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Article: Computational methods for the comparative quantification of proteins in label-free LCn-MS experiments

TitleComputational methods for the comparative quantification of proteins in label-free LC<sup>n</sup>-MS experiments
Authors
KeywordsIon chromatogram extraction
Comparative quantification
Mass spectrometry-based proteomics
Spectral counting
Label-free quantification
Issue Date2008
Citation
Briefings in Bioinformatics, 2008, v. 9, n. 2, p. 156-165 How to Cite?
AbstractLiquid chromatography (LC) coupled to electrospray mass spectrometry (MS) is well established in high-throughput proteomics. The technology enables rapid identification of large numbers of proteins in a relatively short time. Comparative quantification of identified proteins from different samples is often regarded as the next step in proteomics experiments enabling the comparison of protein expression in different proteomes. Differential labeling of samples using stable isotope incorporation or conjugation is commonly used to compare protein levels between samples but these procedures are difficult to carry out in the laboratory and for large numbers of samples. Recently, comparative quantification of label-free LC n -MS proteomics data has emerged as an alternative approach. In this review, we discuss different computational approaches for extracting comparative quantitative information from label-free LC n -MS proteomics data. The procedure for computationally recovering the quantitative information is described. Furthermore, statistical tests used to evaluate the relevance of results will also be discussed. © The Author 2007. Published by Oxford University Press.
Persistent Identifierhttp://hdl.handle.net/10722/250864
ISSN
2023 Impact Factor: 6.8
2023 SCImago Journal Rankings: 2.143
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWong, Jason W.H.-
dc.contributor.authorSullivan, Matthew J.-
dc.contributor.authorCagney, Gerard-
dc.date.accessioned2018-02-01T01:53:55Z-
dc.date.available2018-02-01T01:53:55Z-
dc.date.issued2008-
dc.identifier.citationBriefings in Bioinformatics, 2008, v. 9, n. 2, p. 156-165-
dc.identifier.issn1467-5463-
dc.identifier.urihttp://hdl.handle.net/10722/250864-
dc.description.abstractLiquid chromatography (LC) coupled to electrospray mass spectrometry (MS) is well established in high-throughput proteomics. The technology enables rapid identification of large numbers of proteins in a relatively short time. Comparative quantification of identified proteins from different samples is often regarded as the next step in proteomics experiments enabling the comparison of protein expression in different proteomes. Differential labeling of samples using stable isotope incorporation or conjugation is commonly used to compare protein levels between samples but these procedures are difficult to carry out in the laboratory and for large numbers of samples. Recently, comparative quantification of label-free LC n -MS proteomics data has emerged as an alternative approach. In this review, we discuss different computational approaches for extracting comparative quantitative information from label-free LC n -MS proteomics data. The procedure for computationally recovering the quantitative information is described. Furthermore, statistical tests used to evaluate the relevance of results will also be discussed. © The Author 2007. Published by Oxford University Press.-
dc.languageeng-
dc.relation.ispartofBriefings in Bioinformatics-
dc.subjectIon chromatogram extraction-
dc.subjectComparative quantification-
dc.subjectMass spectrometry-based proteomics-
dc.subjectSpectral counting-
dc.subjectLabel-free quantification-
dc.titleComputational methods for the comparative quantification of proteins in label-free LC<sup>n</sup>-MS experiments-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/bib/bbm046-
dc.identifier.pmid17905794-
dc.identifier.scopuseid_2-s2.0-42049094894-
dc.identifier.volume9-
dc.identifier.issue2-
dc.identifier.spage156-
dc.identifier.epage165-
dc.identifier.eissn1477-4054-
dc.identifier.isiWOS:000254682400006-
dc.identifier.issnl1467-5463-

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