Protein mass spectrum data analysis method and system based on protein stability

By calculating the local noise variance and Bayesian probability correction, combined with adaptive Gaussian filtering and fuzzy membership, the problem of effective peptide signal peak identification of protein mass spectrometry data under non-stationary background noise conditions is solved, and accurate peptide signal peak extraction is achieved.

CN120636550AInactive Publication Date: 2025-09-12唐韵
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Patent Information

Application Number
CN202510689455.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-05-27
Publication Date
2025-09-12
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Under the non-stationary state of background noise, it is difficult to accurately identify the effective peptide signal peaks in protein mass spectrometry data in existing mass spectrometry data analysis, resulting in the generation of false positive peaks and the loss of key proteins.

Method used

By calculating the local noise variance of each data point in protein mass spectrometry data, determining the scale constraint parameters during smoothing, combining Bayesian probability for baseline correction, extracting edge-retained data of stable protein characteristic peaks, and using adaptive Gaussian filtering and fuzzy membership to identify peptide signal peaks.

Benefits of technology

Under the non-stationary background noise state, the effective peptide signal peaks in protein mass spectrometry data can be effectively identified and extracted, avoiding false peak identification and improving the stability and accuracy of identification.

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Abstract

The invention provides a protein mass spectrum data analysis method and system based on protein stability. The method comprises the following steps: determining scale constraint parameters of a sliding window during smoothing of protein mass spectrum data according to local noise variances at data points in the protein mass spectrum data; carrying out loss constraint on the edge of a protein stability characteristic peak in the protein mass spectrum data based on the scale constraint parameter in combination with a preset sliding window to obtain edge retention data of the protein stability characteristic peak; determining a fuzzy membership degree of each data point belonging to a protein stability characteristic peak according to a plurality of pre-identification peaks in the edge retention data and spatial distribution characteristics of each data point in the edge retention data; and performing baseline correction on the edge retention data based on Bayesian probability in combination with all fuzzy membership degrees, and further extracting peptide fragment signal peaks of the protein. According to the technical scheme provided by the invention, the effective peptide fragment signal peak in the protein mass spectrum data can be analyzed in a non-stationary background noise state.
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