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The exhibition designers have turned a DNA microarray into a glorious macroarray, a giant box gridded with lights of different hues and intensities.
For statistical analysis of the microarray data, we first transformed the values from the microarray into log2 format for ease of comparison and data representation [ 76].
Briefly, a gene set file was created classifying all the genes included in the microarray into groups according to their specific involvement in a biological process.
Effectively translating the results from the microarray into a biological interpretation requires an accurate mapping between the probesets on the array and the genes that they are targeting.
Particularly, our SOM machine learning method partitions the more than twenty thousand 'single' genes probed by each microarray into 3600 miniclusters arranged in a two-dimensional mosaic map.
For this purpose a gene set file was created classifying all the genes included in the microarray into groups according to their specific involvement in a biological process.
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This problem arises from various technical and biological sources including platform differences [2], and has been a major obstacle to moving microarrays into the clinic as a tool to uncover as yet unrecognized disease subtypes.
Breast cancer has been successfully classified using microarrays into clinically relevant subgroups based on variations in gene expression patterns.
We strongly recommend using one or several of these metrics before performing meta-analyses or integrating microarrays into databases, as we do in Bgee.
Diagnostic signature patterns for these models were derived and evaluated based on 500 random divisions of the complete Affymetrix array set (47 microarrays) into training and test samples.
The one-step, cost-effective DNA-linking method on non-modified polymers significantly simplifies microarray fabrication procedures and permits great flexibility to plastic material selection, thus making it convenient to integrate microarrays into plastic microfluidic systems.
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