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A copula-based method for synthetic microarray data generation

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dc.contributor Universitat de Vic. Escola Politècnica Superior
dc.contributor Universitat de Vic. Grup de Recerca en Tecnologies Digitals
dc.contributor International Conference on Advances in Statistics (2012: Barcelona)
dc.contributor.author Lew, Sergio
dc.contributor.author Solé-Casals, Jordi
dc.contributor.author Caiafa, Cesar F.
dc.contributor.author Bau i Macià, Josep
dc.date.accessioned 2014-04-07T12:21:31Z
dc.date.available 2014-04-07T12:21:31Z
dc.date.issued 2012
dc.identifier.uri http://hdl.handle.net/10854/2858
dc.description.abstract In this work, we propose a copula-based method to generate synthetic gene expression data that account for marginal and joint probability distributions features captured from real data. Our method allows us to implant significant genes in the synthetic dataset in a controlled manner, giving the possibility of testing new detection algorithms under more realistic environments. ca_ES
dc.format application/pdf
dc.format.extent 3 p. ca_ES
dc.language.iso eng ca_ES
dc.rights Aquest document està subjecte a aquesta llicència Creative Commons ca_ES
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Dependència (Estadística) ca_ES
dc.subject.other Distribució (Teoria de la probabilitat) ca_ES
dc.title A copula-based method for synthetic microarray data generation ca_ES
dc.type info:eu-repo/semantics/conferenceObject ca_ES
dc.rights.accesRights info:eu-repo/semantics/openAccess ca_ES

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