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.
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Schleif, FM., Villmann, T., Hammer, B. (2007). Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps. In: Masulli, F., Mitra, S., Pasi, G. (eds) Applications of Fuzzy Sets Theory. WILF 2007. Lecture Notes in Computer Science(), vol 4578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73400-0_72
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DOI: https://doi.org/10.1007/978-3-540-73400-0_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73399-7
Online ISBN: 978-3-540-73400-0
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