Tran Ngoc Tam L, Mohan Sominder, Xu Zhuoqing, Huang Chun-Hsi
Brief Bioinform. 2015 May;16(3):497-525. doi: 10.1093/bib/bbu021. Epub 2014 Jun 24.
Network motif detection is the search for statistically overrepresented subgraphs present in a larger target network. They are thought to represent key structure and control mechanisms. Although the problem is exponential in nature, several algorithms and tools have been developed for efficiently detecting network motifs. This work analyzes 11 network motif detection tools and algorithms. Detailed comparisons and insightful directions for using these tools and algorithms are discussed. Key aspects of network motif detection are investigated. Network motif types and common network motifs as well as their biological functions are discussed. Applications of network motifs are also presented. Finally, the challenges, future improvements and future research directions for network motif detection are also discussed.
网络基序检测是在一个更大的目标网络中寻找统计上过度呈现的子图。它们被认为代表了关键结构和控制机制。尽管该问题本质上是指数级的，但已经开发了几种算法和工具来有效地检测网络基序。这项工作分析了11种网络基序检测工具和算法。讨论了使用这些工具和算法的详细比较和有见地的方向。研究了网络基序检测的关键方面。讨论了网络基序类型、常见网络基序及其生物学功能。还介绍了网络基序的应用。最后，也讨论了网络基序检测面临的挑战、未来改进和未来研究方向。
