As covered in section 1.5, every human cell has on the order of 104 genes. Typically, not all the genes are expressed equally at any one time. At different stages of development, or as a response to extracellular perturbation, different genes of a cell are switched on at different intensity levels and at various time points. The genes and their associated, generally time dependent, levels interact with one another in a sophisticated regulatory web of cause and effect known as a genetic network. Restated, genetic regulatory networks are the set of mutually activating and repressing genes and gene products and their interactions .
It is generally difficult, if not impossible, to come up with the full set of parameters which completely characterize a genetic network. These parameters may be intracellular in nature, such as the mRNA concentration of another gene; intercellular, such as a hormone secreted by one organ to communicate a signal to another; or extracellular, such as an environmental condition like heat shock. Uncovering and understanding these interactions may potentially lead to new applications and insights on developmental disorders and diseases such as diabetes, cancer, and others.
The expression level of a gene is manifest by the presence of mRNA corresponding to its DNA transcript. Qualitatively, it is commonplace to say that a particular gene is highly expressed when high levels of its complementary mRNA are detected, whether by Northern blot, PCR, or microarray. Quantitatively, the reader may ask the obvious and more delicate question of how much mRNA should be present in a system in order that the gene be critically expressed so as to effect a biological state transition. In practice, this question is made more difficult by the realities of detection device sensitivity, repeat measurement variations, and how one defines a measurable biological state transition.
With the advent of microarrays, it has become possible to measure, in a relatively accurate and easy way, the expression levels of a great number of genes simultaneously. As a consequence, it is now possible to investigate topics such as time course development and drug intervention within the framework of the coordinated action of an entire transcriptome—the cellular genetic network—with the objective of reverse-engineering or unraveling the system's internal interdependencies.
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