The combined use of Liquid Chromatography coupled to two mass-analyzer. In the first stage a ion, namely precursor ion is selected and fragmented. In the second stage these fragments are analyzed. This techniques enable in such a way the identification of proteins in a sample starting from the constitutive peptides analyzed in the second stage.
Published in Chapter:
Management and Analysis of Mass Spectrometry Proteomics Data on the Grid
Mario Cannataro (University Magna Graecia of Catanzaro, Italy), Pietro Hiram Guzzi (University Magna Graecia of Catanzaro, Italy), Giuseppe Tradigo (University Magna Graecia of Catanzaro, Italy), and Pierangelo Veltri (University Magna Graecia of Catanzaro, Italy)
Copyright: © 2009
|Pages: 22
DOI: 10.4018/978-1-60566-374-6.ch011
Abstract
Recent advances in high throughput technologies analysing biological samples enabled the researchers to collect a huge amount of data. In particular, mass spectrometry-based proteomics uses the mass spectrometry to investigate proteins expressed in an organism or a cell. The manual inspection of spectra is unfeasible, so the need to introduce a set of algorithms, tools and platforms to manage and analyze them arises. Computational Proteomics regards the computational methods for analyzing spectra data in qualitative (i.e. peptide/protein identification in tandem mass spectrometry), and quantitative proteomics (i.e. protein expression in samples), as well as in biomarker discovery (i.e. the identification of a molecular signature of a disease directly from spectra). This chapter presents main standards, tools, and technologies for building scalable, reusable, and portable applications in this field. The chapter surveys available solutions for computational proteomics and includes a deep description of MS-Analyzer, a Grid-based software platform for the integrated management and analysis of spectra data. MS-Analyzer provides efficient spectra management through a specialized spectra database, and supports the semantic composition of pre-processing and data mining services to analyze spectra on the Grid.