{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T09:59:34Z","timestamp":1772099974284,"version":"3.50.1"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Identification of proteins by mass spectrometry\u2013based proteomics requires automated interpretation of peptide tandem mass spectrometry spectra. The effectiveness of peptide identification can be greatly improved by filtering out extraneous noise peaks before the subsequent database searching steps.<\/jats:p>\n               <jats:p>Results: Here we present a novel chemical rule-based filtering algorithm, termed CRF, which makes use of the predictable patterns (rules) of collision-induced peptide fragmentation. The algorithm selects peak pairs that obey the common fragmentation rules within plausible limits of mass tolerance as well as peak intensity and produces spectra that can be subsequently submitted to any search engine. CRF increases the positive predictive value and decreases the number of random matches and thus improves performance by 15\u201320% in terms of peptide annotation using search engines, such as X!Tandem. Importantly, the algorithm also achieves data compression rates of \u223c75%.<\/jats:p>\n               <jats:p>Availability: The MATLAB source code and a web server are available at http:\/\/hydrax.icgeb.trieste.it\/CRFilter\/<\/jats:p>\n               <jats:p>Contact: \u00a0myers@icgeb.org<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt061","type":"journal-article","created":{"date-parts":[[2013,2,16]],"date-time":"2013-02-16T05:36:01Z","timestamp":1360992961000},"page":"925-932","source":"Crossref","is-referenced-by-count":6,"title":["Chemical rule-based filtering of MS\/MS spectra"],"prefix":"10.1093","volume":"29","author":[{"given":"Be\u00e1ta","family":"Reiz","sequence":"first","affiliation":[{"name":"1 Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy, 2Laboratory of Bioinformatics, Biological Research Centre, Hungarian Academy of Sciences, H-6726 Szeged, Hungary, 3Institute of Informatics, University of Szeged, H-6720 Szeged, 4Faculty of Information Technology, P\u00e1zm\u00e1ny P\u00e9ter Catholic University, 1083 Budapest, Hungary and 5Protein Networks Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy"},{"name":"1 Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy, 2Laboratory of Bioinformatics, Biological Research Centre, Hungarian Academy of Sciences, H-6726 Szeged, Hungary, 3Institute of Informatics, University of Szeged, H-6720 Szeged, 4Faculty of Information Technology, P\u00e1zm\u00e1ny P\u00e9ter Catholic University, 1083 Budapest, Hungary and 5Protein Networks Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy"},{"name":"1 Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy, 2Laboratory of Bioinformatics, Biological Research Centre, Hungarian Academy of Sciences, H-6726 Szeged, Hungary, 3Institute of Informatics, University of Szeged, H-6720 Szeged, 4Faculty of Information Technology, P\u00e1zm\u00e1ny P\u00e9ter Catholic University, 1083 Budapest, Hungary and 5Protein Networks Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy"}]},{"given":"Attila","family":"Kert\u00e9sz-Farkas","sequence":"additional","affiliation":[{"name":"1 Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy, 2Laboratory of Bioinformatics, Biological Research Centre, Hungarian Academy of Sciences, H-6726 Szeged, Hungary, 3Institute of Informatics, University of Szeged, H-6720 Szeged, 4Faculty of Information Technology, P\u00e1zm\u00e1ny P\u00e9ter Catholic University, 1083 Budapest, Hungary and 5Protein Networks Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy"}]},{"given":"S\u00e1ndor","family":"Pongor","sequence":"additional","affiliation":[{"name":"1 Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy, 2Laboratory of Bioinformatics, Biological Research Centre, Hungarian Academy of Sciences, H-6726 Szeged, Hungary, 3Institute of Informatics, University of Szeged, H-6720 Szeged, 4Faculty of Information Technology, P\u00e1zm\u00e1ny P\u00e9ter Catholic University, 1083 Budapest, Hungary and 5Protein Networks Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy"},{"name":"1 Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy, 2Laboratory of Bioinformatics, Biological Research Centre, Hungarian Academy of Sciences, H-6726 Szeged, Hungary, 3Institute of Informatics, University of Szeged, H-6720 Szeged, 4Faculty of Information Technology, P\u00e1zm\u00e1ny P\u00e9ter Catholic University, 1083 Budapest, Hungary and 5Protein Networks Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy"}]},{"given":"Michael P.","family":"Myers","sequence":"additional","affiliation":[{"name":"1 Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy, 2Laboratory of Bioinformatics, Biological Research Centre, Hungarian Academy of Sciences, H-6726 Szeged, Hungary, 3Institute of Informatics, University of Szeged, H-6720 Szeged, 4Faculty of Information Technology, P\u00e1zm\u00e1ny P\u00e9ter Catholic University, 1083 Budapest, Hungary and 5Protein Networks Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy"},{"name":"1 Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy, 2Laboratory of Bioinformatics, Biological Research Centre, Hungarian Academy of Sciences, H-6726 Szeged, Hungary, 3Institute of Informatics, University of Szeged, H-6720 Szeged, 4Faculty of Information Technology, P\u00e1zm\u00e1ny P\u00e9ter Catholic University, 1083 Budapest, Hungary and 5Protein Networks Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy"}]}],"member":"286","published-online":{"date-parts":[[2013,2,15]]},"reference":[{"key":"2023020303311211200_btt061-B1","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1038\/nature01511","article-title":"Mass spectrometry-based proteomics","volume":"422","author":"Aebersold","year":"2003","journal-title":"Nature"},{"key":"2023020303311211200_btt061-B39","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1136\/bmj.309.6947.102","article-title":"Diagnostic tests 2: Predictive 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