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

# metadata.dc.description.abstract[].value
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)...

# metadata.dc.relation.ispartof[].value
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.

# metadata.dc.rights[].value
cc by (c) Reverter Comes, Ferran et al., 2012

# metadata.dc.source[].value
Llibres / Capítols de llibre (Genètica, Microbiologia i Estadística)

# metadata.dc.title[].value
Kernel Methods for Dimensionality Reduction Applied to the «Omics» Data