Assessing peptide de novo sequencing algorithms performance on large and diverse data sets |
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Authors: | Pitzer Erik Masselot Alexandre Colinge Jacques |
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Affiliation: | Bioinformatics Department, Upper Austria University of Applied Sciences at Hagenberg, Hagenberg, Austria. |
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Abstract: | De novo peptide sequencing algorithms are often tested on relatively small data sets made of excellent spectra. Since there are always more and more tandem mass spectra available, we have assembled six large, reliable, and diverse (three mass spectrometer types) data sets intended for such tests and we make them accessible via a web server. To exemplify their use we investigate the performance of Lutefisk, PepNovo, and PepNovoTag, three well-established peptide de novo sequencing programs. |
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Keywords: | Algorithm Bioinformatics De novo sequencing |
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