Protein function is a complex notion, which is now receiving renewed attention from a bioinformatics and genomics perspective. After a general discussion of the principles of experimental methods employed to decipher gene/protein function, the contributions made by new, high-throughput methods in terms of function discovery are discussed. Recent work on functional ontologies and the necessity to describe function within the context of hierarchical levels of complexity are presented. The concepts of molecular interactions and genetic networks are then discussed, leading to a useful new framework with which to describe protein function using new tools such as 2D interaction maps. Finally, it is proposed that interaction data could be used to develop new methods for the functional classification of proteins. An example of functional comparisons on a real data set of yeast chromosomal proteins is presented.