Is there a bias in proteome research?

Advances in technology have enabled us to take a fresh look at data acquire d by traditional single experiments and to compare them with genomewide dat a. The differences can be tremendous, as we show here, in the field of prot eomics. We have compared data sets of protein-protein interactions in Sacch aromyces cerevisiae that were detected by an identical underlying technical method, the yeast two-hybrid system. We found that the individually identi fied protein-protein interactions are considerably different from those ide ntified by two genomewide scans. Interacting proteins in the pooled databas e from single publications are much more closely related to each other with respect to transcription profiles when compared to genomewide data. This d ifference may have been introduced by two factors: by a selection process i n individual publications and by false positives in the whole-genome scans. If we assume that the differences are a result of false positives in the w hole-genome data, the scans would contain 47%, 44%, and 91% of false positi ves for the UETZ, ITO-core, and ITO-full data, respectively. If, however, t he true fraction of false positives is considerably lower than estimated he re, the data from hypothesis-driven experiments must have been Subjected to a serious selection process.