Novel map descriptors for characterization of toxic effects in proteomics maps.

We consider a novel numerical characterization of proteomics maps based on the construction of a graph obtained by connecting all protein spots in a proteomics map that are at distance equal to, or smaller than, a critical distance D(c). We refer to the so constructed graph as a cluster graph and we calculate four associated characteristic matrices, previously considered in the literature: (1) the Euclidean-distance matrix ED; (2) the neighborhood-distance matrix ND; (3) the path-distance matrix based on the shortest paths between connected spots PD; and (4) the quotient matrix Q, the elements of which are given as the quotient of the corresponding elements of ED and ND matrices. Numerical descriptors for proteomics maps include in particular the leading eigenvalue of the Q matrix and the family of associated "higher order" matrices defined as powers of Q. These map descriptors show considerable sensitivity to perturbations of proteomics maps by toxicants.