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arXiv · 1706.08499

Hidden long evolutionary memory in a model biochemical network

Md. Zulfikar Ali·Ned S. Wingreen·Ranjan Mukhopadhyay
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Abstract

We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.

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Md. Zulfikar Ali, Ned S. Wingreen, Ranjan Mukhopadhyay. 2017-06-26. Hidden long evolutionary memory in a model biochemical network. https://doi.org/10.1103/physreve.97.040401

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