A new approach for the analysis of mass spectrometry data for biomarker discovery.

In the last few years a growing interest has been devoted to disease diagnosis based on proteomic profiles of body fluids generated by mass spectrometry. In this work, we will present a new approach for their analysis for biomarker discovery. In particular, we will describe a new strategy for the analysis of SELDI/MALDI-TOF serum data based on the following three steps: i) data-preprocessing, ii) feature (mass/charge ratio, m/z) reduction and selection, iii) association of the selected features to a list of compatible known proteins. The method is applied to an ovarian cancer dataset.