Figure 1

A flowchart of the process described to build networks and find gateway nodes. The first step is to create a K_n network base (where n = number of probes) on which layers of information are applied, including state data from gene expression correlation. The K_n network skeleton is then filtered and annotated to only include edges with correlations within threshold range, and each edge is annotated with its state. This results in graph G with two types of edges, an integrated network. Identification of biologically relevant clusters and gateway nodes follows, and functional annotation is then performed using Gene Ontology node enrichment and edge annotation. Once these target genes are identified, importance is determined via manual literature curation toward the experimental objective at hand, in this case, the implications of gateway nodes in the aging mouse hippocampus.