All networks, including biological networks (e.g., metabolic networks, transcription regulatory networks, protein-protein interaction networks, protein structure networks, neural networks, ecological networks), social networks, technological networks (e.g., computer networks, electrical circuits), etc., can be represented as 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. Motifs, sub-graphs that repeat themselves in a specific network or even among various networks, would be consistent with the tenets of evolutionary theory. 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. Although network motifs may provide a deep insight into the network’s functional abilities, their detection is computationally challenging.
Famous quotes containing the word network:
“Parents need all the help they can get. The strongest as well as the most fragile family requires a vital network of social supports.”
—Bernice Weissbourd (20th century)