Bayesian non-linear matching of pairwise microarray gene expressions

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Show simple item record Marín Díazaraque, Juan Miguel Nieto, Carmen
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística 2008-05-28T09:45:57Z 2008-05-28T09:45:57Z 2008-05
dc.description.abstract In this paper, we present a Bayesian non-linear model to analyze matching pairs of microarray expression data. This model generalizes, in terms of neural networks, standard linear matching models. As a practical application, we analyze data of patients with Acute Lymphoblastic Leukemia and we find out the best neural net model that relates the expression levels of two types of cytogenetically different samples from them.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 08-07
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other MCMC computation
dc.subject.other Microarray data analysis
dc.subject.other Multidimensional scaling
dc.subject.other Neural network
dc.subject.other Spatial Bayesian methods
dc.title Bayesian non-linear matching of pairwise microarray gene expressions
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws082507
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