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Improving automatic peptide mass fingerprint protein identification by combining many peak sets
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0001-5163-2997
Department of Theoretical Physics, Lund University, Sölvegatan 14A, SE-223 62 Lund, Sweden.
Molecular Sciences, AstraZeneca RandD Lund, SE-221 87 Lund, Sweden.
Molecular Sciences, AstraZeneca RandD Lund, SE-221 87 Lund, Sweden.
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2004 (English)In: Journal of chromatography. B, ISSN 1570-0232, E-ISSN 1873-376X, Vol. 807, no 2, p. 209-215Article in journal (Refereed) Published
Abstract [en]

An automated peak picking strategy is presented where several peak sets with different signal-to-noise levels are combined to form a more reliable statement on the protein identity. The strategy is compared against both manual peak picking and industry standard automated peak picking on a set of mass spectra obtained after tryptic in gel digestion of 2D-gel samples from human fetal fibroblasts. The set of spectra contain samples ranging from strong to weak spectra, and the proposed multiple-scale method is shown to be much better on weak spectra than the industry standard method and a human operator, and equal in performance to these on strong and medium strong spectra. It is also demonstrated that peak sets selected by a human operator display a considerable variability and that it is impossible to speak of a single “true” peak set for a given spectrum. The described multiple-scale strategy both avoids time-consuming parameter tuning and exceeds the human operator in protein identification efficiency. The strategy therefore promises reliable automated user-independent protein identification using peptide mass fingerprints.

Place, publisher, year, edition, pages
Elsevier, 2004. Vol. 807, no 2, p. 209-215
Keywords [en]
Peak set combining, Peptide mass fingerprinting, Protein identification
National Category
Biochemistry Molecular Biology
Identifiers
URN: urn:nbn:se:hh:diva-225DOI: 10.1016/j.jchromb.2004.04.010ISI: 000222283800006PubMedID: 15203031Scopus ID: 2-s2.0-2942529269Local ID: 2082/520OAI: oai:DiVA.org:hh-225DiVA, id: diva2:237403
Available from: 2006-11-24 Created: 2006-11-24 Last updated: 2025-02-21Bibliographically approved

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Rögnvaldsson, Thorsteinn

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CiteExportLink to record
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