title: LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise.
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.
  
  
  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 variation associated with the peak intensity, improving the reliability of the information that can be extracted from single spectra. Our results show that LIMPIC peak-picking is effective even in low protein concentration regimes. The analytical comparison with commercial and freeware peak-picking algorithms demonstrates its superior performances in terms of sensitivity and specificity, both on in-vitro purified protein samples and human plasma samples.
  
  
  CONCLUSIONS
  The quantitative information on the peak intensity extracted with LIMPIC could be used for the recognition of significant protein profiles by means of advanced statistic tools: LIMPIC might be valuable in the perspective of biomarker discovery.
authors: Istituto Tecnologie Avanzate Biomediche, Fondazione G. D'Annunzio, Chieti, Italy. d.mantini@unich.it <d.mantini@unich.it>
authors: Dante
authors: D
authors: Mantini
authors: Francesca
authors: F
authors: Petrucci
authors: Damiana
authors: D
authors: Pieragostino
authors: Piero
authors: P
authors: Del Boccio
authors: Marta
authors: M
authors: Di Nicola
authors: Carmine
authors: C
authors: Di Ilio
authors: Giorgio
authors: G
authors: Federici
authors: Paolo
authors: P
authors: Sacchetta
authors: Silvia
authors: S
authors: Comani
authors: Andrea
authors: A
authors: Urbani
mesh_terms: D000328:Adult; D019295:Computational Biology / Q000295:instrumentation / Q000379:methods* / Q000592:standards; D004560:Electricity / Q000009:adverse effects; D006801:Humans; D011506:Proteins / Q000032:analysis*; D040901:Proteomics / Q000295:instrumentation / Q000379:methods / Q000592:standards; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000295:instrumentation / Q000379:methods* / Q000592:standards
chemical_list: D011506:Proteins