In this talk I will describe how to robustly identify peptide peaks in
mass spectroscopy SELDI-TOF data to separate
Cancer from Non-Cancer using a data base for Prostate Cancer. The talk will
give a brief overview of the disease and
discuss the potential of mass spectroscopy in cancer detection and
therapy. Next I will describe pattern identification, data preparation and
machine learning and noise analysis techniques that must be applied to the
data to obtain robust classifiers. Finally, I will describe the
metaclassifier which is based on a number of machine learning approaches
and show how it improves both specificity and sensitivity of predictions.
I will conclude with some suggestions for future work.
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