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Hidden long evolutionary memory in a model biochemical network.

Author(s): Al, Md Zulfikar; Wingreen, Ned; Mukhopadhyay, Ranjan

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Abstract: We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational aWe introduce a minimal model for the evolution of functional protein-interaction networks using a sequencebased 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 Date: Apr-2018
Electronic Publication Date: 20-Apr-2018
Citation: Ali, Md Zulfikar, Wingreen, Ned S, Mukhopadhyay, Ranjan. (2018). Hidden long evolutionary memory in a model biochemical network.. Physical review. E, 97 (4-1), 040401 - ?. doi:10.1103/physreve.97.040401
DOI: doi:10.1103/physreve.97.040401
ISSN: 2470-0045
EISSN: 2470-0053
Pages: 040401 - 040401
Language: eng
Type of Material: Journal Article
Journal/Proceeding Title: Physical Review E
Version: Final published version. Article is made available in OAR by the publisher's permission or policy.



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