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:
“Of what use, however, is a general certainty that an insect will not walk with his head hindmost, when what you need to know is the play of inward stimulus that sends him hither and thither in a network of possible paths?”
—George Eliot [Mary Ann (or Marian)