IEEE/ACM Trans Comput Biol Bioinform. 2017 Sep-Oct;14(5):1181-1186. doi: 10.1109/TCBB.2016.2576442. Epub 2016 Jun 7.
A determinant property of the structure of a biological network is the distribution of local connectivity patterns, i.e., network motifs. In this work, a method for creating directed, unweighted networks while promoting a certain combination of motifs is presented. This motif-based network algorithm starts with an empty graph and randomly connects the nodes by advancing or discouraging the formation of chosen motifs. The in- or out-degree distribution of the generated networks can be explicitly chosen. The algorithm is shown to perform well in producing networks with high occurrences of the targeted motifs, both ones consisting of three nodes as well as ones consisting of four nodes. Moreover, the algorithm can also be tuned to bring about global network characteristics found in many natural networks, such as small-worldness and modularity.
生物网络结构的一个决定性特征是局部连接模式(即网络基元)的分布。在这项工作中,提出了一种创建有向无权重网络的方法,同时促进特定组合的基元。这种基于基元的网络算法从一个空图开始,通过推进或阻止选择的基元的形成来随机连接节点。生成网络的入度和出度分布可以明确选择。该算法在产生具有高目标基元出现频率的网络方面表现良好,包括由三个节点组成的基元和由四个节点组成的基元。此外,该算法还可以进行调整,以产生许多自然网络中发现的全局网络特征,如小世界特性和模块性。