Updating JPROT's publication standards for large-scale proteomic studies: towards hypothesis-driven interpretation of predictive biological models.

The development in the 1990s of biological mass spectrometry into a robust analytical tool heralded a paradigm shift in biological research. Advances in instrumentation and methodologies have since fueled an expansion of the scope of biologicalmass spectrometry, from the simple analysis of single proteins to the characterization of highly complex proteomes. The cornerstone of proteomics analysis is the simultaneous identification and quantitation of the protein components of biological systems using increasingly sophisticated and sensitive mass analyzers; its beast, data validation and the interpretation of large-scale experiments. Data validation represents an essential step for ensuring independent repeatability and replication of the experiment by other researchers. However, the toughest aspect of proteomics studies is the interpretation in ameaningful biological context of both limited 2DE gel-based protein maps and large (gel-free, high-throughput) datasets. Around the turn of the new century, proteomics began moving from a purely descriptive mode to quantitative methods. The throughput of proteomics measurements depends on the level of detail desired. Paradoxically, the increased capabilities of mass spectrometry have led to proteomics increasingly functioning as a ‘black box’ [1]. However, with thousands of genomes sequenced to date, and many other in progress, the goal for the proteomics community now is to show how the ‘parts-list’ of a complex proteome provides a valuable asset for hypothesisdriven research in biological sciences. The central thesis of this Editorial, developed below, is that validation and interpretation become unified through the formulation of an adequate testable biological hypothesis. A corollary of this statement is that making biological sense of a proteomics experiment requires a paradigm shift in both experimental design and publication policy of biological mass spectrometric data. There is a lack of conformity among proteomics journals about publication standards for proteomics studies, and this is certainly not a trivial matter. Proteomics is applied to investigate a wide range of biological systems, both model (genome sequence available) and non-model organisms, and each study requires a somehow different experimental approach. Although high-quality research on non-model organisms, as well as papers describing