Abstract
Protein profiling using high-throughput tandem mass spectrometry has become a powerful method for analyzing changes in global protein expression patterns in cells and tissues as a function of developmental, physiologic and disease processes. This review summarizes the utility and practical application of multidimensional protein identification technology as a platform for comprehensive proteomic profiling of complex biologic samples. The strengths and potential problems and limitations associated with this powerful technology are discussed, with an emphasis placed on one of the biggest challenges currently facing large-scale expression profiling projects – namely, data analysis. Complementary bioinformatic computational data mining strategies, such as clustering, functional annotation and statistical inference, are also discussed as these are increasingly necessary for interpreting the results of global proteomic profiling studies.
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