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Preprocessing , Management , and Analysis of Mass Spectrometry Proteomics Data

Mass Spectrometry (MS) based proteomics is becoming a powerful, widely used technique in order to identify different molecular targets in different pathological conditions [1]. Proteomics experiments involve different and heterogeneous technological platforms so a clear understanding of the function and errors related to each one has to be taken into account. In particular, data produced by mass spectrometer are affected by errors and noise due to sample preparation, sample insertion into the instrument (different operators can lead to different results using the same sample) and instrument itself. Mass spectrometrybased proteomics experiments usually comprise a data generation phase, a data preprocessing phase and a data analysis phase (usually data mining, pattern extraction or peptide/protein identification). Mass spectrometry produces a huge volume of data, said spectra, that are represented as a very large set of measures (intensity, m/Z), representing the abundance (intensity) of biomolecules having certain mass to charge ratio (m/Z) values. In this paper, after introducing Mass Spectrometry, we survey different techniques for spectra preprocessing and we present a first design of a software tool that allows to manage efficient storing and preprocessing of mass spectrometry data. A first performance evaluation of MS-Analyzer is also presented.