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题名

Comprehensive Evaluation and Optimization of the Data-Dependent LC-MS/MS Workflow for Deep Proteome Profiling

作者
通讯作者Tian, Ruijun; Liu, Chao
发表日期
2023-05-10
DOI
发表期刊
ISSN
0003-2700
EISSN
1520-6882
卷号95期号:20页码:7897-7905
摘要
Data-dependentliquid chromatography-tandem massspectrometry(LC-MS/MS) is widely used in proteomic analyses. A well-performedLC-MS/MS workflow, which involves multiple procedures and interdependentmetrics, is a prerequisite for deep proteome profiling. Researchershave previously evaluated LC-MS/MS performance mainly basedon the number of identified peptides and proteins. However, this isnot a comprehensive approach. This motivates us to develop MSRefine,which aims to evaluate and optimize the performance of the LC-MS/MSworkflow for data-dependent acquisition (DDA) proteomics. It extracts 47 kinds of metrics, scores the metrics, and reports visual results,assisting users in evaluating the workflow, locating problems, andproviding optimizing strategies. In this study, we compared and analyzedmultiple pairs of datasets spanning different samples, methods, andinstruments and demonstrated that the comprehensive visual metricsand scores in MSRefine enable us to evaluate the performance of thevarious experiments and provide optimal strategies for the identificationof more peptides and proteins.
相关链接[来源记录]
收录类别
SCI ; EI
语种
英语
重要成果
NI论文
学校署名
通讯
资助项目
National Key R&D Program of China["2021YFA1301602","2021YFA1301603"] ; National Natural Science Foundation of China[32171442]
WOS研究方向
Chemistry
WOS类目
Chemistry, Analytical
WOS记录号
WOS:001010178800001
出版者
EI入藏号
20232314180995
EI主题词
Liquid chromatography ; Mass spectrometry ; Molecular biology
EI分类号
Biology:461.9 ; Chemistry:801
ESI学科分类
CHEMISTRY
来源库
Web of Science
引用统计
被引频次[WOS]:2
成果类型期刊论文
条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/549158
专题理学院_化学系
作者单位
1.Beihang Univ, Sch Biol Sci & Med Engn, Beijing 100191, Peoples R China
2.Beihang Univ, Sch Engn Med, Beijing 100191, Peoples R China
3.Southern Univ Sci & Technol, Dept Chem, Shenzhen 518055, Peoples R China
4.Southern Univ Sci & Technol, Res Ctr Chem Biol & Om Anal, Shenzhen 518055, Peoples R China
5.Zhejiang Univ, Inst Immunol, Sch Med, Hangzhou 310058, Zhejiang, Peoples R China
6.Zhejiang Univ, Sir Run Run Shaw Hosp, Sch Med, Dept Rheumatol, Hangzhou 310058, Zhejiang, Peoples R China
7.Shandong Univ Technol, Sch Comp Sci & Technol, Zibo 266590, Peoples R China
8.Shanghai Omicsolut Co Ltd, Shanghai 201199, Peoples R China
通讯作者单位化学系;  南方科技大学
推荐引用方式
GB/T 7714
Tang, Min,Huang, Peiwu,Wu, Lize,et al. Comprehensive Evaluation and Optimization of the Data-Dependent LC-MS/MS Workflow for Deep Proteome Profiling[J]. ANALYTICAL CHEMISTRY,2023,95(20):7897-7905.
APA
Tang, Min.,Huang, Peiwu.,Wu, Lize.,Zhou, Piyu.,Gong, Pengyun.,...&Liu, Chao.(2023).Comprehensive Evaluation and Optimization of the Data-Dependent LC-MS/MS Workflow for Deep Proteome Profiling.ANALYTICAL CHEMISTRY,95(20),7897-7905.
MLA
Tang, Min,et al."Comprehensive Evaluation and Optimization of the Data-Dependent LC-MS/MS Workflow for Deep Proteome Profiling".ANALYTICAL CHEMISTRY 95.20(2023):7897-7905.
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