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

✍ Scribed by 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

• Publisher: Elsevier
• Year: 2010
• Tongue: English
• Weight: 535 KB
• Volume: 73
• Category: Article
• ISSN: 1874-3919
• DOI: 10.1016/j.jprot.2009.11.004

✦ Synopsis

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.