| Literature DB >> 34236654 |
Avinash Yadav1, Federica Marini1, Alessandro Cuomo1, Tiziana Bonaldi2.
Abstract
Mass spectrometry (MS)-based proteomics is currently the most successful approach to measure and compare peptides and proteins in a large variety of biological samples. Modern mass spectrometers, equipped with high-resolution analyzers, provide large amounts of data output. This is the case of shotgun/bottom-up proteomics, which consists in the enzymatic digestion of protein into peptides that are then measured by MS-instruments through a data dependent acquisition (DDA) mode. Dedicated bioinformatic tools and platforms have been developed to face the increasing size and complexity of raw MS data that need to be processed and interpreted for large-scale protein identification and quantification. This chapter illustrates the most popular bioinformatics solution for the analysis of shotgun MS-proteomics data. A general description will be provided on the data preprocessing options and the different search engines available, including practical suggestions on how to optimize the parameters for peptide search, based on hands-on experience.Entities:
Keywords: Algorithms; Databases; Mass spectrometry; Protein identification; Protein quantification; Shotgun proteomics; Software
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Year: 2021 PMID: 34236654 DOI: 10.1007/978-1-0716-1641-3_3
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745