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Assessing peptide de novo sequencing algorithms performance on large and diverse data sets
Author(s) -
Pitzer Erik,
Masselot Alexandre,
Colinge Jacques
Publication year - 2007
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200700224
Subject(s) - computer science , computational biology , peptide , mass spectrometry , tandem mass spectrometry , dna sequencing , biology , algorithm , chemistry , genetics , chromatography , biochemistry , dna
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.