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Nowadays microarray studies offer a robust method for the analysis of whole genome mRNA expression patterns.
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In contrast, microarray-based studies offer the opportunity to analyze the complete genome of closely related strains, and have been applied to study the diversity and the difference in virulence properties of many bacterial pathogens [ 33].
But a few studies offer some hints.
Published studies offer conflicting results.
Combining microarray data with quantitative trait loci (pQTL) linkage studies offers new options of understanding the biology at a global level and the genetic factors affecting the trait of interest.
Recent RNA-seq time course studies offered significant gains in detail over previous microarray efforts, but lacked the temporal resolution to address how changes in gene expression precisely correspond to developmental progression [ 4, 12, 16- 18].
Recently, Park and colleagues[ 57] offered a meta-analysis of four diverse glioblastoma microarray studies.
A total of 4420 genotypes were scored by each method and accordingly this study offers a thorough characterization of a microarray-based technique in terms of accuracy, robustness and variability.
Last year, Karumanchi reviewed the data from his initial microarray studies and identified a second protein that could damage endothelial cells: endoglin.
Nevertheless, microarray studies have generated new and interesting insights.
The author mentioned that the proteomics approach may be complementary to microarray studies [47].
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