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All networks, including [[biological network]]s, social networks, technological networks (e.g., computer networks and electrical circuits) and more, can be represented as [[complex network|graphs]], which include a wide variety of subgraphs. One important local property of networks are so-called '''network motifs''', which are defined as recurrent and [[statistically significant]] sub-graphs or patterns.

All networks, including [[biological network]]s, social networks, technological networks (e.g., computer networks and electrical circuits) and more, can be represented as [[complex network|graphs]], which include a wide variety of subgraphs. One important local property of networks are so-called '''network motifs''', which are defined as recurrent and [[statistically significant]] sub-graphs or patterns.

所有网络，包括生物网络(biological networks)、社会网络(social networks)、技术网络（例如计算机网络和电路）等，都可以用图的形式来表示，这些图中会包括各种各样的子图(subgraphs)。网络的一个重要的局部性质是所谓的网络基序，即重复且具有统计意义的子图或模式(patterns)。

所有网络，包括生物网络(biological networks)、社交网络(social networks)、技术网络（例如计算机网络和电路）等，都可以用图的形式来表示，这些图中会包括各种各样的子图(subgraphs)。网络的一个重要的局部性质是所谓的网络模体，即重复且具有统计意义的子图或模式(patterns)。

Network motifs are sub-graphs that repeat themselves in a specific network or even among various networks. Each of these sub-graphs, defined by a particular pattern of interactions between vertices, may reflect a framework in which particular functions are achieved efficiently. Indeed, motifs are of notable importance largely because they may reflect functional properties. They have recently gathered much attention as a useful concept to uncover structural design principles of complex networks.<ref name="mas1">{{cite journal |vauthors=Masoudi-Nejad A, Schreiber F, Razaghi MK Z |title=Building Blocks of Biological Networks: A Review on Major Network Motif Discovery Algorithms |journal=IET Systems Biology |volume=6 |issue=5 |pages=164–74 |year=2012|doi=10.1049/iet-syb.2011.0011 |pmid=23101871 }}</ref> Although network motifs may provide a deep insight into the network's functional abilities, their detection is computationally challenging.

Network motifs are sub-graphs that repeat themselves in a specific network or even among various networks. Each of these sub-graphs, defined by a particular pattern of interactions between vertices, may reflect a framework in which particular functions are achieved efficiently. Indeed, motifs are of notable importance largely because they may reflect functional properties. They have recently gathered much attention as a useful concept to uncover structural design principles of complex networks.<ref name="mas1">{{cite journal |vauthors=Masoudi-Nejad A, Schreiber F, Razaghi MK Z |title=Building Blocks of Biological Networks: A Review on Major Network Motif Discovery Algorithms |journal=IET Systems Biology |volume=6 |issue=5 |pages=164–74 |year=2012|doi=10.1049/iet-syb.2011.0011 |pmid=23101871 }}</ref> Although network motifs may provide a deep insight into the network's functional abilities, their detection is computationally challenging.