Abstract
The sequencing of the human genome and other ongoing sequencing projects have accelerated the pace of gene discovery and caused the identification of thousands of new genes. However, it also entails realisation that the genome alone could not provide enough information to understand the complex cellular network on the molecular level. Although genetic information provides us with the sequence of each protein, it is currently not possible to entirely deduce its localisation, structure, modifications, interactions, activities, and, ultimately, their function from it sequence. This lack of information becomes especially
obvious upon observation of a relatively closely linked relationship, the stoichiometry between RNA transcripts and their corresponding protein abundances. Although gene-protein dynamics were analysed for several tissues (1, 2), there is still no reliable correlation between gene activity and protein abundance. Besides this, protein abundances and their entirety, the proteome, are highly dynamic and therefore require tools that are amenable for describing several variables simultaneously. Up to today two-dimensional (2D) gel electrophoresis for protein separation, followed by mass spectrometry (MS) and database searches for protein identification, are the only real high-throughput techniques for the complex description of a
proteome. They are especially important in the classical proteome analysis, which focuses on studying complete proteomes, e.g. from two differentially treated cell lines, and the corresponding identification of single proteins.
