SnapShot: Network Motifs

SnapShot: Network Motifs

Dynamics of network motifs

A biased distribution of local network structures, or network motifs, has been widely observed but remains poorly understood. By comprehensively studying their dynamics, we show that some network motifs are fundamentally more versatile—capable of executing a variety of tasks—than others. We calculate the value of a motif by comparing its versatility to its range of possible update rules. Our wo...

Discovering Colored Network Motifs

Network motifs are small overrepresented patterns that have been used successfully to characterize complex networks. Current algorithmic approaches focus essentially on pure topology and disregard node and edge nature. However, it is often the case that nodes and edges can also be classified and separated into different classes. This kind of networks can be modeled by colored (or labeled) graph...

Social Network Analysis Based on Network Motifs

In combination with the method of social network analysis, a set of network analysis methods is established based on the theory and methods of frequent subgraph mining, network motifs, at el, which is different from the traditional social network analysis. It can be used to analyze the properties of social network and judge the roles of the nodes effectively.

Discovering larger network motifs: Network Motif clustering

In this project, we aim to discover large network motifs. The main idea would be 1) combining smaller network motifs and extend it to larger network motifs or 2) using clustering algorithms to find more compact representation for the whole network, then using existing or new algorithm for finding network motifs. In order to find the appropriate approaches, we reviewed some of related papers, ab...