Automatic peak identification method

Details Automatic peak identification method Automatic peak identification method

2007-05-15

2007-05-15

Barlow, John (Department: 2863)

Data processing: measuring, calibrating, or testing

Measurement system

Measured signal processing

C356S303000

Reexamination Certificate

active

11386437

ABSTRACT:
The invention described herein details a protocol to improve analysis and peak identification in spectroscopic data. Bayesian methods are used to automatically identify peaks in data sets. After identifying peak shapes, the method tests the hypothesis that a given number of peaks is found within any given data window. If a peak is identified within a given window, then the likelihood function is maximized in order to estimate peak position and amplitude. This process yields a spectrum with high resolution and minimal artifacts. The method described herein is particularly useful for identifying peaks in data sets obtained from spectroscopy.

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Gulam-Razul et al., Bayesian Deconvolution in Nuclear Spectroscopy Using RJMCMC, 2002 IEEE.
Yanofsky et al., Determination of the Systematic and Random Measurement Error in an LC-FTICR Mass Spectroscopy Analysis of a Partially Characterized Complex Peptide Mixture, Sep. 1-5, 2004, Proceedings of the 26th Annual International Conference of the IEEE EMBS, pp. 216-219.
Schwarz-Selinger et al., Analysis of Multicomponent Mass Spectra Applying Bayesian Probability Theory, 2001, Journal of Mass Spectrometry, pp. 866-874.

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