In the future we will report on the use of this isolation chamber in specific experiments to further demonstrate its versatility and usefulness. Proteomics: Challenges, Techniques and Possibilities to Overcome Biological Sample Complexity Proteomics is the large-scale study of the structure and function of proteins in complex biological sample. Such an approach has the potential value to understand the complex nature of the organism. Current proteomic tools allow large-scale, high-throughput analyses for the detection, identification, and functional investigation of proteome. Advances in protein fractionation and labeling techniques have improved protein identification to include the least abundant proteins. In addition, proteomics has been complemented by the analysis of posttranslational modifications and techniques for the quantitative comparison of different proteomes. However, the major limitation of proteomic investigations remains the complexity of biological structures and physiological processes, rendering the path of exploration paved with various difficulties and pitfalls. The quantity of data that is acquired with new techniques places new challenges on data processing and analysis. This article provides a brief overview of currently available proteomic techniques and their applications, followed by detailed description of advantages and technical challenges. Some solutions to circumvent technical difficulties are proposed. The term proteomics describes the study and characterization of complete set of proteins present in a cell, organ, or organism at a given time [1] . In general, proteomic approaches can be used (a) for proteome profiling, (b) for comparative expression analysis of two or more protein samples, (c) for the localization and identification of posttranslational modifications, and (d) for the study of protein-protein interactions. The human genome harbors 26000-31000 protein encoding genes [2] ; whereas the total number of human protein products, including splice variants and essential posttranslational modifications (PTMs), has been estimated to be close to one million [3, 4] . It is evident that most of the functional information on the genes resides in the proteome, which is the sum of multiple dynamic processes that include protein phosphorylation, protein trafficking, localization, and protein-protein interactions [5] . Moreover, the proteomes of mammalian cells, tissues, and body fluids are complex and display a wide dynamic range of proteins concentration one cell can contain between one and more than 100000 copies of a single protein [6] . In spite of new technologies, analysis of complex biological mixtures, ability to quantify separated protein species, sufficient sensitivity for proteins of low abundance, quantification over a wide dynamic range, ability to analyze protein complexes, and high throughput applications is not yet fulfilled [7] . Biomarker discovery remains a very challenging task due to the complexity of the samples (e.g., serum, other bodily fluids, or tissues) and the wide dynamic range of protein concentrations [8] . Most of the serum biomarker studies performed to date seem to have converged on a set of proteins that are repeatedly identified in many studies and that represent only a small fraction of the entire blood proteome [9] . Processing and analysis of proteomics data is indeed a very complex multistep process [10, 11] . The consistent and transparent analysis of LC/MS and LC-MS/MS data requires multiple stages [12] , and this process remains the main bottleneck for many larger proteomics studies. To overcome these issues, effective sample preparation (to reduce complexity and to enrich for lower abundance components while depleting the most abundant ones), state-of-the-art mass spectrometry instrumentation, and extensive data processing and data analysis are required. A wide range of proteomic approaches are available such as gel-based applications include one-dimensional and twodimensional polyacrylamide gel electrophoresis [13, 14] , and gel-free high throughput screening technologies are equally available, including multidimensional protein identification technology [15] , isotope-coded affinity tag ICAT [16] ; SILAC [17] ; isobaric tagging for relative and absolute quantitation (iTRAQ) [18] . Shotgun proteomics [19] and 2DE DIGE [20] as well as protein microarrays [21, 22] are applied to obtain overviews of protein expression in tissues, cells, and organelles. Large-scale western blot assays [23] , multiple reaction monitoring assay (MRM) [24] , and label-free quantification of high mass resolution LC-MS data [25] are being explored for high throughput analysis. Many different bioinformatics tools have been developed to aid research in this field such as optimizing the storage and accessibility of proteomic data or statistically ascertaining the significance of protein identifications made from a single peptide match [26] . In this review we attempt to provide a overview of the major developments in the field of proteomics, some success stories as well as challenges that are currently being faced.