Are Genetically Robust Regulatory Networks Dynamically Different from Random Ones?
分子网络
2010-12-07 v2 统计力学
适应与自组织系统
定量方法
摘要
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.
引用
@article{arxiv.q-bio/0703022,
title = {Are Genetically Robust Regulatory Networks Dynamically Different from Random Ones?},
author = {Volkan Sevim and Per Arne Rikvold},
journal= {arXiv preprint arXiv:q-bio/0703022},
year = {2010}
}
备注
To be published in Computer Simulation Studies in Condensed-Matter Physics XX. Ed. by D.P. Landau, S. P. Lewis, H.-B. Schuttler (Springer-Verlag, Berlin Heidelberg New York)