LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise

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. Results: LIMPIC preprocessing proves to be superior than other classical preprocessing techniques, allowing for a reliable decomposition of the background noise and the baseline drift from the MALDI-TOF mass spectra. It provides lower coefficient of variat...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Dante Mantini, Francesca Petrucci, Damiana Pieragostino, Piero Del Boccio, Marta Di Nicola, Carmine Di Ilio, Giorgio Federici, Paolo Sacchetta, Silvia Comani, Andrea Urbani
• Keywords: Background Noise, Biomarker Discovery, BMCBI 2007, Protein