With the massive amount of sequence and structural data being produced, new avenues emerge for exploiting the information therein for applications in several fields. Fold distributions can be mapped onto entire genomes to learn about the nature of the protein universe and many of the interactions between proteins can now be predicted solely on the basis of the genomic context of their genes. Furthermore, by utilising the new incoming data on single nucleotide polymorphisms by mapping them onto three-dimensional structures of proteins, problems concerning population, medical and evolutionary genetics can be addressed.

Recently, a number of techniques have been proposed that use completely sequenced genomes for the function prediction of individual proteins encoded therein. They use the fusion of genes, their conserved location in operons or merely their co-occurrence in genomes to predict the existence of functional interactions between the proteins they encode. This type of information complements functional features that are predicted by classical homology-based search techniques.