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Because the Cancer Genome Atlas (TCGA) Data Portal [ 13] contains RNA-seq based gene expression measurements mostly for tumor tissues, we compared a gene's expression in a tissue where the gene acquired a repeat mutation (relative to the matched normal tissue) with the gene's expression in a tissue where it did not acquire such a mutation.
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After 24 hours of exposure, RNA was isolated and synthesized to cDNA for real-time PCR based gene expression measurement.
Thus, extrapolation of protein expression on the basis of microarray-based gene expression measurements must be validated by direct measurement of the protein [15].
The same FS techniques are now widely used in bioinformatics for identification of biomarkers or lists of relevant genes from DNA microarray-based gene expression measurements.
However, microarray-based gene expression measurements require a substantial amount of knowledge about the targeted species' transcriptome, and these valuable tools are therefore unavailable for many ecologically important species.
The inference of biological networks based on gene expression measurements is a complex task.
On the other hand, the inter-patient proximities based on gene expression measurements across days (gene expression profile) for a specific gene reflected the variability of patients either according to response of this gene to treatment, or according to genetic heterogeneity of patients, or both.
This is because gene network inference is typically based on gene expression measurements across a wide range of conditions.
However, development of assays to identify likely responders to a drug based on gene expression measurements has some inherent difficulties.
Given a gene expression matrix, a RF classifier was constructed to classify tissue samples into relevant disease classes (NN, PN, PP) based on gene expression measurements (variables).
Microarray diagnostics of tumour specimens is based on gene expression measurement of a specific set of predictive or prognostic genes.
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