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[…] ation as fixed and variable modifications, respectively. The search engine used for peptide identifications was Mascot v2.3 (Matrix Science). The protein sequence databases derived from the genomes of E. coli O157:H7 strain EDL933 and Sus scrofa were downloaded from RefSeq in NCBI., Protein identifications derived from Mascot v2.3 searches required at least one unique peptide with an e-value <0.1. Mascot search peptide false discovery rates (FDRs) were determined searching a randomized E. coli O157:H7 EDL933 decoy protein sequence database. The average FDR for 19 2D-LC-MS/MS experiments was 1.3%. Following file conversion into the mzXML format, MS data were re-scored using the algorithms PeptideProphet™ and ProteinProphet™ , . Prot.xml files were analysed using an in house-developed software tool termed APEX quantitative proteomics tool v1.1 . Using a pre-defined set of MS analysis parameters and 30 physicochemical properties provided by the APEX tool (default settings), ARFF files for Oi computations were generated for a set of 100 highly abundant bacterial proteins with Mr values >30 kDa (according to 2D gel data) to achieve a good representation of tryptic peptides. Observation of tryptic peptides in the training dataset were correlated with the 30 physicochemical peptide properties, resulting in the computation of Oi values (the expected number of unique proteotypic peptides for a given protein i) for all protein sequences, in this case 5397 annotated proteins in the E. coli O157:H7 […]

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