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Cited by 490

The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

MS Amanda, a Universal Identification Algorithm Optimized for High Accuracy Tandem Mass Spectra

Open access
Dorfer, Viktoria, Pichler, Peter, Stranzl, Thomas, Stadlmann, Johannes, Taus, Thomas, Winkler, Stephan, Mechtler, Karl·2014·Journal of Proteome Research

Abstract

Today's highly accurate spectra provided by modern tandem mass spectrometers offer considerable advantages for the analysis of proteomic samples of increased complexity. Among other factors, the quantity of reliably identified peptides is considerably influenced by the peptide identification algorithm. While most widely used search engines were developed when high-resolution mass spectrometry data were not readily available for fragment ion masses, we have designed a scoring algorithm particularly suitable for high mass accuracy. Our algorithm, MS Amanda, is generally applicable to HCD, ETD, and CID fragmentation type data. The algorithm confidently explains more spectra at the same false discovery rate than Mascot or SEQUEST on examined high mass accuracy data sets, with excellent overlap and identical peptide sequence identification for most spectra also explained by Mascot or SEQUEST. MS Amanda, available at http://ms.imp.ac.at/?goto=msamanda , is provided free of charge both as standalone version for integration into custom workflows and as a plugin for the Proteome Discoverer platform.

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Metadata

Authors
Dorfer, V., Pichler, P., Stranzl, T., Stadlmann, J., Taus, T., Winkler, S., & Mechtler, K.
Venue
Journal of Proteome Research
Published
2014-06-26
Volume
13
Issue
8
Pages
3679-3684
ISSN
  • 1535-3893 (ISSN-L)
  • 1535-3907
OpenAlex
W2087934409
Cited by
490
References
36
FWCI
12.24
Type
journal article
Language
en
Open access
hybrid

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