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生物网络的功能模块识别有助于理解网络的结构和功能关系,有助于发现网络中的隐藏规律以及预测网络的行为等,是当前生物网络研究方面的一个重要研究主题。然而,当前的功能模块识别方法大多依赖于对网络中的节点进行聚类分析,其主要缺陷在于:每个节点只能属于某一个模块,而生物网络中的节点很难划分到某个独立的模块中。本文介绍了新近发展的基于边相似性的聚类方法,通过2个具体的生物网络功能模块识别实例,考察了这种新兴的方法在生物网络研究中的应用,结果表明了该方法的高效性。
Identification of functional modules of biological networks helps to understand the structure and function of the network, helps to discover the hidden laws in the network, and predicts the behavior of the network. It is an important research subject in current biological network research. However, most of the current functional module identification methods rely on cluster analysis of nodes in the network. The main drawback is that each node can only belong to a certain module, and it is difficult for nodes in a biological network to be divided into an independent Module. This paper introduces the newly developed clustering method based on edge similarity. Through the identification of two specific biological network function modules, the application of this emerging method in biological networks is investigated. The results show that this method is efficient .