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Microarray based gene expression profiling was then carried out to compare gene expression in the scrambled and KDM2B shRNA lines.
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We used microarray-based gene expression profiling to search for genotypically distinct subgroups of non-functional PA associated with the early recurrent phenotype.
For overall gene expression, we observed an average correlation coefficient of >0.8, suggesting a clear validation of the microarray-based gene expression profiling data with the mRNA-Seq data.
Second, we have assessed global gene expression changes in our model using microarray-based gene expression profiling.
Here, we report an in-depth exploration of the functional and regulatory networks associated with PIP gene expression in breast carcinoma cell lines using DNA microarray-based gene expression profiling techniques.
We previously validated our sequence-based gene expression profiling against array-based technology in rice.
Measurements were performed in the same RNA samples used for microarray-based gene expression profiling.
The objective of the present study was to address this question using microarray-based gene expression profiling.
The first application of microarray-based gene expression profiling analysis to the study of breast cancer consisted of disease assessment at the molecular level.
The expression of the hormone receptors also broadly overlaps with more detailed molecular subclassifications of breast tumors as determined by microarray-based gene expression profiling [ 4, 5].
Here, we performed Illumina microarray-based gene expression profiling to quantify the relative abundance of transcripts in peripheral blood that are associated with AMI and/or CAD.
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