title: Improving peptide identification with single-stage mass spectrum peaks.
abstract: BACKGROUND
  Database searching is the major peptide identification method in shotgun proteomics. It searches tandem mass spectrometry (MS/MS) spectra against a protein database to identify target peptides. The success of such a database searching method relies on a scoring algorithm that can evaluate the quality of peptide-spectrum matches (PSMs) accurately. However, current scoring algorithms frequently generate inaccurate assignments due to variations and noises in the MS/MS spectra. To address this issue, we like to improve peptide identification by using additional information from other data sources.
  
  
  RESULTS
  Single-stage MS data is complementary to MS/MS data in the sense that it provides broader mass coverage but less sequence information. In this article, we show that single-stage MS data can be used to re-rank PSMs. The proposed method explores a linear combination of scores between MS and MS/MS data to perform re-ranking. Experimental results on real data show that such a re-ranking strategy improves the identification performance significantly.
  
  
  BACKGROUND
  http://bioinformatics.ust.hk/ReRankPSMwMS1.rar
authors.affiliation: Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China. eezyhe@ust.hk
authors.forename: Zengyou
authors.initials: Z
authors.lastname: He
authors.forename: Weichuan
authors.initials: W
authors.lastname: Yu
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D013058:Mass Spectrometry / Q000379:methods*; D010455:Peptides / Q000032:analysis / Q000737:chemistry*; D020539:Sequence Analysis, Protein / Q000379:methods
chemical_list: D010455:Peptides