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http://hdl.handle.net/1942/23381
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DC Field | Value | Language |
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dc.contributor.author | BURZYKOWSKI, Tomasz | - |
dc.contributor.author | CLAESEN, Jurgen | - |
dc.contributor.author | VALKENBORG, Dirk | - |
dc.date.accessioned | 2017-03-16T08:42:30Z | - |
dc.date.available | 2017-03-16T08:42:30Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Datta, Susmitta; Mertens, Bart J.A. (Ed.). Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry, Springer International Publishing, p. 45-64 | - |
dc.identifier.isbn | 9783319458076 | - |
dc.identifier.uri | http://hdl.handle.net/1942/23381 | - |
dc.description.abstract | In shotgun proteomics, much attention and instrument time is dedicated to the generation of tandem mass spectra. These spectra contain information about the fragments of, ideally, one peptide and are used to infer the amino acid sequence of the scrutinized peptide. This type of spectrum acquisition is called a product ion scan, tandem MS, or MS2 spectrum. Another type of spectrum is the, often overlooked, precursor ion scan or MS1 spectrum that catalogs all ionized analytes present in a mass spectrometer. While MS2 spectra are important to identify the peptides and proteins in the sample, MS1 spectra provide valuable information about the quantity of the analyte. In this chapter, we describe some properties of MS1 spectra, such as the isotope distribution, and how these properties can be employed for low-level signal processing to reduce data complexity and as a tool for quality assurance. Furthermore, we describe some cases in which advanced modeling of the isotope distribution can be used in quantitative proteomics analysis. | - |
dc.language.iso | en | - |
dc.publisher | Springer International Publishing | - |
dc.relation.ispartofseries | Frontiers in Probability and the Statistical Sciences | - |
dc.rights | Springer International Publishing Switzerland | - |
dc.title | The Analysis of Peptide-Centric Mass-Spectrometry Data Utilizing Information About the Expected Isotope Distribution | - |
dc.type | Book Section | - |
dc.relation.edition | 1 | - |
local.bibliographicCitation.authors | Datta, Susmitta | - |
local.bibliographicCitation.authors | Mertens, Bart J.A. | - |
dc.identifier.epage | 64 | - |
dc.identifier.spage | 45 | - |
local.bibliographicCitation.jcat | B2 | - |
local.publisher.place | Cham, Switzerland | - |
local.type.refereed | Refereed | - |
local.type.specified | Book Section | - |
local.identifier.vabb | c:vabb:437860 | - |
dc.identifier.doi | 10.1007/978-3-319-45809-0_3 | - |
local.bibliographicCitation.btitle | Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry | - |
item.accessRights | Restricted Access | - |
item.validation | vabb 2019 | - |
item.fulltext | With Fulltext | - |
item.fullcitation | BURZYKOWSKI, Tomasz; CLAESEN, Jurgen & VALKENBORG, Dirk (2017) The Analysis of Peptide-Centric Mass-Spectrometry Data Utilizing Information About the Expected Isotope Distribution. In: Datta, Susmitta; Mertens, Bart J.A. (Ed.). Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry, Springer International Publishing, p. 45-64. | - |
item.contributor | BURZYKOWSKI, Tomasz | - |
item.contributor | CLAESEN, Jurgen | - |
item.contributor | VALKENBORG, Dirk | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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BookChapter_29Apr2016.pdf Restricted Access | Peer-reviewed author version | 583.47 kB | Adobe PDF | View/Open Request a copy |
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