BACKGROUND: The sequence database searching has been the dominant method for peptide identification, in which a large number of peptide spectra generated from LC/MS/MS experiments are searched using a search engine against theoretical fragmentation spectra derived from a protein sequences database or a spectral library. Selecting trustworthy peptide spectrum matches (PSMs) remains a challenge. RESULTS: A novel scoring method named FC-Ranker is developed to assign a nonnegative weight to each target PSM based on the possibility of its being correct. Particularly, the scores of PSMs are updated by using a fuzzy SVM classification model and a fuzzy silhouette index iteratively. Trustworthy PSMs will be assigned high scores when the algorithm stops. CONCLUSIONS: Our experimental studies show that FC-Ranker outperforms other post-database search algorithms over a variety of datasets, and it can be extended to solve a general classification problem with uncertain labels.
BACKGROUND: The sequence database searching has been the dominant method for peptide identification, in which a large number of peptide spectra generated from LC/MS/MS experiments are searched using a search engine against theoretical fragmentation spectra derived from a protein sequences database or a spectral library. Selecting trustworthy peptide spectrum matches (PSMs) remains a challenge. RESULTS: A novel scoring method named FC-Ranker is developed to assign a nonnegative weight to each target PSM based on the possibility of its being correct. Particularly, the scores of PSMs are updated by using a fuzzy SVM classification model and a fuzzy silhouette index iteratively. Trustworthy PSMs will be assigned high scores when the algorithm stops. CONCLUSIONS: Our experimental studies show that FC-Ranker outperforms other post-database search algorithms over a variety of datasets, and it can be extended to solve a general classification problem with uncertain labels.
Authors: Smriti R Ramakrishnan; Rui Mao; Aleksey A Nakorchevskiy; John T Prince; Willard S Willard; Weijia Xu; Edward M Marcotte; Daniel P Miranker Journal: Bioinformatics Date: 2006-04-03 Impact factor: 6.937
Authors: Richard E Higgs; Michael D Knierman; Angela Bonner Freeman; Lawrence M Gelbert; Sandeep T Patil; John E Hale Journal: J Proteome Res Date: 2007-03-31 Impact factor: 4.466
Authors: Steven L Sanders; Jennifer Jennings; Adrian Canutescu; Andrew J Link; P Anthony Weil Journal: Mol Cell Biol Date: 2002-07 Impact factor: 4.272