Protein secondary mass spectrometric identification method based on probability statistic model

A probabilistic statistical model and secondary mass spectrometry technology, which is applied in the direction of measuring devices, material analysis through electromagnetic means, instruments, etc., can solve the problems of not fully reflecting the ion characteristics of experimental mass spectrometry

Inactive Publication Date: 2012-06-13
JINAN UNIVERSITY
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Problems solved by technology

However, it uniformly defines the peak intensity as three values: 50 (b and y ions), 25 (b, y ions dehydration and deamination ions) and 10 (a ions), which do not fully reflect the characteristics of the experimental mass spectrometry ions

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  • Protein secondary mass spectrometric identification method based on probability statistic model
  • Protein secondary mass spectrometric identification method based on probability statistic model
  • Protein secondary mass spectrometric identification method based on probability statistic model

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Embodiment

[0098] Such as figure 1 As shown, a probabilistic statistical model-based protein secondary mass spectrometry identification method, comprising the following steps:

[0099] (1) Virtual enzymolysis protein database sequence, and establish peptide database and peptide database index for the peptide after enzymolysis according to the mass number of the peptide;

[0100] (2) According to the nucleoplasmic ratio of the parent ion in the experimental spectrum to be analyzed, find out the candidate peptides that meet the requirements in the peptide database described in step (1), and generate a theoretical spectrum that meets the requirements for all the candidate peptides found ;

[0101] (3) De-isotope and de-noising processing of the experimental spectrum to be analyzed;

[0102] (4) Match and score the experimental spectrum to be analyzed obtained in step (3) and the theoretical spectrum of each candidate peptide obtained in step (2), and select the candidate peptide with the ...

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Abstract

The invention discloses a protein secondary mass spectrometric identification method based on a probability statistic model. The method comprises the following steps of: firstly, virtualizing an enzymolysis protein database array, and establishing a peptide section database and a peptide section database index for peptide sections processed by the enzymolysis according to the mass number of the peptide sections; secondly, finding out standby peptide sections meeting the requirements from the peptide section database according to a nuclear-cytoplasmic ratio of parent ions in an experiment map to be analyzed, and generating a theoretical map meeting the requirements by all the standby peptide sections; thirdly, removing isotopes and noises from the experiment map to be analyzed; matching the processed experiment map to be analyzed and the theoretical map of each standby peptide section and grading, and selecting the standby peptide section with the highest score as an identification result of the experiment map; and finally, carrying out whole false positive control according to all the experiment map identification results. According to the invention, the quantity of effective massspectrums and the quantity of the protein peptide sections are higher than those of an existing algorithm; and the method has the advantages of capability of dynamically selecting peaks and fast operation speed.

Description

technical field [0001] The invention relates to the field of protein secondary mass spectrometry identification, in particular to a protein secondary mass spectrometry identification method based on a probability statistical model. Background technique [0002] With the emergence of two soft ionization techniques, matrix-assisted laser desorption ionization (MALDI) and electrospray (Electrospray Ionization, ESI), biological mass spectrometry can introduce fewer impurities and maintain the integrity of peptide molecules , so that biological mass spectrometry can be applied to protein analysis on a large scale. At present, biological mass spectrometry has become one of the supporting technologies for proteome research, which mainly uses tandem mass spectrometry (LC MS / MS) to analyze protein samples. In the bioinformatics research of proteome, mass spectrometry data processing is a very important research content, and its task is to infer the protein composition of the sample ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N27/62
Inventor 肖传乐马超刘帅陈晓舟何庆瑜
Owner JINAN UNIVERSITY
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