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This factor is different for each sample, and it is what between-sample normalization aims to detect and correct for.
A critical pre-processing procedure for detecting differentially expressed miRNAs is normalization, aiming at removing the between-array systematic bias.
(Pitino aims for 40).
This normalization method aims to make the distribution of intensities for each array in a set of arrays the same.
Here we present a strategy for an in depth evaluation of normalization methods aiming at identifying the most appropriate one for a given data set.
Nevertheless, this hypothesis derived from our epidemiological study has to be confirmed in further studies by e.g. intervention studies aiming for a normalization of the postulated over-activated distress network in subjectively electromagnetic hypersensitive (e.g. cognitive behavioral therapy, which has been shown to be successful in electromagnetic hypersensitivity [45] and tinnitus patients).
Based on these principles, Rivers et al. [ 3] showed that an early therapeutic strategy that includes aiming for the rapid normalization of ScvO2 (≥70%) in patients suffering from severe sepsis or septic shock at presentation to the emergency department could improve survival.
Normalization techniques aim to correct such biases.
Normalization is aimed at solving these problems.
Normalization procedures aim to mitigate systematic differences between images.
They aim for perfection.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com