Mining Spatial Association Rules for Composite Motif Discovery (Contributo in volume (capitolo o saggio))

Type
Label
  • Mining Spatial Association Rules for Composite Motif Discovery (Contributo in volume (capitolo o saggio)) (literal)
Anno
  • 2011-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1007/978-1-4419-6800-5_5 (literal)
Alternative label
  • 1 Michelangelo Ceci, 1 Corrado Loglisci, 1Eliana Salvemini, 2 Domenica D'Elia, and 1Donato Malerba (2011)
    Mining Spatial Association Rules for Composite Motif Discovery
    in Mathematical Approaches to Polymer Sequence Analysis and Related Problems, 2011
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • 1 Michelangelo Ceci, 1 Corrado Loglisci, 1Eliana Salvemini, 2 Domenica D'Elia, and 1Donato Malerba (literal)
Pagina inizio
  • 87 (literal)
Pagina fine
  • 109 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://link.springer.com/chapter/10.1007/978-1-4419-6800-5_5 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Mathematical Approaches to Polymer Sequence Analysis and Related Problems (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 2011 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 22 (literal)
Note
  • SpringerLink (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • 1. Dipartimento di Informatica, Università degli Studi di Bari \"Aldo Moro,\", via Orabona 4, 70126, Bari, Italy 2. CNR - Istituto di Tecnologie Biomediche, Via Amendola 122/d, 70126 Bari, Italy (literal)
Titolo
  • Mining Spatial Association Rules for Composite Motif Discovery (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-1-4419-6799-2 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autoriVolume
  • Renato Bruni Editor (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
  • Springer New York Publisher (literal)
Abstract
  • Motif discovery in biological sequences is an important field in bioinformatics. Most of the scientific research focuses on the de novo discovery of single motifs, but biological activities are typically co-regulated by several factors and this feature is properly reflected by higher order structures, called composite motifs, or cis-regulatory modules or simply modules. A module is a set of motifs, constrained both in number and location, which is statistically overrepresented and hence may be indicative of a biological function. Several methods have been studied for the de novo discovery of modules. We propose an alternative approach based on the discovery of rules that define strong spatial associations between single motifs and suggest the structure of a module. Single motifs involved in the mined rules might be either de novo discovered by motif discovery algorithms or taken from databases of single motifs. Rules are expressed in a first-order logic formalism and are mined by means of an inductive logic programming system. We also propose computational solutions to two issues: the hard discretization of numerical inter-motif distances and the choice of a minimum support threshold. All methods have been implemented and integrated in a tool designed to support biologists in the discovery and characterization of composite motifs. A case study is reported in order to show the potential of the tool. (literal)
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