In the general case, each node of an immunomic regulatory network represents a combination of the epitope, the cytokine response measured, and the T cell population used as the target; in most cases, each node is in a one-to-one relationship with a single physical spot on an immunomic microarray experiment with a given T cell population. The edges between nodes represent putative regulatory relationships between the cells that respond to the respective epitopes. Figure 6 depicts a simple example with quantized Boolean responses, where peptide-MHC microarrays are used in conjunction with three kinds of T cell targets: CD4 þ helper T cells, CD4 þ regulatory T cells, and CD8 þ cytotoxic T cells. Epitope A is specific to the CD4 þ helper T cells that promote the response to epitope C, which is specific to the CD8 þ effector T cells that produce the actual protective mechanism. In addition, there is an epitope B that activates the CD4 þ regulatory T cells that suppress the effector response to epitope C, thereby producing an antiinflammatory response. In practice, such a model would be derived from microarray data by automatic epitope (feature) selection and determination of predictive relationships (classifier design). In this example, the effector response is activated only in the presence of both help from epitope A and an absence of regulatory response to epitope B. The suppressing response to epitope B is itself promoted by the presence of a response to epitope C, providing a negative feedback mechanism. These relationships can be represented by a wiring diagram and transition rules, depicted in Figure 6a .