Characterizing the functional similarity of enzymes with high co-citation in interaction networks.
New methods for reliable quantitative analysis of biological network data are in high demand in today's bioinformatics and systems biology. Here we demonstrate the applicability of the co-citation, developed earlier for the analysis of scientific literature for finding functionally similar nodes in protein-protein interaction networks in several model organisms. We prove the power of our approach in a novel way: the predicted closely related enzymes are compared to the closeness of their enzyme commission (EC) numbers, therefore we can numerically evaluate our prediction method. We have found clear correspondence between related enzymatic functions and high co-citation of proteins in interaction networks.