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Prostate Cancer Biomarker Identification: A Comparative Study, Wenjuan Jiang
Prostate Cancer Biomarker Identification: A Comparative Study, Wenjuan Jiang
Computational Modeling & Simulation Engineering Theses & Dissertations
With the current development of proteomics techniques, the discovery of potential molecular biomarkers for early detection of prostate cancer has been greatly improved. In this thesis, we implemented five classifiers including the support vector machine (SVM), Bayesian Classifier, Decision Tree, Random Forest and the Multilayer perceptron (MLP) to test their effectiveness in prostate cancer biomarker identification using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) tissue imaging data. The classifiers were utilized to discriminate cancer mass spectra from normal ones for the data collected at the Eastern Virginia Medical School (EVMS). There are 94 7 spectra from normal tissues and 27 from …