动态网络模式挖掘方法及其应用

静态复杂网络研究在揭示社会网络、信息网络和生物网络的形成和演化机制方面取得了重要成果,其方法和结果对系统生物学产生了重要影响.但现实世界中,很多网络是随时间发生变化的,即动态网络.以动态网络为对象,对动态网络的拓扑特性分析、动态网络相关的各种模式挖掘模型和方法进行了综述、比较和分析.特别地,将动态网络模式分析方法应用于生物网络和社会网络,分析了生物网络相关的动态功能模块和模式演化问题、科学家合作网络和社交网络的动态模式.最后指出了动态网络的模式挖掘方法及其在动态生物网络和社会网络研究中存在的问题和挑战,并对未来的研究方向进行了分析.

Methods for Pattern Mining in Dynamic Networks and Applications

Studies of static complex networks have brought significant progress in revealing the mechanism for forming and evolving of social networks, information networks, and biological networks. However, many real word networks change with time and this type of networks is the so called dynamic networks. This paper focuses on dynamic networks to study the related pattern mining method and its applications in biological and social networks. First, the study analyzes the topological properties of the dynamic networks. Then we make a comparison and analysis to the algorithms and models for variety of pattern mining in dynamic networks. Specifically, we analyze the dynamics properties of biological and social networks. Based on this property, we study the biological networks related pattern mining problems, such as dynamic function module, pattern evolution and complex diseases associated pattern, the dynamic pattern in social network. Finally, some key problems and challenges in biological and social network are highlighted, as well as the future research directions.