Statistical methods for analysing proteomic data

Jolanta Kawulok, Joanna Polańska

Abstract


The aim of the work reported in this paper was to develop statistical tools for mass spectra analysis. They would make it possible to detect cancer at its early stages. The main goal was to construct a classifier which would best distinguish people with cancer from a control group. First, the mass spectral signal is pre-processed. Next, the signals are modeled using Gaussian mixtures and they are later classified. The obtained results confirmed the effectiveness of the presented method.

Keywords


mass spectrometry; Gaussian Mixture Models; classification

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References


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DOI: http://dx.doi.org/10.21936/si2011_v32.n2A.262