Charge Prediction Machine: Tool for Inferring Precursor Charge States of Electron Transfer Dissociation Tandem Mass Spectra

被引：13

作者：

Carvalho, Paulo C. ^{[1
,2
]}

Cociorva, Daniel ^{[2
]}

Wong, Catherine C. L. ^{[2
]}

Carvalho, Maria da Gloria da C. ^{[3
]}

Barbosa, Valmir C. ^{[1
]}

Yates, John R., III ^{[2
]}

机构：

[1] Univ Fed Rio de Janeiro, COPPE, Syst Engn & Comp Sci Program, BR-21941 Rio De Janeiro, Brazil

[2] Scripps Res Inst, Biol Mass Spectrometry Lab, La Jolla, CA 92037 USA

[3] Univ Fed Rio de Janeiro, Inst Biophys, Lab Control Gene Express, BR-21941 Rio De Janeiro, Brazil

来源：

ANALYTICAL CHEMISTRY | 2009年 / 81卷 / 05期

关键词：

PROTEIN IDENTIFICATION; SHOTGUN PROTEOMICS; YEAST PROTEOME; SPECTROMETRY; MS/MS; MODEL;

D O I：

10.1021/ac8025288

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

Electron transfer dissociation (ETD) can dissociate highly charged ions. Efficient analysis of ions dissociated with ETD requires accurate determination of charge states for calculation of molecular weight. We created an algorithm to assign the charge state of ions often used for ETD. The program, Charge Prediction Machine (CPM), uses Bayesian decision theory to account for different charge reduction processes encountered in M and can also handle multiplex spectra. CPM correctly assigned charge states to 98% of the 13 097 MS2 spectra from a combined data set of four experiments. In a comparison between CPM and a competing program, Charger (ThermoFisher), CPM produced half the mistakes.

引用

页码：1996 / 2003

页数：8

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