Physics
Hidden long evolutionary memory in a model biochemical network
Document Type
Article
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.
Publication Title
Physical Review E
Publication Date
4-20-2018
Volume
97
Issue
4
ISSN
2470-0045
DOI
10.1103/PhysRevE.97.040401
Keywords
emergent biological functions from complex interactions, evolutionary and population dynamics, protein interaction networks
Repository Citation
Ali, Md Zulfikar; Wingreen, Ned S.; and Mukhopadhyay, Ranjan, "Hidden long evolutionary memory in a model biochemical network" (2018). Physics. 147.
https://commons.clarku.edu/faculty_physics/147
Cross Post Location
Student Publications
