Przytycka Teresa M, Yu Yi-Kuo
NCBI/NLM/NIH 8600 Rockville Pike, Bethesda, MD 20894, USA.
Comput Biol Chem. 2004 Oct;28(4):257-64. doi: 10.1016/j.compbiolchem.2004.07.001.
Recent studies of properties of various biological networks revealed that many of them display scale-free characteristics. Since the theory of scale-free networks is applicable to evolving networks, one can hope that it provides not only a model of a biological network in its current state but also sheds some insight into the evolution of the network. In this work, we investigate the probability distributions and scaling properties underlying some models for biological networks and protein domain evolution. The analysis of evolutionary models for domain similarity networks indicates that models which include evolutionary drift are typically not scale free. Instead they adhere quite closely to the Yule distribution. This finding indicates that the direct applicability of scale-free models in understanding the evolution of biological network may not be as wide as it has been hoped for.
近期对各种生物网络特性的研究表明，其中许多网络呈现出无标度特征。由于无标度网络理论适用于不断演化的网络，人们希望它不仅能提供生物网络当前状态的模型，还能对网络的演化有所洞察。在这项工作中，我们研究了一些生物网络和蛋白质结构域进化模型背后的概率分布和标度特性。对结构域相似性网络进化模型的分析表明，包含进化漂移的模型通常不是无标度的。相反，它们非常接近尤尔分布。这一发现表明，无标度模型在理解生物网络进化方面的直接适用性可能不像人们期望的那么广泛。
