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

Abstract. 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. Key words: fuzzy visualization, clinical proteomics, wavelet analysis, biomarker, spectra preprocessing

• Type: Conference
• Year: 2007
• Where: WILF
• Authors: Frank-Michael Schleif, Thomas Villmann, Barbara Hammer
• Keywords: Artificial Intelligence, Clinical Proteomic Spectra, Fuzzy Visualization, Mass Spectrometric Measurements, WILF 2007