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The basic rationale of normalization is to remove or adjust for artifacts caused by microarray technology rather than biological differences of the samples between printed probes.
In order to adjust for the effects that arise from variation inherent to microarray technology rather than biological differences in the RNA samples, filtered data was normalized using intensity-dependent normalization [ 19].
With the microarray technology, rather than studying effect of the drug on a single gene or protein, we can now look for signatures consisting of multiple genes that are altered in some way, and together define novel set of pharmacodynamic biomarkers of the drug response as well as of resistance[ 23].
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All data were normalized to remove from the expression measures any systematic bias which arise due to the microarray technology itself, rather than differences between the probes or between RNA samples targets hybridized to the arrays.
In [ 9], we tried to make the case that the observed strong and long-ranged correlation between gene expression levels are of a biological nature rather than a technical flaw of the microarray technology.
RNA microarray technology was used for genome-wide expression analysis.
Microarray: Microarray technology is based on hybridization between the target DNA and probe DNA designed with known sequences.
Microarray technology is a powerful approach for genomics research.
Recently, microarray technology has increasingly been widely applied in glycobiology.
Target applications of the sensor include biomolecular microarray technology.
The University Health Network (UHN) Microarray Centre (MAC) is a leader in microarray technology.
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