Each of the experiments mentioned were based around the abundance of gene expression found in a given sample. Gene expression can be thought of as gene activation, e.g. the higher the expression value, the more often that particular gene is doing work.
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Quantification of these abundances was made possible by the advent of microarray technologies. A full discussion of microarray technology is beyond the scope of this paper, but a basic explanation is as follows. A simple microarray is comprised of a solid surface, such as glass, covered in thousands of microscopic divots. Each divot contains many synthetically produced, single-stranded DNA, which represent a particular gene. Two groups of sample DNA are prepared; a control group to provide a standard of comparison and the experimental group. Both groups are colored with a fluorescent dye, typically green for the control group and red for the experimental group, and then introduced to the microarray platform. Upon contact with the platform, the sample strands of DNA will bind with the synthetic DNA found in the divots, in a process called hybridization. The divots will now emit levels of fluorescence dependent upon the abundance of each group (control, experimental, both, or neither) that adhered to a particular divot. By measuring the wavelengths of the fluorescence, it is possible to measure the abundance of experimental vs control that bound to a particular gene’s site.
As mentioned in the introduction, one of the major hurdles impeding the analysis of gene expression data is the lack of samples. Thankfully, recent years have seen an increase in the potential and motivation for researchers to store their data sets on publicly accessible repositories.
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