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Title: Peptide identification

Abstract

Peptides are identified from a list of candidates using collision-induced dissociation tandem mass spectrometry data. A probabilistic model for the occurrence of spectral peaks corresponding to frequently observed partial peptide fragment ions is applied. As part of the identification procedure, a probability score is produced that indicates the likelihood of any given candidate being the correct match. The statistical significance of the score is known without necessarily having reference to the actual identity of the peptide. In one form of the invention, a genetic algorithm is applied to candidate peptides using an objective function that takes into account the number of shifted peaks appearing in the candidate spectrum relative to the test spectrum.

Inventors:
 [1];  [1];  [1];  [1]
  1. Richland, WA
Issue Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1019425
Patent Number(s):
7979214
Application Number:
US Patent Application 11/592,610
Assignee:
Battelle Memorial Institute (Richland, WA)
Patent Classifications (CPCs):
Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y10 - TECHNICAL SUBJECTS COVERED BY FORMER USPC Y10T - TECHNICAL SUBJECTS COVERED BY FORMER US CLASSIFICATION
H - ELECTRICITY H01 - BASIC ELECTRIC ELEMENTS H01J - ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
DOE Contract Number:  
AC06-76RL01830
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Jarman, Kristin H, Cannon, William R, Jarman, Kenneth D, and Heredia-Langner, Alejandro. Peptide identification. United States: N. p., 2011. Web.
Jarman, Kristin H, Cannon, William R, Jarman, Kenneth D, & Heredia-Langner, Alejandro. Peptide identification. United States.
Jarman, Kristin H, Cannon, William R, Jarman, Kenneth D, and Heredia-Langner, Alejandro. Tue . "Peptide identification". United States. https://www.osti.gov/servlets/purl/1019425.
@article{osti_1019425,
title = {Peptide identification},
author = {Jarman, Kristin H and Cannon, William R and Jarman, Kenneth D and Heredia-Langner, Alejandro},
abstractNote = {Peptides are identified from a list of candidates using collision-induced dissociation tandem mass spectrometry data. A probabilistic model for the occurrence of spectral peaks corresponding to frequently observed partial peptide fragment ions is applied. As part of the identification procedure, a probability score is produced that indicates the likelihood of any given candidate being the correct match. The statistical significance of the score is known without necessarily having reference to the actual identity of the peptide. In one form of the invention, a genetic algorithm is applied to candidate peptides using an objective function that takes into account the number of shifted peaks appearing in the candidate spectrum relative to the test spectrum.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2011},
month = {7}
}

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Works referenced in this record:

De Novo Peptide Sequencing via Tandem Mass Spectrometry
journal, October 1999


Analysis of Microbial Mixtures by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry
journal, December 2002


Role of Accurate Mass Measurement (±10 ppm) in Protein Identification Strategies Employing MS or MS/MS and Database Searching
journal, July 1999


Mutation-Tolerant Protein Identification by Mass Spectrometry
journal, December 2000


Sequence optimization as an alternative to de novo analysis of tandem mass spectrometry data
journal, April 2004


Scoring methods in MALDI peptide mass fingerprinting: ChemScore, and the ChemApplex program
journal, January 2002


An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database
journal, November 1994


ProFound:  An Expert System for Protein Identification Using Mass Spectrometric Peptide Mapping Information
journal, June 2000


An Algorithm for Automated Bacterial Identification Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry
journal, March 2000


Use of Artificial Neural Networks for the Accurate Prediction of Peptide Liquid Chromatography Elution Times in Proteome Analyses
journal, March 2003