منابع مشابه
Detecting Network Motifs by Local Concentration
Abstract: Studying the topology of so-called real networks, that is networks obtained from sociological or biological data for instance, has become a major field of interest in the last decade. One way to deal with it is to consider that networks are built from small functional units called motifs, which can be found by looking for small subgraphs whose numbers of occurrences in the whole netwo...
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Motifs in a network are small connected subnetworks that occur in significantly higher frequencies than in random networks. They have recently gathered much attention as a useful concept to uncover structural design principles of complex networks. Kashtan et al. [Bioinformatics, 2004] proposed a sampling algorithm for efficiently performing the computationally challenging task of detecting netw...
متن کاملDetecting Strong Ties Using Network Motifs
Detecting strong ties among users in social and information networks is a fundamental operation that can improve performance on a multitude of personalization and ranking tasks. There are a variety of ways a tie can be deemed “strong”, and in this work we use a data-driven (or supervised) approach by assuming that we are provided a sample set of edges labeled as strong ties in the network. Such...
متن کاملDetecting Network Motifs in Gene Co-expression Networks
Biological networks can be broken down into modules, groups of interacting molecules. To uncover these functional modules and study their evolution, our research groups are developing graphtheory based strategies for the analysis of gene expression data. We are looking for groups of completely connected subgraphs (e.g. cliques) in which corresponding members have the same combination of protein...
متن کاملDetecting Motifs from Sequences
The problem of multiple global comparison in families of biological sequences has been wellstudied. Fewer algorithms have been developed for identifying local consensus patterns or motifs in biological sequence. These two important problems have di erent biological constraints and, consequently, di erent computational approaches. The di culty of nding the biologically meaningful motifs results ...
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ژورنال
عنوان ژورنال: Electronic Journal of Statistics
سال: 2012
ISSN: 1935-7524
DOI: 10.1214/12-ejs698