Recent advances in computational analysis of mass spectrometry for proteomic profiling

摘要

The proteome, defined as an organism's proteins and their actions, is a highly complex end-effector of molecular and cellular events. Differing amounts of proteins in a sample can be indicators of an individual's health status; thus, it is valuable to identify key proteins that serve as 'biomarkers' for diseases. Since the proteome cannot be simply inferred from the genome due to pre- and posttranslational modifications, a direct approach toward mapping the proteome must be taken. The difficulty in evaluating a large number of individual proteins has been eased with the development of high-throughput methods based on mass spectrometry (MS) of peptide or protein mixtures, bypassing the time-consuming, laborious process of protein purification. However, proteomic profiling by MS requires extensive computational analysis. This article describes key issues and recent advances in computational analysis of mass spectra for biomarker identification.