LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise |
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| Authors: | Dante Mantini Francesca Petrucci Damiana Pieragostino Piero Del Boccio Marta Di Nicola Carmine Di Ilio Giorgio Federici Paolo Sacchetta Silvia Comani Andrea Urbani |
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| Institution: | 1.Istituto Tecnologie Avanzate Biomediche (ITAB),Fondazione "G. D'Annunzio",Chieti,Italy;2.Centro Studi sull'Invecchiamento (Ce.S.I.),Fondazione "G.D'Annunzio",Chieti,Italy;3.Dipartimento di Scienze Biomediche,Università "G. D'Annunzio",Chieti,Italy;4.Centro Europeo Ricerca sul Cervello (CERC),IRCCS-Fondazione S. Lucia,Roma,Italy;5.Dipartimento di Scienze Cliniche e Bioimmagini,Università "G. D'Annunzio",Chieti,Italy;6.Dipartimento di Medicina Interna,Università di Roma "Tor Vergata",Roma,Italy;7.Ospedale Pediatrico Bambino Gesù,IRCCS,Roma,Italy |
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| Abstract: | Background Mass spectrometry protein profiling is a promising tool for biomarker discovery in clinical proteomics. However, the development
of a reliable approach for the separation of protein signals from noise is required. In this paper, LIMPIC, a computational
method for the detection of protein peaks from linear-mode MALDI-TOF data is proposed. LIMPIC is based on novel techniques
for background noise reduction and baseline removal. Peak detection is performed considering the presence of a non-homogeneous
noise level in the mass spectrum. A comparison of the peaks collected from multiple spectra is used to classify them on the
basis of a detection rate parameter, and hence to separate the protein signals from other disturbances. |
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