Interactome and Gene Ontology provide congruent yet subtly different views of a eukaryotic cell

This study presents a comparison of the global structures of the Gene Ontology and the interactome of Saccharomyces cerevisiae. Sensitive, unsupervised methods of clustering applied to a large fraction of the proteome led to establish a GO-interactome correlation value of +0.47 for a general dataset that contains both high and low-confidence interactions and +0.58 for a smaller, high-confidence dataset.The structures of the yeast cell deduced from GO and interactome are substantially congruent. However, some significant differences were also detected, which may contribute to a better understanding of cell function and also to a refinement of the current ontologies.Gene Ontology (GO) is "a set of structured vocabularies for specific biological domains that can be used to describe gene products in any organism" [1]. GO attempts to summarize the current knowledge of the basic components that shape cell function in a given organism. However, the current GO is still limited, given that we understand only part of the functions of any cell. Moreover, our current views are biased by the concentration of research efforts on some aspects of cell metabolism and function in detriment of others. This bias is caused by most data used to assign GO terms deriving from hypothesis-driven approaches.In the last years, large protein-protein interaction (PPI) datasets have been characterized in several organisms using non-directed, massive approaches (reviewed in references [2-4]). This accumulation of knowledge is of fundamental importance, because the set of all PPIs (known as PPI graph, PPI network or interactome) may be envisaged as a functional map of the cell [3,5,6]. The fact that most interactome data have been obtained by non-directed approaches avoids the bias just described for GO. However, PPI data have also their own significant biases and shortcomings. An intrinsic problem is unavoidable: some aspects of cell metabolism may require few or no PPIs and therefore they will no