networks with simultaneous global and local connections (such as small worlds) do not lead to the same outcomes as DPE. ...
... What phenomena depend on such phases with a well-defined transition, and what can also be caused by stochastic occurrences of local and global interactions, such as in small-world networks? Research shows that distinct phases can lead to superior adaptation and self-organization in simple genetic systems, compared with stochastically occurring local and global interactions [160]. However, it remains unclear when and if this result applies in natural systems. ...
Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are typical of systems in different connectivity phases, as well as characteristics commonly associated with the phase transitions. We synthesize these common features into a common framework, which we term dual-phase evolution (DPE). Using this framework, we review the literature from several disciplines to show that recurrent connectivity phase transitions underlie the complex properties of many biological, physical and human systems. We argue that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality. Our review concludes with a discussion of the way DPE relates to other frameworks, in particular, self-organized criticality and the adaptive cycle.
