Scott A. Kuzdzal

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BACKGROUND Most cases of ovarian cancer are detected at later stages when the 5-year survival is approximately 15%, but 5-year survival approaches 90% when the cancer is detected early (stage I). To use mass spectrometry (MS) of serum proteins for early detection, a seamless workflow is needed that provides an opportunity for rapid profiling along with(More)
Proteomic patterns as a potential diagnostic technology has been well established for several cancer conditions and other diseases. The use of machine learning techniques such as decision trees, neural networks, genetic algorithms, and other methods has been the basis for pattern determination. Cancer is known to involve signaling pathways that are(More)
BACKGROUND Researchers typically search for disease markers using a "targeted" approach in which a hypothesis about the disease mechanism is tested and experimental results either confirm or disprove the involvement of a particular gene or protein in the disease. Recently, there has been interest in developing disease diagnostics based on unbiased(More)
A high-throughput software pipeline for analyzing high-performance mass spectral data sets has been developed to facilitate rapid and accurate biomarker determination. The software exploits the mass precision and resolution of high-performance instrumentation, bypasses peak-finding steps, and instead uses discrete m/z data points to identify putative(More)
Fractionation enhances the resolution of proteins with similar characteristics by reducing the number of proteins that comigrate in gels, thus facilitating the detection of lower-abundance proteins and the accurate determination of quantitative and qualitative differences in disease and normal samples. An efficient, reproducible microscale fractionation(More)
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