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Peptides are routinely identified from mass spectrometry-based proteomics experiments by matching observed spectra to peptides derived from protein databases. The error rates of these identifications can be estimated by target-decoy analysis, which involves matching spectra to shuffled or reversed peptides. Besides estimating error rates, decoy searches can be used by semi-supervised machine learning algorithms to increase the number of confidently identified peptides. As for all machinedoi:10.1186/1471-2105-13-s16-s3 pmid:23176259 pmcid:PMC3489528 fatcat:ohqvuwz4abe2vdem6kotmprooq