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.
Barbarini
N
N
Department of Computer Science and Systems, University of Pavia, Italy. nicola.barbarini01@ateneopv.it
Magni
P
P
Bellazzi
R
R
D000465:Algorithms; D015415:Biomarkers / Q000097:blood*; D014408:Biomarkers, Tumor / Q000097:blood; D005260:Female; D006801:Humans; D009363:Neoplasm Proteins / Q000097:blood; D010051:Ovarian Neoplasms / Q000175:diagnosis; D010455:Peptides / Q000097:blood*; D040901:Proteomics / Q000379:methods; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
D015415:Biomarkers; D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins; D010455:Peptides