Work

Are genetically robust regulatory networks dynamically different from random ones?

Year: 2010

Type: article

Abstract: We study a genetic regulatory network model developed to demonstrate that genetic robustness can evolve through stabilizing selection for optimal phenotypes. We report preliminary results on whether such selection could result in a reorganization of the state space of the system. For the chosen parameters, the evolution moves the system slightly toward the more ordered part of the phase diagram. We also find that strong memory effects cause the Derrida annealed approximation to give erroneous predictions about the model’s phase diagram.

Source: Physics Procedia

DOI: 10.1016/j.phpro.2010.09.051

Authors: Volkan Sevim, Per Arne Rikvold

Institutions: Florida State University, Duke University

Language: English

Topic: Gene Regulatory Network Analysis

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: diamond