In the future, additional microarray data from rodents, primates, and perhaps other mammals will contribute to a further understanding of the common in vivo response and, ultimately, identification of disease mechanisms that are unique to specific agents or pathogens.
The comparison between inbred rat strains for hepatic and renal gene expression, which was repeated on Affymetrix, Illumina and Operon microarrays, showed that the kidney appeared to produce less reproducible data, perhaps due to morphological heterogeneity of this organ.
The CoD was perhaps the first predictive paradigm utilized in the context of microarray data, the goal being to provide a measure of nonlinear interaction among genes [1 6].
TK and RNI analyzed the microarray data.
Thus, understanding microarray data processing steps becomes critical for performing optimal microarray data analysis.
Steps 3.3 and 3.4 extracted drug microarray and disease microarray data respectively.
Fig. 2 Validation of microarray data by quantitative RT-PCR.
The center panels display light vs. dark NSF45K microarray data.
The accession number of the microarray data was GSE73814.
