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Sato et al. also evaluated five commercial miRNA microarray platforms from Agilent, Exiqon, Ambion, Invitrogen, and Toray using two RNA samples and found the miRNA microarray to have high intra-platform repeatability and comparability to qRT-PCR but lower inter-platform concordance [29].
For each strain, we chose genes that were predicted by the microarray to have significant changes in transcription.
We also performed in situ hybridization to 19 genes that were identified by microarray to have changed in expression only on the opposite side of the head (versus also changing in the blastema) during regeneration.
Some of the differentially expressed proteins we identified were also found on microarray to have altered mRNA levels (two H-FABPs, ACBP, GOT, GAPDH and the stress-activated protein kinase 3 [MK12]).
The observation that those genes expressed at low levels had the lowest intra-individual correlations may be partly due to the known characteristic of probe sets at the lower end of the quantitative range of a microarray to have poorer reproducibility [ 36].
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MicroRNA microarray data have various distribution profiles between different platforms, although microarray data tend to have positive skewness (a right-side longer tail).
Recently, different microarray platforms have been reported to have a good agreement [ 79, 80].
7 Various gene expression profiling techniques ranging from differential display, SAGE to microarrays, have been utilised.
Second, in order to confirm the results, the clones printed on the microarray have to be correct and error free.
All EST sequences used to fabricate microarrays have been submitted to dbEST at GenBank [ 46].
Microarray studies have contributed to our understanding of key pathways activated during T-cell stimulation.
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