Abstract

The paper presents two analyzes of the MALDI-TOF mass spectrometry dataset. Both analyzes use the support vector machine as a tool to build a prediction model. The first analysis which is our contribution to the competition uses the given spectra data without further processing. In the second analysis, we employed an additional preprocessing step consisting of peak detection, peak alignment and feature selection based on statistical tests. The experimental results suggest that the preprocessing step with feature selection improves prediction accuracy.

Submitted: January 25, 2008 · Accepted: January 26, 2008 · Published: February 21, 2008

Recommended Citation

Pham, Thang V.; van de Wiel, Mark A.; and Jimenez, Connie R. (2008) "Support Vector Machine Approach to Separate Control and Breast Cancer Serum Samples," Statistical Applications in Genetics and Molecular Biology: Vol. 7 : Iss. 2, Article 11.
Available at: http://www.bepress.com/sagmb/vol7/iss2/art11