Hidden long evolutionary memory in a model biochemical network

Autor:	Ali, Md. Zulfikar, Wingreen, Ned S., Mukhopadhyay, Ranjan
Rok vydání:	2017
Předmět:	Quantitative Biology - Molecular Networks Physics - Biological Physics
Zdroj:	Phys. Rev. E 97, 040401 (2018)
Druh dokumentu:	Working Paper
DOI:	10.1103/PhysRevE.97.040401
Popis:	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. Comment: 20 Pages, 14 Figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1706.08499 Zobrazit plný text záznamu View this record from Arxiv