Proteome Profiling without Selection Bias

Authors:
Annalisa Barla;Bettina Irler;Stefano Merler;Giuseppe Jurman;Silvano Paoli;Cesare Furlanello
Affiliations:
ITC-irst, Italy;ITC-irst, Italy;ITC-irst, Italy;ITC-irst, Italy;ITC-irst, Italy;ITC-irst, Italy
Venue:
CBMS '06 Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems
Year:
2006

Citing 0
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Abstract

In this paper, we present a method for predictive profiling of mass spectrometry data. The method integrates a spectra preprocessing pipeline with a complete validation setup aimed at identifying the discriminating peaks and at providing an unbiased estimate of the predictive classification error, based on SVM classifiers and on Entropy-based RFE procedure. A particular emphasis is placed upon avoiding selection bias effects throughout all the analysis steps, from preprocessing to peak importance ranking.