摘要
复杂网络在现实世界中普遍存在,具有小世界性和无标度性等统计特性,网络簇结构是复杂网络重要的拓扑属性之一。在复杂生物网络中使用聚类算法揭示生物网络中的簇结构对分析生物网络的拓扑结构、预测其功能都具有重要意义。对复杂网络聚类方法在蛋白质-蛋白质相互作用网络和新陈代谢网络中的应用及其进展情况进行了综述,分析了几种聚类算法的评价函数和适用条件,并对生物网络聚类算法研究所面临的主要问题进行了讨论。
Complex networks are prevalent in the real world, they have small-world and scale-free properties. Network community structure is one of the most important topological properties of complex networks among its statistical properties. Using the clustering algorithm in complex biological networks can help us to reveal the community structure of biological networks, which is helpful to analyze the topological structures of biological networks, predict the function of community structure. This paper reviews the application and the progress of complex networks clustering algorithm used in protein-protein interaction networks and metabolic networks, analyzes the evaluation function of several clustering algorithms and their application of occasions, and discusses the major problems in clustering algorithm of the biological networks.
出处
《计算机科学与探索》
CSCD
2010年第4期330-337,共8页
Journal of Frontiers of Computer Science and Technology
基金
国家自然科学基金No.60603030
60773099
60873149
60503016
60703022
国家高技术研究发展计划(863)No.2006AA10Z245
2006AA10A309
模式识别国家重点实验室开放课题~~
