Fig. 2
A protocol for identifying functional modules using spectral clustering and the Gene Ontology. Given an input set of genes, first map each gene to the corresponding GO term(s) that annotate(s) it according to the GO annotation database [23]. For example, if G denotes the set of input genes then we map each gene g (where g ∈ G), to the GO term go (where go ∈ GO) that annotates it. Here, GO refers to a set of biological process terms in the GO. For example, the mapping M(g 1) = {go 1, go 3} means that terms go 1 and go 3 annotate gene g 1. Second, form a set union of all GO terms that annotate at least one member of the input gene set. Third, using semantic similarity [24] as a distance measure, construct a similarity matrix among the GO terms. Fourth, with the similarity matrix as input, applied the spectral clustering algorithm [25] to group the GO terms into functionally similar clusters. Fifth, apply the Silhouette value technique [26] to estimate appropriate cluster size as well as cluster validity. Finally, map each gene g i (i.e., keys of map M) to cluster C i if there exist at least one term in C i that annotates g i