Abstract
Motifs have been recognized as basic network blocks and are found to be quite powerful in modeling certain patterns. Generally speaking, local characteristics of big networks could be reflected in network motifs. Over the years, motifs have attracted a lot of attention from researchers. However, most current literature reviews on motifs generally focus on the field of biological science. In contrast, here we try to present a comprehensive survey on motifs in the context of big networks. We introduce the definition of motifs and other related concepts. Big networks with motif-based structures are analyzed. Specifically, we respectively analyze four kinds of networks, including biological networks, social networks, academic networks, and infrastructure networks. We then examine methods for motif discovery, motif counting, and motif clustering. The applications of motifs in different areas have also been reviewed. Finally, some challenges and open issues in this direction are discussed.
Highlights
In molecular biology science, motifs are defined as frequent subpatterns that appear more often in a set of data, and are considered to have specific biological significance [1], [2]
It shows the interaction of molecules by establishing biological networks, and the concept of network motifs comes into being
MOTIF PROCESSING METHODS we mainly introduce some methods for processing motifs in big networks, including three different issues, i.e. motif detection, motif counting, and motif clustering
Summary
Motifs are defined as frequent subpatterns that appear more often in a set of data, and are considered to have specific biological significance [1], [2]. System biology focuses more on molecular interactions than on individual molecules [3], [4] It shows the interaction of molecules by establishing biological networks, and the concept of network motifs comes into being. As the scale of the network increases, more recurrent and statistically significant correlation patterns appear in real networks This kind of pattern is regarded as a motif. In recent years, the concept of motifs has been further expanded, which incentivizes researchers to pay more attention to the pattern characteristics of the network neutron map. This weakens the significance of its statistics.
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