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The lessons we have learned in years of prognostic and predictive factor identification and implication need to be implemented in microarray approaches for the management of breast cancer.
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Alternatively, microarray-based approaches have been applied to extract features that can be implemented in a model that accurately predicts various phenotypes of diseases.
Here, we report on a national consensus approach how microarray is implemented in all genetic centres in Belgium.
Prediction Analysis of Microarray (PAM) was implemented in order to find which genes are most useful to discriminate between the two groups of myofibers.
This algorithm has been implemented in a software application designed to analyze microarray data.
During the last decade, microarray technology has been implemented in molecular biological laboratories world-wide, and numerous studies have been performed in a wide range of human tissues and conditions.
The Significance Analysis of Microarray (SAM) algorithm [ 84], which is implemented in TMEV, was used to generate a list of differentially expressed genes.
The microarray data analysis-based strategy has been implemented in PlantRGS also, for the identification of most suitable candidate reference gene(s) under given experimental conditions.
Probe-level summaries of microarray expression data were calculated using fRMA, which was implemented in R Bioconductor (http://bioconductor.org).
It was implemented in full in Scotland.
The recommendation was implemented in 1955.
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