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Modular multi-relational framework for gene group function prediction

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Laboratorio de Control, Aprendizaje y Optimización de Sistemas (CAOS)es
dc.contributor.authorGarcía Jiménez, Beatriz
dc.contributor.authorLedezma Espino, Agapito Ismael
dc.contributor.authorSanchis de Miguel, María Araceli
dc.date.accessioned2010-12-16T09:19:27Z
dc.date.available2010-12-16T09:19:27Z
dc.date.issued2009
dc.descriptionPoster of: 19th International Conference on Inductive Logic Programming (ILP 2009), Leuven, Belgium, 2 - 4 Jul, 2009
dc.description.abstractDetermining the functions of genes is essential for understanding how the metabolisms work, and for trying to solve their malfunctions. Genes usually work in groups rather than isolated, so functions should be assigned to gene groups and not to individual genes. Moreover, the genetic knowledge has many relations and is very frequently changeable. Thus, a propositional ad-hoc approach is not appropriate to deal with the gene group function prediction domain. We propose the Modular Multi-Relational Framework (MMRF), which faces the problem from a relational and flexible point of view. The MMRF consists of several modules covering all involved domain tasks (grouping, representing and learning using computational prediction techniques). A specific application is described, including a relational representation language, where each module of MMRF is individually instantiated and refined for obtaining a prediction under specific given conditions.
dc.description.sponsorshipThe research reported here has been supported by CICYT, TRA2007-67374-C02-02 project.
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.identifier.bibliographicCitation19th International Conference on Inductive Logic Programming, ILP 2009, p. 1-6.
dc.identifier.publicationfirstpage1
dc.identifier.publicationlastpage6
dc.identifier.publicationtitle19th International Conference on Inductive Logic Programming, ILP 2009
dc.identifier.urihttps://hdl.handle.net/10016/9784
dc.language.isoeng
dc.relation.eventdate2 - 4 Jul, 2009
dc.relation.eventnumber19
dc.relation.eventplaceInternational Conference on Inductive Logic Programming (ILP 2009)
dc.relation.eventplaceLeuven (Belgium)
dc.rights.accessRightsopen access
dc.subject.ecienciaInformática
dc.subject.otherMulti relational data mining
dc.subject.otherGene function
dc.subject.otherMulti-label relational decision tree
dc.subject.otherInductive logic programming
dc.subject.otherStructure data
dc.titleModular multi-relational framework for gene group function prediction
dc.typelecture*
dspace.entity.typePublication
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