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Improved label-free...
Improved label-free LC-MS analysis by wavelet-based noise rejection
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Cappadona, Salvatore (author)
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Nanni, Paolo (author)
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Benevento, Marco (author)
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- Levander, Fredrik (author)
- Lund University,Lunds universitet,Institutionen för immunteknologi,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Immunotechnology,Departments at LTH,Faculty of Engineering, LTH
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Versura, Pierra (author)
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Roda, Aldo (author)
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Cerutti, Sergio (author)
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Pattini, Linda (author)
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(creator_code:org_t)
- Hindawi Limited, 2010
- 2010
- English.
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In: Journal of Biomedicine and Biotechnology. - : Hindawi Limited. - 1110-7251 .- 1110-7243. ; 2010
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http://dx.doi.org/10... (free)
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Abstract
Subject headings
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- 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.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Immunologi inom det medicinska området (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Immunology in the medical area (hsv//eng)
Publication and Content Type
- art (subject category)
- ref (subject category)
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