Wilds Roy, Kauffman Stuart A, Glass Leon
Department of Mathematics and Statistics, McGill University, 805 Sherbrooke St. West, Montreal, Quebec H3A 2K6, Canada.
Chaos. 2008 Sep;18(3):033109. doi: 10.1063/1.2962223.
We study the evolution of complex dynamics in a model of a genetic regulatory network. The fitness is associated with the topological entropy in a class of piecewise linear equations, and the mutations are associated with changes in the logical structure of the network. We compare hill climbing evolution, in which only mutations that increase the fitness are allowed, with neutral evolution, in which mutations that leave the fitness unchanged are allowed. The simple structure of the fitness landscape enables us to estimate analytically the rates of hill climbing and neutral evolution. In this model, allowing neutral mutations accelerates the rate of evolutionary advancement for low mutation frequencies. These results are applicable to evolution in natural and technological systems.
我们研究了遗传调控网络模型中复杂动力学的演变。适应度与一类分段线性方程中的拓扑熵相关，而突变与网络的逻辑结构变化相关。我们将只允许增加适应度的突变的爬山进化与允许适应度不变的突变的中性进化进行了比较。适应度景观的简单结构使我们能够通过分析估计爬山进化和中性进化的速率。在这个模型中，对于低突变频率，允许中性突变会加速进化进程的速率。这些结果适用于自然系统和技术系统中的进化。
