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In this study, we applied our method to genomic aberration profiles obtained by the microarray technology.
4. The approach follows the selection criterion of robustness, i.e. technical noise in measured mRNA concentrations caused by the microarray technology does not alter inferred regulatory interactions.
Obviously, most of the data obtained by the microarray technology could not have been addressed by any other method, featuring the exceptional power of this technology.
However, based on our findings of unacceptable experimental variations and artefacts produced by the microarray technology itself, we searched for genes that were not influenced by the experimental variations (see Materials and Methods).
Considering that average validation percentage is usually below 5% out of total candidate genes for reported cDNA microarrays studies [ 35, 49, 52] the number of validated genes in this work is highly representative of the transcription profile patterns detected by the microarray technology (12.5% out of total of differentially expressed genes) (Table 2).
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Transcript levels for CCR7 were the lowest ones among those for the 10 selected genes by using RT-qPCR, and very low signal intensities were measured for CCR7 by using the microarray technology; this indicates that differences in gene expression are more difficult to quantify by using microarray technology for low transcript levels.
By using the microarray technology, which has developed rapidly in last ten years, various gene signatures are developed for various complex diseases, especially the cancer.
By using the microarray technology, it was shown that 4 days of premetamorphic X laevis tadpoles treatment with BPA (22.8 and 228 μg/L) caused a downregulation of about 33% of the T3-induced genes.
The use of ratios or raw intensities is governed by the capabilities of the microarray technology, not by our algorithm.
These surprising results can only be partially explained by the limitations of the microarray technology.
The great opportunities offered by the development of the microarray technology have fueled many studies in cancer and more are underway exploiting proteomic tools.
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