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• W2022687384 abstract "Abstract Mass spectrometry (MS) is a technique of paramount importance in Proteomics, and developments in this field have been possible owing to novel MS instrumentation, experimental strategies, and bioinformatics tools. Today it is possible to identify and determine relative expression levels of thousands of proteins in a biological system by MS analysis of peptides produced by proteolytic digestion. In some situations, however, the precise characterization of a particular peptide species in a very complex peptide mixture is needed. While single‐fragment ion‐based scanning modes such as selected ion reaction monitoring (SIRM) or consecutive reaction monitoring (CRM) may be highly sensitive, they do not produce MS/MS information and their actual specificity must be determined in advance, a prerequisite that is not usually met in a basic research context. In such cases, the MS detector may be programmed to perform continuous MS/MS spectra on the peptide ion of interest in order to obtain structural information. This selected MS/MS ion monitoring (SMIM) mode has a number of advantages that are fully exploited by MS detectors that, like the linear ion trap, are characterized by high scanning speeds. In this work, we show some applications of this technique in the context of biological studies. These results were obtained by selecting an appropriate combination of scans according to the purpose of each one of these research scenarios. They include highly specific identification of proteins present in low amounts, characterization and relative quantification of post‐translational modifications such as phosphorylation and S ‐nitrosylation and species‐specific peptide identification. Copyright © 2007 John Wiley & Sons, Ltd." @default.
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• W2022687384 date "2007-10-24" @default.
• W2022687384 modified "2023-10-18" @default.
• W2022687384 title "High-sensitivity analysis of specific peptides in complex samples by selected MS/MS ion monitoring and linear ion trap mass spectrometry: Application to biological studies" @default.
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• W2022687384 doi "https://doi.org/10.1002/jms.1314" @default.
• W2022687384 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/17960563" @default.
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