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Based on these results, we developed a classifier algorithm that was capable of accurately discerning 93% of the infected animals using the microarray platform.
As shown in Figure 4a, TNF-α was not DE according to results obtained using the microarray platform.
We therefore predict that it will not be possible to discriminate the ~15% of the paralog pairs with the least sequence divergence using the microarray platform.
We determined the correlation of LCM selected epithelial cells derived from the same tissue type and variability of the triplicate LCM experiments using the microarray platform.
By contrast, no significant trend is observed for highly expressed genes using the microarray platform and only a slight trend is induced for genes with low expression.
While some empirical work has been carried out on probe/target identity (PTI) and data analysis using the microarray platform, the focus has largely been on optimization of species detection and/or identification in complex samples [ 21- 23].
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Differences may reflect disparities between the probes used on the microarray platform, NanoString probes, and the primer sets employed for RT-PCR.
All data were analysed using the microarray analysis and visualization platform R2 (http://r2.amc.nl).
The miRNAs microarray was performed using the LC Sciences microarray platform (LC Sciences).
Microarrays were carried out using the Affymetrix microarray platform and the Genechip Human Gene 1.0 ST Array; 100 ng of total RNA were used per sample.
All data were obtained using the same microarray platform (Affymetrix GeneChip Rice Genome Array; platform accession number GPL2025) and rice seedling samples (Table 1).
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using the weblogo platform
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using the microarray analysis
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