A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
A cross-validation scheme for machine learning algorithms in shotgun proteomics
2012
BMC Bioinformatics
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 machine
doi:10.1186/1471-2105-13-s16-s3
pmid:23176259
pmcid:PMC3489528
fatcat:ohqvuwz4abe2vdem6kotmprooq