In the future gel-free techniques MudPIT, iTRAQ and 18O stable isotope labeling could be expected to gain more importance as they become more established. Sample prefractionation system provides a highly valuable tool to fractionate proteins and peptides from complex eukaryotic samples like plasma. This approach has a positive influence on the number of proteins identified compared to SCX method [228] . iTRAQ is a very powerful tool, recognised form its ability to relatively quantify proteins. iTRAQ reagent improves MALDI ionisation, especially for peptides containing lysine. Although SILAC labelling is easy for any laboratory that uses cell culture, the MS technology that is required is still beyond the capabilities of most groups. One of the factors that contributed to the rapid acceptance of the SILAC technology was the availability of an open-source program, MSQuant, for interpreting results. Protein microarrays offer the ability to simultaneously survey multiple protein markers in an effort to develop expression profile changes across multiple protein analytes for potential use in diagnosis, prognosis, and measurement of therapeutic efficacy [229] . This technology is an excellent high-throughput method used to probe an entire collection of proteins for a specific function or biochemistry. It is an exceptional new way to discover previously unknown multifunctional proteins, and to discover new functionalities for well-studied proteins [230] . A systematic and efficient analysis of vast genomic and proteomic data sets is a major challenge for researchers today. To overcome limitations of current proteomics strategies in regard to the dynamic range of peptides detected and alternative mass spectrometrybased approaches are being explored. Targeted strategies exemplified by multiple reaction monitoring detect, quantify, and possibly collect a product ion spectrum to confirm the identity of a peptide with much greater sensitivity because the precursor ion is not detected in the full mass spectrum [231] . A systematic and efficient evaluation of large-scale experimental results requires (1) automatic retrieval of user defined information to construct a customized, queryable database; (2) an intuitive graphical and query platform to display and analyze experimental data in the context of the customized database; (3) efficient utilization of webbased bioinformatics software tools for data interpretation, prediction of function, and modeling; (4) scalability and reconstruction of the database in response to changing user needs and an ever-expanding base of knowledge and bioinformatics tools [232] . Creating a software tool to encompass the four crucial features outlined above is a challenging and ongoing task, particularly with respect to the ever-expanding publicly available base of knowledge and bioinformatics tools. The data processing and analysis bottleneck can be overcome through integration of the entire suite of tools into one linear pipeline. The good news is that all of the various proteomics strategies are in phases of very rapid technological development and that important advances in sensitivity, throughput, and proteome coverage can be expected in the near future for all of them.