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More specifically, it is useful for independent confirmation of results obtained by the use of microarray analysis or RNA-seq and for evaluating RNA interference (RNAi -mediated gene knockdown.
In this article, we review the use of microarray analysis in Parkinson's disease (PD).
Further, we studied the autocrine effect of hHGF-expression on myoblast gene expression profiles by use of microarray analysis.
Through the use of microarray analysis of polysome fractions, we identified novel eIF4E targets that are involved in ribosome biogenesis, cell proliferation and survival.
There are several limitations to the use of microarray analysis as a single method for exploring tumour biology.
With the use of microarray analysis, extensive studies have been focused on identifying morphine-induced changes in gene expression [ 6– 19].
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We previously used a combination of microarray analysis and a motif identification algorithm to identify 46 potential Zap1 targets [ 3].
Differentially expressed genes were then identified using the linear models of microarray analysis (LIMMA) package.
The outputs of microarray analysis used in this study (series number GSE24937) are available at NCBI-GEO [69].
Using SAM Significance Analysiss of Microarrays) analysis, we identified 877 genes with significantly different levels of expression following PS treatment: 441 genes were up-regulated and 436 genes were down-regulated.
The quality evaluation of RNA used for microarray analysis.
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