The cell can be seen as an intricate network of molecular relationships that determines its potential activities. The study of the composition of such a complex network including not only the description of their elements but also the structure of their relationships, i.e. its topology, was previously used to extract important elements (e.g. hubs proteins) and to find recurrent circuits that characterize regulatory events (e.g. feedforward loops) using mainly protein-protein interactions networks. However, there are no studies that address these questions in a realistic picture of the cell where not only proteins are present but also other elements involved in cell regulation such as DNA, RNA, chemicals or other metabolites. This project proposes building an in silico model of the cell including all these molecules and their interactions by adding several until now unconnected layers of information to address the topological characterization and comparison of several types of protein post-translational modifications, the major mechanism by which protein function is regulated in eukaryotes. This novel network will be annotated by a novel ontology of actions describing molecular relationships and statistically addressed to evaluate the significance of every interaction. This framework will lead to elucidate specific mechanisms of regulation for each type of post-translational modification and be able to make functional prediction the molecules participating by finding similar motifs in uncharacterized events. Moreover, we will study the conservation of the PTMs residues across species to calibrate the potential of the annotation transfer among species that would lead to novel discoveries also in non-model organisms.