NeMo: Fast Count and Statistical Significance of Network Motifs
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Événement(s) lié(s) : - JOBIM 2011; Paris (FRA) - (2008-06-28 - 2008-07-01)
Networks is now the most popular way to describe interaction between biological objects. Studying network motifs is of particular interest in systems biology because these building blocks constitute functional units. We propose a tool to compute and statistically study the total number of occurrences of a given connected sub-graph, called topological motif, in a network. This tool relies on two very efficient algorithms to enumerate and/or count all the occurrences of a given topological motif in a given graph. Moreover, it implements approximate p-value computation in several probabilistic graph models extending some previous statistical results. The method is available through an R package named NeMo.
Networks is now the most popular way to describe interaction between biological objects. Studying network motifs is of particular interest in systems biology because these building blocks constitute functional units. We propose a tool to compute and statistically study the total number of occurrences of a given connected sub-graph, called topological motif, in a network. This tool relies on two very efficient algorithms to enumerate and/or count all the occurrences of a given topological motif in a given graph. Moreover, it implements approximate p-value computation in several probabilistic graph models extending some previous statistical results. The method is available through an R package named NeMo.