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Variable Selection for Multifactorial Genomic Data

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Variable Selection for Multifactorial Genomic Data

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Tarazona Campos, S.; Prado-López, S.; Dopazo, J.; Ferrer Riquelme, AJ.; Conesa, A. (2012). Variable Selection for Multifactorial Genomic Data. Chemometrics and Intelligent Laboratory Systems. 110(1):113-122. doi:10.1016/j.chemolab.2011.10.012

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/64780

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Title: Variable Selection for Multifactorial Genomic Data
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Issued date:
Abstract:
[EN] Dimension reduction techniques are used to explore genomic data. Due to the large number of variables (genes) included in this kind of studies, variable selection methods are needed to identify the most responsive genes ...[+]
Subjects: Gene expression , Multifactorial data , Principal component analysis , Variable selection
Copyrigths: Reserva de todos los derechos
Source:
Chemometrics and Intelligent Laboratory Systems. (issn: 0169-7439 )
DOI: 10.1016/j.chemolab.2011.10.012
Publisher:
Elsevier
Publisher version: https://dx.doi.org/10.1016/j.chemolab.2011.10.012
Thanks:
This work was partially funded by Spanish Ministry of Science and Innovation [grants BIO2008-05266-E and DPI2008-06880-C03-03/DPI] and by Universidad Politecnica de Valencia [UPV-PAID 05-09]. The English revision of this ...[+]
Type: Artículo

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