Large amounts of 'raw' genomic sequence data already exist and continue to grow exponentially. Many tools are available for automated analysis of these data by comparison to known sequences or by pattern recognition. One of the hardest problems is how to present the sequence data and its derived annotation in an intuitive way. We present here a workbench for analysis of large-scale genomic sequence data, with strong emphasis on the production of enriched graphical representation of the analysed data. The GESTALT Workbench can execute a variety of external analysis programmes (e.g.
Corra is a single, user-friendly, informatic framework, that is simple to use and fully customizable, for the enabling of LC-MS-based quantitative proteomic workflows of any size, able to guide the user seamlessly from MS data generation, through data processing, visualization, and statistical analysis steps, to the identification of differentially abundant or expressed candidate features for prioritized targeted identification by subsequent MS/MS.
As a complement to the well-established discovery proteomic methods, targeted mass spectrometry based on SRM is becoming an important tool for the generation of reproducible, sensitive and quantitatively accurate data from biological samples.