Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps

摘要

Analysis and visualization of high-dimensional clinical proteomic spectra obtained from mass spectrometric measurements is a complicated issue. We present a wavelet based preprocessing combined with an unsupervised and supervised analysis by Self-Organizing Maps and a fuzzy variant thereof. This leads to an optimal encoding and a robust classifier incorporating the possibility of fuzzy labels.