Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/178162
Title: Kernel Methods for Dimensionality Reduction Applied to the «Omics» Data
Author: Reverter Comes, Ferran
Vegas Lozano, Esteban
Oller i Sala, Josep Maria
Keywords: Microarrays
Expressió gènica
Protein microarrays
Gene expression
Issue Date: Feb-2012
Publisher: IntechOpen
Abstract: 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)...
Note: Reprodució del document publicat a: http://doi.org/10.5772/37431
It is part of: 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.
URI: http://hdl.handle.net/2445/178162
Related resource: http://doi.org/10.5772/37431
Appears in Collections:Llibres / Capítols de llibre (Genètica, Microbiologia i Estadística)

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