The effects of incomplete protein interaction data on structural and evolutionary inferences

Here we study how properties of the yeast protein interaction network are affected by random and non-random sampling schemes using a range of different network statistics. Effects are shown to be independent of the inherent noise in protein interaction data. The effects of the incomplete nature of network data become very noticeable, especially for so-called network motifs. We also consider the effect of incomplete network data on functional and evolutionary inferences.Crucially, when only small, partial network data sets are considered, bias is virtually inevitable. Given the scope of effects considered here, previous analyses may have to be carefully reassessed: ignoring the fact that present network data are incomplete will severely affect our ability to understand biological systems.Molecular networks such as protein interaction, transcriptional or metabolic networks are widely seen as integrative and coherent descriptions for the whole complement of molecular processes inside a cell [1]. There has been considerable interest in their structure, their functional organization and their evolutionary properties. For important model organisms such as Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster there are now extensive protein interaction data deposited in public-domain databases and serious attempts are being made at elucidating the human protein interaction network (PIN) [2,3]. These network data sets – extensive though they are thanks to experimental advances and in silico prediction – do not cover the entire network. In particular they do not include all the proteins in these organisms and represent samples only from much larger networks.But a network introduces a set of relationships and potential dependencies between the constituent nodes and these may be broken up in the subnet. By subnet we mean a subset S MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBamrtHrhAL1wy0L2yHvtyaeHbnfgDOvwBHrxAJfwna