A computational platform for MALDI-TOF mass spectrometry data: Application to serum and plasma samples

Dante Mantini, Francesca Petrucci, Damiana Pieragostino, Piero Del Boccio, Paolo Sacchetta, Giovanni Candiano, Gian Marco Ghiggeri, Alessandra Lugaresi, Giorgio Federici, Carmine Di Ilio, Andrea Urbani

Research output: Contribution to journalArticlepeer-review


Background: Mass spectrometry (MS) is becoming the gold standard for biomarker discovery. Several MS-based bioinformatics methods have been proposed for this application, but the divergence of the findings by different research groups on the same MS data suggests that the definition of a reliable method has not been achieved yet. In this work, we propose an integrated software platform, MASCAP, intended for comparative biomarker detection from MALDI-TOF MS data. Results: MASCAP integrates denoising and feature extraction algorithms, which have already shown to provide consistent peaks across mass spectra; furthermore, it relies on statistical analysis and graphical tools to compare the results between groups. The effectiveness in mass spectrum processing is demonstrated using MALDI-TOF data, as well as SELDI-TOF data. The usefulness in detecting potential protein biomarkers is shown comparing MALDI-TOF mass spectra collected from serum and plasma samples belonging to the same clinical population. Conclusions: The analysis approach implemented in MASCAP may simplify biomarker detection, by assisting the recognition of proteomic expression signatures of the disease. A MATLAB implementation of the software and the data used for its validation are available at http://www.unich.it/proteomica/bioinf.

Original languageEnglish
Pages (from-to)562-570
Number of pages9
JournalJournal of Proteomics
Issue number3
Publication statusPublished - Jan 3 2010


  • Biomarker discovery
  • Graphical tools
  • Mass spectrometry
  • Proteomics
  • Statistical analysis

ASJC Scopus subject areas

  • Biochemistry
  • Biophysics


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