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A significant positive correlation for both ITIH5 (P = 0.040) and DKK3 (P = 0.033) promoter methylation between both technologies was found.
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A comparison of power consumption and maximum attainable frequency between both technologies is performed.
Despite the conflicting information given by a handful of early published studies where both concordance[7] [9] and discordance[10] [12] between technologies was demonstrated, the maturation of microarray technology and data analysis methods has led to improved cross-platform correlations[6], [13].
For each metric, the significance of differences between technologies was also tested using the Monte Carlo method.
The overall sequence identity between the two technologies was 99.8%.
After excluding those four genes, the overall percentage of matches between the two technologies was approximately 90% (Additional file 2).
For this reason, a low correlation between proteome and transcriptome technologies was assumed.
The easiest way to avoid interference between two technologies is to operate both technologies on non-overlapping channels.
To make the most of such network effects, interoperability between different technologies is essential.
The common characteristic between these technologies is that they aim to improve the cutting process.
Similarities between agglomeration technologies are elaborated and the reasons why certain processes are preferred by some industries are explained.
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CEO of Professional Science Editing for Scientists @ prosciediting.com