Meta-analysis of microarray data demonstrates that cell lines, losing the organization required to form tissues, express both a smaller proportion of genes, and a different set of clustered genes, as compared to that observed in intact tissues in vivo [52].
In fact, our microarray data demonstrates that the levels of almost all these enzymes are down (10 genes pass all cutoff filters) following TSA treatment.
Our microarray data demonstrated a significant interaction between dietary fat and PCB exposure.
The microarray data demonstrated that the dataset can be used for typical analyses, including principal component analysis (PCA) and differential gene expression analysis.
Furthermore, we present microarray data demonstrating that off-targeting is significantly minimized by using siRNAs that contain "safe" seeds, an important strategy to consider during preclinical development of RNAi-based therapeutics.
Using three statistical methods, microarray data demonstrated marked changes in the old mouse.
The results for the 12 MSC samples used for microarray analysis were in line with the microarray data demonstrating the reliability of the method (figure 3A).
Analysis of the comparative microarray data demonstrated that strains with the same sequence type clustered together (Figure 2), demonstrating a strong correlation with our MLST analysis.
Microarray data demonstrated that ERB-041, MF101 and liquiritigenin were the most ERβ-selective agonists compared to estradiol, followed by nyasol and then diarylpropionitrile.
Indeed, our real time RT-PCR microarray data demonstrate that a large number of GPCRs are expressed not only in undifferentiated ES cells but in differentiating ES cells in EBs as well.
Our microarray data demonstrate the down-regulation of Cyclin G1, SerpinB9, BIRC6, and NAIP with simultaneous up-regulation of p21WAF1, CASP10, CARD9, BCCIP, CARD6, BAX, BIK, FASTKD2, and TNF-family member levels in both cell types.
