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The resolution of this microarray methodology is ∼15% in exon inclusion differences [15].
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Microarray methodology was developed as an epochal method to simultaneously analyze enormous data sets for gene expression patterns in various biological conditions [ 7].
Thus, we propose that peptide microarray methodologies are a powerful new tool for elucidating molecular interactions at chromatin.
Study Design: The current literature relating to microarray technology and methodology is reviewed, specifically the use of DNA microarrays to characterize gene expression.
Automated microscopes can also be used to quantify pathology on tissue microarrays (TMAs); of note, TMA methodology is often used in cancer research in which one slide contains samples of many different cases.
For the first time the microarray methodology has been applied for the simultaneous identification of different mixed population of spoilage yeast and bacteria directly isolated from wine, thus indicating the practicability of oligonucleotide microarrays as a contamination control in wine industry.
This three-color microarray methodology can be utilized for pre-hybridization quality assessment [ 18], to facilitate automated post-hybridization image analysis [ 24], as well as post-hybridization data filtering [ 19].
Several power calculations for microarray methodologies exist, consequently sample size was determined and compared with two power calculation approaches.
Unwanted variance in microarrays arising from technical aspects of the methodology is removed using normalization methods such as RMA [ 2].
Our basic analysis of the data generated in this work indicates that DGE methodology is quite sensitive but noisier than microarrays themselves.
Our methodology is general enough to apply to any set of microarray experiments, using any scoring function.
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