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Utility of mass spectrometry for proteome analysis: part II. Ion-activation methods, statistics, bioinformatics and annotation

Journal

EXPERT REVIEW OF PROTEOMICS
Volume 6, Issue 2, Pages 171-197

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1586/EPR.09.4

Keywords

data analysis; fragmentation; molecular dissociation; normalization; ontology; pattern recognition

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This is the second article in a series, intended as a tutorial to provide the interested reader with an overview of the concepts not covered in part I, such as: the principles of ion-activation methods, the ability of mass-spectrometric methods to interface with various proteomic strategies, analysis techniques, bioinformatics and data interpretation and annotation. Although these are different topics, it is important that a reader has a basic and collective understanding of all of them for an overall appreciation of how to carry out and analyze a proteomic experiment. Different ion-activation methods for MS/MS, such as collision-induced dissociation (including postsource decay) and surface-induced dissociation, electron capture and electron-transfer dissociation, infrared multiphoton and blackbody infrared radiative dissociation have been discussed since they are used in proteomic research. The high dimensionality of data generated from proteomic studies requires an understanding of the underlying analytical procedures used to obtain these data, as well as the development of improved bioinformatics tools and data-mining approaches for efficient and accurate statistical analyses of biological samples from healthy and diseased individuals, in addition to determining the utility of the interpreted data. Currently available strategies for the analysis of the proteome by mass spectrometry, such as those employed for the analysis of substantially purified proteins and complex peptide mixtures, as well as hypothesis-driven strategies, have been elaborated upon. Processing steps prior to the analysis of mass spectrometry data, statistics and the several informatics steps currently used for the analysis of shotgun proteomic experiments, as well as proteomics ontology, are also discussed.

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