Bioinformatics Advance Access originally published online on June 18, 2008
Bioinformatics 2008 24(16):1812-1818; doi:10.1093/bioinformatics/btn316
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Biomarker selection and sample prediction for multi-category disease on MALDI-TOF data
1Department of Computer Science and Engineering, The University of Texas, Arlington, TX 76019, 2PerkinElmer Life & Analytical Sciences, Waleham, MA 02451 and 3Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, TX 77555, USA
*To whom correspondence should be addressed.
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Abstract |
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Motivation: Diseases normally progress through several stages. Therefore, biomarkers corresponding to each stage may exist. To deal with such a multi-category problem, including sample stage prediction and biomarker selection, we propose methods for classification and feature selection. The proposed classification method is based on two schemes: error-correcting output coding (ECOC) and pairwise coupling (PWC). The final decision for a test sample prediction is an integration of these two schemes. The biomarker pattern for distinguishing each disease category from another one is achieved by the development of an extended Markov blanket (EMB) feature selection method.
Results: In this study, a liver cancer matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) dataset was used, which comprises hepatocellular carcinoma (HCC), cirrhosis, and healthy spectra. Peak patterns were discovered for distinguishing pairwise categories among the three classes. Importance and reliability of individual peaks were presented by the measurements of certain weight values and frequencies. The classification capability of the proposed approach was compared with classical ECOC, random forest, Naive Bayes, and J48 methods.
Availability: Supplementary materials are available at http://visionlab.uta.edu/biomarker/bioinfo.htm
Contact: gao{at}uta.edu
Associate Editor: Jonathan Wren
Received on April 4, 2008; revised on May 25, 2008; accepted on June 12, 2008
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