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EECS Publication

Computational Analysis of Mass Spectrometry Data Using Novel Combinatorial Methods

A. Fadiel, M. A. Langston, X. Peng, A. D. Perkins, H. S. Taylor, O. Tuncalp, D. Vitello, P. Pevsner and F. Naftolin

The analysis of proteome profiles offers a new approach to understanding how cellular machinery functions and responds under certain conditions. By combining two-dimensional electrophoresis with mass pectrometry (MS), a snapshot of the cell's protein expression status and quantitative proteome profiling can be provided. As the cell's proteome becomes defined in normal and altered states, possible utilization of MS proteome profiling as a diagnostic tool becomes a reality. The ability of Matrix Assisted Laser Desorption Ionization Mass Spectrometry (MALDI-MS) to generate a spectrum with thousands of data points, necessitate the development of sophisticated analytical algorithms. In this paper, we describe how MALDI-MS can be used in monitoring proteomic profile in patients before and after treatment using a non- invasive sampling method. Because data analysisin this process possesses a challenge, we present a novel mathematical approach for analyzing data produced by MALDI MS, and discuss current applications of mass spectrometry in clinical medicine as well as challenges faced during procedures and experimentation. As a case study, we analyze protein expression patterns in premenopausal versus postmenopausal women. We also provide a proteomic profiling of premenopausal women versus postmenopausal women treated with estrogen as a hormone replacement therapy.

Published  2006-05-01 04:00:00  as  ut-cs-06-576 (ID:134)


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