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cc by (c) Reverter Comes, Ferran et al., 2012
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/178162

Kernel Methods for Dimensionality Reduction Applied to the «Omics» Data

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Microarray technology has been advanced to the point at which the simultaneous monitoring of gene expression on a genome scale is now possible. Microarray experiments often aim to identify individual genes that are differentially expressed under distinct conditions, such as between two or more phenotypes, cell lines, under different treatment types or diseased and healthy subjects. Such experiments may be the first step towards inferring gene function and constructing gene networks in systems biology. The term ”gene expression profile” refers to the gene expression values on all arrays for a given gene in different groups of arrays. Frequently, a summary statistic of the gene expression values, such as the mean or the median, is also reported. Dot plots of the gene expression measurements in subsets of arrays, and line plots of the summaries of gene expression measurements are the most common plots used to display gene expression data (See for example Chambers (1983) and references therein)...

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REVERTER COMES, Ferran, VEGAS LOZANO, Esteban, OLLER I SALA, Josep maria. Kernel Methods for Dimensionality Reduction Applied to the «Omics» Data. _Chapter 1 in: Sanguansat_. Parinya. 2012. Principal Component Analysis - Multidisciplinary Applications. IntechOpen. ISBN: 978-953-51-0129-1. DOI: 10.5772/2694. pp: 1-20.. [consulta: 24 de novembre de 2025]. [Disponible a: https://hdl.handle.net/2445/178162]

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