Segmentation Based Feature Selection on Classifying Proteomic Spectral Data

Abstract

Feature selection has been an important issue for classification of proteomic mass spectra data since researchers are often interested in identifying potentially important biomarkers. In this study, a segmentation approach is adopted to locate the potential biomarker regions from the possible m/z range. Illustration is through real prostate cancer proteomic mass spectra data.