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      Better score function for peptide identification with ETD MS/MS spectra

      1 , 2 , 3 , 2 , 3 , , 1

      BMC Bioinformatics

      BioMed Central

      The Eighth Asia Pacific Bioinformatics Conference (APBC 2010)

      18–21 January 2010

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          Abstract

          Background

          Tandem mass spectrometry (MS/MS) has become the primary way for protein identification in proteomics. A good score function for measuring the match quality between a peptide and an MS/MS spectrum is instrumental for the protein identification. Traditionally the to-be-measured peptides are fragmented with the collision induced dissociation (CID) method. More recently, the electron transfer dissociation (ETD) method was introduced and has proven to produce better fragment ion ladders for larger and more basic peptides. However, the existing software programs that analyze ETD MS/MS data are not as advanced as they are for CID.

          Results

          To take full advantage of ETD data, in this paper we develop a new score function to evaluate the match between a peptide and an ETD MS/MS spectrum. Experiments on real data demonstrated that this newly developed score function significantly improved the de novo sequencing accuracy of the PEAKS software on ETD data.

          Conclusion

          A new and better score function for ETD MS/MS peptide identification was developed. The method used to develop our ETD score function can be easily reused to train new score functions for other types of MS/MS data.

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          Most cited references 19

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          TANDEM: matching proteins with tandem mass spectra.

          Tandem mass spectra obtained from fragmenting peptide ions contain some peptide sequence specific information, but often there is not enough information to sequence the original peptide completely. Several proprietary software applications have been developed to attempt to match the spectra with a list of protein sequences that may contain the sequence of the peptide. The application TANDEM was written to provide the proteomics research community with a set of components that can be used to test new methods and algorithms for performing this type of sequence-to-data matching. The source code and binaries for this software are available at http://www.proteome.ca/opensource.html, for Windows, Linux and Macintosh OSX. The source code is made available under the Artistic License, from the authors.
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            Open mass spectrometry search algorithm.

            Large numbers of MS/MS peptide spectra generated in proteomics experiments require efficient, sensitive and specific algorithms for peptide identification. In the Open Mass Spectrometry Search Algorithm (OMSSA), specificity is calculated by a classic probability score using an explicit model for matching experimental spectra to sequences. At default thresholds, OMSSA matches more spectra from a standard protein cocktail than a comparable algorithm. OMSSA is designed to be faster than published algorithms in searching large MS/MS datasets.
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              Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry.

              Peptide sequence analysis using a combination of gas-phase ion/ion chemistry and tandem mass spectrometry (MS/MS) is demonstrated. Singly charged anthracene anions transfer an electron to multiply protonated peptides in a radio frequency quadrupole linear ion trap (QLT) and induce fragmentation of the peptide backbone along pathways that are analogous to those observed in electron capture dissociation. Modifications to the QLT that enable this ion/ion chemistry are presented, and automated acquisition of high-quality, single-scan electron transfer dissociation MS/MS spectra of phosphopeptides separated by nanoflow HPLC is described.
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                Author and article information

                Conference
                BMC Bioinformatics
                BMC Bioinformatics
                BioMed Central
                1471-2105
                2010
                18 January 2010
                : 11
                : Suppl 1
                : S4
                Affiliations
                [1 ]David R. Cheriton School of Computer Science, University of Waterloo, Canada
                [2 ]Bioinformatics Solutions, Inc., Waterloo, Canada
                [3 ]Department of Computer Science, University of Western Ontario, Canada
                Article
                1471-2105-11-S1-S4
                10.1186/1471-2105-11-S1-S4
                3009512
                20122213
                Copyright ©2010 Liu et al; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                The Eighth Asia Pacific Bioinformatics Conference (APBC 2010)
                Bangalore, India
                18–21 January 2010
                Categories
                Research

                Bioinformatics & Computational biology

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