Fig 1. Schematic illustration of edge inference by PPIDM in a tripartite graph setting ${\mathcal{G}}^{}(X,Y,Z,E^{})$.

Z is here PPI, a set of PPIs, X and Y are D_L and D_R, two sets of Pfam domains. Each item in PPI is an ordered pair of proteins ppi_i = (L_i, R_i) with Id(L_i) ≤ Id(R_i). Domains in D_L and D_R are connected to their common neighbor item ppi_i in PPI through L_i and R_i respectively. The (d1, d2) edge comes from the Gold-Standard dataset of DDIs. With PPIDM, new edges are inferred between domains of D_L and domains of D_R if their adjacency vectors in PPI are similar. Here, the (d3, d2) edge is inferred because d3 and d2 are found in ppi1 and ppi2, and (d3, d4) is inferred because d3 and d4 are found in ppi2 and ppi3. However, the score of (d3, d2) will be lower than the score of (d1, d2) because d3 has one neighbor that does not contain d2 (namely ppi3).