OUR TECHNOLOGY
Why mRNA Data?
Highly evolved cells need a software system that operates proteins for stable functioning
Proteins build the cell’s structure and participate in chemical reactions to realize the cell’s function within the cell.
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From a fragmentary point of view, the proteome is the primary material that implements the functions of the cell, and the genome is only an auxiliary device of the proteome.
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From a microscopic point of view, proteins are substances that simply undergo biochemical reactions under given conditions. They need precise physical and chemical controls to perform their functions properly.
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From a macroscopic point of view, the cell requires the coordination of several heterogeneous biological processes. It is precarious for the cell to function if it relies solely on the interactions of proteins involved in different processes.
Just as modern machines have software that operates the components to work at maximum efficiency, cells need a software system that uses proteins for stable functioning. In eukaryotic cells, only DNA can do this.
Although cells constituting each tissue and organ of the human body have the same DNA composed of about 25,000 to 30,000 genes, the amount of mRNA and protein produced based on the DNA of each gene is not the same for each cell. The properties of a cell are determined not by its DNA but by the amount of mRNA and protein.
To understand the large-scale control from the genome over the proteome for the expression of cell characteristics and to find out the abnormalities in this control system in cancer, it is necessary to analyze the amount of mRNA of the whole genome measured simultaneously.
Properties of gene expression data in eukaryotic cells
The eukaryotic genome is no longer a storage device of genetic information but a sophisticated system that has evolved into a control device regulating cellular functions. Therefore, it is meaningless to judge the significance of an individual gene expression rate by itself; what is essential is to understand the balance within the expression rates of all genes.
Gene expression data obtained from one sample can be located as a single point in a space with as many dimensions as the number of genes, called a gene space, just as three values are plotted as a single point in a three-dimensional space.
When gene expression data from multiple normal tissues performing the same function are located in this space, the points will gather in a very narrow area, which results in a low entropy.
The pattern in which the samples gather in a gene space can be expressed as a “density matrix.” The eigenvector and eigenvalue of the density matrix represent the biological characteristics of the sample group, and the von Neumann entropy calculated from the density matrix represents the degree of concentration on the biological function of the sample group.