Improved label-free LC-MS analysis by wavelet-based noise rejection.
Label-free LC-MS analysis allows determining the differential expression level of proteins in multiple samples, without the use of stable isotopes. This technique is based on the direct comparison of multiple runs, obtained by continuous detection in MS mode. Only differentially expressed peptides a...
| Publicado en: | Journal of Biomedicine & Biotechnology pp. 131505 - 131506 |
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| Autores principales: | , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
2010
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105081931&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105081931 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 11107243 137K jtl: Journal of Biomedicine & Biotechnology issn: 11107243 maglogo: N pubinfo: dt: 2010 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 105081931 2010748369 NLM20150965 PMC2817556 105081931 ppf: 131505 ppct: 1 formats: fmt: @attributes: type: P tig: atl: Improved label-free LC-MS analysis by wavelet-based noise rejection. aug: au: Cappadona S Nanni P Benevento M Levander F Versura P Roda A Cerutti S Pattini L affil: Department of Bioengineering, Politecnico di Milano, 20133 Milan, Italy. salvatore.cappadona@polimi.it sug: subj: Chromatography, Liquid Methods Mass Spectrometry Methods Peptides Proteomics Methods Signal Processing, Computer Assisted Dry Eye Syndromes Metabolism Proteins Software Tears ab: Label-free LC-MS analysis allows determining the differential expression level of proteins in multiple samples, without the use of stable isotopes. This technique is based on the direct comparison of multiple runs, obtained by continuous detection in MS mode. Only differentially expressed peptides are selected for further fragmentation, thus avoiding the bias toward abundant peptides typical of data-dependent tandem MS. The computational framework includes detection, alignment, normalization and matching of peaks across multiple sets, and several software packages are available to address these processing steps. Yet, more care should be taken to improve the quality of the LC-MS maps entering the pipeline, as this parameter severely affects the results of all downstream analyses. In this paper we show how the inclusion of a preprocessing step of background subtraction in a common laboratory pipeline can lead to an enhanced inclusion list of peptides selected for fragmentation and consequently to better protein identification. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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