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Applying it to arrays with only one probe per gene (cDNA microarrays) will result in a much lower number of genes for which expression levels can be determined.
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The microarray datasets, where the tissue samples represent the samples from cancerous (malignant) and non-cancerous (benign) cells, the classification of them will result in binary cancer classification.
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As expected chicken spleen samples performed the best with 78% spots passing quality control (it is not expected that hybridising chicken to the whole chicken genome microarray will ever result in 100% spot hybridisation as not all genes in the genome will be expressed in any one sample).
Degradation of the Cy5 signal relative to the Cy3 signal in 2-color microarrays will adversely reduce the Cy5/Cy3 ratio resulting in unreliable microarray data.
Results from the microarrays will be submitted to ArrayExpress as per the standards set forth by the Microarray Gene Expression Data Society.
The microarrays will increase the sensitivity, compared to EST sequencing, and thereby might give a more reliable result regarding which genes are actually differentially expressed.
As the compositions of microarrays are regularly updated to incorporate new genes with improved target sequences, it is evident that combining data from different generations of the same microarray platform will generally result in largely varying numbers of samples per gene.
Affymetrix's microarrays will provide insight into complex genetic diseases.
Alternatively, these probes may contain conserved motifs and therefore the probes on the microarray will cross-hybridize to multiple transcripts resulting in the higher signal intensities observed on the microarray for these elements.
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