Disease classification from capillary electrophoresis: mass spectrometry

Authors:
Simon Rogers;Mark Girolami;Ronald Krebs;Harald Mischak
Affiliations:
Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, Glasgow, UK;Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, Glasgow, UK;Mosaiques Diagnostics and Therapeutics AG, Hannover, Germany;Mosaiques Diagnostics and Therapeutics AG, Hannover, Germany
Venue:
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Year:
2005

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Abstract

We investigate the possibility of using pattern recognition techniques to classify various disease types using data produced by a new form of rapid Mass Spectrometry. The data format has several advantages over other high-throughput technologies and as such could become a useful diagnostic tool. We investigate the binary and multi-class performances obtained using standard classifiers as the number of features is varied and conclude that there is potential in this technique and suggest research directions that would improve performance.