title: Networks of motifs from sequences of symbols.
abstract: We introduce a method to convert an ensemble of sequences of symbols into a weighted directed network whose nodes are motifs, while the directed links and their weights are defined from statistically significant co-occurences of two motifs in the same sequence. The analysis of communities of networks of motifs is shown to be able to correlate sequences with functions in the human proteome database, to detect hot topics from online social dialogs, to characterize trajectories of dynamical systems, and it might find other useful applications to process large amounts of data in various fields.
authors.affiliation: Dipartimento di Fisica ed Astronomia, Università di Catania, INFN, Italy. roberta.sinatra@ct.infn.it
authors.forename: Roberta
authors.initials: R
authors.lastname: Sinatra
authors.forename: Daniele
authors.initials: D
authors.lastname: Condorelli
authors.forename: Vito
authors.initials: V
authors.lastname: Latora
mesh_terms: D020816:Amino Acid Motifs; D000595:Amino Acid Sequence; D057218:Blogging; D006801:Humans; D017711:Nonlinear Dynamics; D020543:Proteome / Q000737:chemistry; D012944:Social Support
chemical_list: D020543:Proteome