Peak bagging for peptide mass fingerprinting

by: Zengyou He, Can Yang, Weichuan Yu

Bioinformatics, Vol. 24, No. 10. (15 May 2008), pp. 1293-1299.

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摘要

Motivation: Mass Spectrometry (MS)-based protein identification via peptide mass fingerprinting (PMF) is a key component in high-throughput proteome research. While PMF was the first commonly used protein identification method, provided higher throughput than the tandem MS-based method, its accuracy is lower than that of the tandem MS method. Thus, it is desirable to develop PMF-based algorithm with higher protein identification accuracy to facilitate proteome research. Results: We propose a peak bagging method for single MS-based protein identification. It combines results from multiple PMF algorithms, where each PMF algorithm takes a random peak subset as input. Evaluation with a set of real MALDI-TOF MS spectra shows that the new peak bagging method provides consistent improvements over the single PMF algorithm. Contact: eezyhe@ust.hk 10.1093/bioinformatics/btn123

@article{citeulike:2764618, abstract = {Motivation: Mass Spectrometry (MS)-based protein identification via peptide mass fingerprinting (PMF) is a key component in high-throughput proteome research. While PMF was the first commonly used protein identification method, provided higher throughput than the tandem MS-based method, its accuracy is lower than that of the tandem MS method. Thus, it is desirable to develop PMF-based algorithm with higher protein identification accuracy to facilitate proteome research. Results: We propose a peak bagging method for single MS-based protein identification. It combines results from multiple PMF algorithms, where each PMF algorithm takes a random peak subset as input. Evaluation with a set of real MALDI-TOF MS spectra shows that the new peak bagging method provides consistent improvements over the single PMF algorithm. Contact: eezyhe@ust.hk 10.1093/bioinformatics/btn123}, author = {He, Zengyou and Yang, Can and Yu, Weichuan }, citeulike-article-id = {2764618}, doi = {10.1093/bioinformatics/btn123}, journal = {Bioinformatics}, month = {May}, number = {10}, pages = {1293--1299}, posted-at = {2008-05-09 03:15:16}, priority = {2}, title = {Peak bagging for peptide mass fingerprinting}, url = {http://dx.doi.org/10.1093/bioinformatics/btn123}, volume = {24}, year = {2008} }

RIS record

TY - JOUR ID - citeulike:2764618 L3 - citeulike-article-id:2764618 TI - Peak bagging for peptide mass fingerprinting JF - Bioinformatics VL - 24 IS - 10 SP - 1293 EP - 1299 N2 - Motivation: Mass Spectrometry (MS)-based protein identification via peptide mass fingerprinting (PMF) is a key component in high-throughput proteome research. While PMF was the first commonly used protein identification method, provided higher throughput than the tandem MS-based method, its accuracy is lower than that of the tandem MS method. Thus, it is desirable to develop PMF-based algorithm with higher protein identification accuracy to facilitate proteome research. Results: We propose a peak bagging method for single MS-based protein identification. It combines results from multiple PMF algorithms, where each PMF algorithm takes a random peak subset as input. Evaluation with a set of real MALDI-TOF MS spectra shows that the new peak bagging method provides consistent improvements over the single PMF algorithm. Contact: eezyhe@ust.hk 10.1093/bioinformatics/btn123 AU - He, Zengyou AU - Yang, Can AU - Yu, Weichuan PY - 2008/05/15/ UR - http://dx.doi.org/10.1093/bioinformatics/btn123 ER -

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