Experiment design space

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Experiment design space is the space of potential combinations of stimuli or conditions to which one can subject the regulatory apparatus of the genome. These stimuli include exposure to pharmaceutical agents such as mitogens, environmental effects such as temperature differences, withdrawal of nutritional sources, overexpression of a particular gene such as a transcriptional factor in a transgenic animal, or conversely, an engineered misexpression or "knockout" model. Other common experimental conditions include the passage of time, such as from a newborn to an old mouse; the observation of the environment (organisms from one particular condition vs. another); the observation of organismal processes (organisms with a particular morphology, or afficted with a particular pathophysiologic condition vs. another); physical manipulation of the cell membrane; exposure to infectious agents; and changes in osmotic conditions, all of which can potentially affect the genomic regulatory mechanisms which maintain cellular existence and the regulation of the cellular response to the environment.

Experimental conditions can be represented as combinations of values on several scales:

• Binary scales, e.g., the presence or absence of a diagnosis.

• Continuous scales, e.g., such as the gradients of exposure to a chemical. These can have value ranges, say, 10.0, 1.0, 0.1, 0.01, representing the chemical concentration or 0, 5, 10,

15, 20, representing time in minutes from the initial state.

Unordered discrete scales, e.g., the type of mutant mouse model created or which of the multiple mammalian muscle tissue types were sampled.

When different experimental conditions from these different scales are combined, then the experiment can be described as being located in a particular locus of the multidimensional experiment design space. Shown in figure 2.1 below is the simple example of an experimental space over three sets of conditions. In this case, the first dimension represents whether the mouse model being studied is an irsl [138] knockout, an irs2 knockout [192], or a wild-type mouse. The insulin receptor signaling proteins irsl and irs2 are thought to be part of the signaling cascade through which multiple cellular events[1] are triggered upon binding of insulin to the cellular receptor. The "knockout" is an engineered mouse in which a particular gene is no longer sufficiently expressed. The second dimension is the amount of insulin to which the mouse circulatory system is exposed. The third dimension represents the three types of mouse tissues being studied in this particular set of experiments, namely, the liver, brain, and fatty tissue. Each of these tissues has distinct metabolic responses to insulin exposure. Within this three-dimensional experiment design space, each set of possible experiments can be uniquely located. This notion obviously generalizes to the much larger number of possible dimensions in any experimental system. Note that the first and third dimensions have unordered discrete scales, whereas the second dimension is continuously scaled.

Figure 2.1: Three experiments within the multi-dimensional representation of experiment design space. Experiment design space defines all the possible stimuli or conditions to which a particular biological system could be subjected. Shown here is an experiment design space that is concerned with insulin signaling in different tissues, in different mouse "knockout" models, with different levels of insulin.

A functional genomic study might involve a trajectory across the experiment design space where the mouse models are studied across multiple insulin levels and multiple tissues. As the number of experimental dimensions increases, the number of experiments required to cover the experimental

Figure 2.1: Three experiments within the multi-dimensional representation of experiment design space. Experiment design space defines all the possible stimuli or conditions to which a particular biological system could be subjected. Shown here is an experiment design space that is concerned with insulin signaling in different tissues, in different mouse "knockout" models, with different levels of insulin.

A functional genomic study might involve a trajectory across the experiment design space where the mouse models are studied across multiple insulin levels and multiple tissues. As the number of experimental dimensions increases, the number of experiments required to cover the experimental design space grows exponentially. However, the concept of an experiment design space by itself does not suffice to determine which kind or number of experiments is adequate to assess the genomic physiology of a tissue or system.

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