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arXiv · 1606.00101

Exploratory Adaptation in Large Random Networks

Hallel I. Schreier·Yoav Soen·Naama Brenner
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Abstract

The capacity of cells and organisms to respond to challenging conditions in a repeatable manner is limited by a finite repertoire of pre-evolved adaptive responses. Beyond this capacity, cells can use exploratory dynamics to cope with a much broader array of conditions. However, the process of adaptation by exploratory dynamics within the lifetime of a cell is not well understood. Here we demonstrate the feasibility of exploratory adaptation in a high-dimensional network model of gene regulation. Exploration is initiated by failure to comply with a constraint and is implemented by random sampling of network configurations. It ceases if and when the network reaches a stable state satisfying the constraint. We find that successful convergence (adaptation) in high dimensions requires outgoing network hubs and is enhanced by their auto-regulation. The ability of these empirically-validated features of gene regulatory networks to support exploratory adaptation without fine-tuning, makes it plausible for biological implementation.

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Hallel I. Schreier, Yoav Soen, Naama Brenner. 2016-06-01. Exploratory Adaptation in Large Random Networks. https://doi.org/10.1038/ncomms14826

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