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Title: Method for predicting peptide detection in mass spectrometry

Abstract

A method of predicting whether a peptide present in a biological sample will be detected by analysis with a mass spectrometer. The method uses at least one mass spectrometer to perform repeated analysis of a sample containing peptides from proteins with known amino acids. The method then generates a data set of peptides identified as contained within the sample by the repeated analysis. The method then calculates the probability that a specific peptide in the data set was detected in the repeated analysis. The method then creates a plurality of vectors, where each vector has a plurality of dimensions, and each dimension represents a property of one or more of the amino acids present in each peptide and adjacent peptides in the data set. Using these vectors, the method then generates an algorithm from the plurality of vectors and the calculated probabilities that specific peptides in the data set were detected in the repeated analysis. The algorithm is thus capable of calculating the probability that a hypothetical peptide represented as a vector will be detected by a mass spectrometry based proteomic platform, given that the peptide is present in a sample introduced into a mass spectrometer.

Inventors:
 [1];  [2];  [2]
  1. West Richland, WA
  2. Richland, WA
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1013000
Patent Number(s):
7,756,646
Application Number:
11/394,839
Assignee:
Battelle Memorial Institute (Richland, WA) RLO
DOE Contract Number:  
AC06-76RL01830
Resource Type:
Patent
Country of Publication:
United States
Language:
English

Citation Formats

Kangas, Lars, Smith, Richard D, and Petritis, Konstantinos. Method for predicting peptide detection in mass spectrometry. United States: N. p., 2010. Web.
Kangas, Lars, Smith, Richard D, & Petritis, Konstantinos. Method for predicting peptide detection in mass spectrometry. United States.
Kangas, Lars, Smith, Richard D, and Petritis, Konstantinos. Tue . "Method for predicting peptide detection in mass spectrometry". United States. doi:. https://www.osti.gov/servlets/purl/1013000.
@article{osti_1013000,
title = {Method for predicting peptide detection in mass spectrometry},
author = {Kangas, Lars and Smith, Richard D and Petritis, Konstantinos},
abstractNote = {A method of predicting whether a peptide present in a biological sample will be detected by analysis with a mass spectrometer. The method uses at least one mass spectrometer to perform repeated analysis of a sample containing peptides from proteins with known amino acids. The method then generates a data set of peptides identified as contained within the sample by the repeated analysis. The method then calculates the probability that a specific peptide in the data set was detected in the repeated analysis. The method then creates a plurality of vectors, where each vector has a plurality of dimensions, and each dimension represents a property of one or more of the amino acids present in each peptide and adjacent peptides in the data set. Using these vectors, the method then generates an algorithm from the plurality of vectors and the calculated probabilities that specific peptides in the data set were detected in the repeated analysis. The algorithm is thus capable of calculating the probability that a hypothetical peptide represented as a vector will be detected by a mass spectrometry based proteomic platform, given that the peptide is present in a sample introduced into a mass spectrometer.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jul 13 00:00:00 EDT 2010},
month = {Tue Jul 13 00:00:00 EDT 2010}
}

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