Computational Analysis of Mass Spectrometry Data Using Novel Combinatorial Methods

Abstract

The analysis of proteome profiles offers a new approach to understanding how cellular machinery functions and responds under certain conditions. By combining twodimensional electrophoresis with mass spectrometry (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 analysis in 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.