Bayesian non-linear matching of pairwise microarray gene expressions

Carmen Nieto

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

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.

Keywords: MCMC; computation; Microarray; data; analysis; Multidimensional; scaling; Neural; network; Spatial; Bayesian; methods (search for similar items in EconPapers)
Date: 2008-05
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:ws082507

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