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We now briefly discuss the four major trends in the microarray data seen in the K-means clustering analysis (Figure 2d), which will allow us to explore the major themes within an enormous amount expression data.
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Further support for DTKR expression in renal tubules is from gene microarray data (see FlyAtlas [34]).
A large number of methods have been introduced to generate biomarkers from available molecular information (in particular from gene expression microarray data – see [1], [2], [3], [4] for reviews).
Based on the network, sox-2 plays a role in the regulation of Dppa5 [44], Alpha crystallin B [45] and P-cadherin [46], and this is consistent with the microarray data (see Figure 3 and Table S3).
These data confirmed the results from the microarray data (see Additional file 5: Figure S4).
Time series analysis is a regression analysis of time course microarray data (see Additional File 3).
Five genes of S36 were chosen to validate our microarray data (see below).
In addition, several filtration criteria were followed to analyze microarray data (see Methods).
This is consistent with our microarray data (see Table 2 and Figure 4C).
Secondary structure analysis of these ncRNAs further supports the classification indicated by the microarray data (see Additional file 2).
Fifteen unstable chromosomal regions were identified using the SNP microarray data (see Additional Files 2, 3, 4 and 5).
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