Kernel conditional Embeddings for associating omic data types

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dc.contributor.authorReverter Comes, Ferran
dc.contributor.authorVegas Lozano, Esteban
dc.contributor.authorOller i Sala, Josep Maria
dc.date.accessioned2020-04-20T13:46:49Z
dc.date.available2020-04-20T13:46:49Z
dc.date.issued2018
dc.date.updated2020-04-20T13:46:49Z
dc.description.abstractComputational methods are needed to combine diverse type of genome-wide data in a meaningful manner. Based on the kernel embedding of conditional probability distributions, a new measure for inferring the degree of association between two multivariate data sources is introduced. We analyze the performance of the proposed measure to integrate mRNA expression, DNA methylation and miRNA expression data.
dc.format.extent10 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec681318
dc.identifier.issn0302-9743
dc.identifier.urihttps://hdl.handle.net/2445/156044
dc.language.isoeng
dc.publisherSpringer Verlag
dc.relation.isformatofVersió postprint del document publicat a: https://doi.org/10.1007/978-3-319-78723-7_43
dc.relation.ispartofLecture Notes in Computer Science, 2018, vol. 10813 LNBI, p. 501-510
dc.relation.urihttps://doi.org/10.1007/978-3-319-78723-7_43
dc.rights(c) Springer Verlag, 2018
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.sourceArticles publicats en revistes (Genètica, Microbiologia i Estadística)
dc.subject.classificationBioinformàtica
dc.subject.classificationGenòmica
dc.subject.otherBioinformatics
dc.subject.otherGenomics
dc.titleKernel conditional Embeddings for associating omic data types
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/acceptedVersion

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Articles publicats en revistes (Genètica, Microbiologia i Estadística)