Analysis, statistical validation and dissemination of large-scale proteomics datasets generated by tandem MS

被引：139

作者：

Nesvizhskii, AI ^{[1
]}

Aebersold, R ^{[1
]}

机构：

[1] Inst Syst Biol, Seattle, WA 98103 USA

来源：

DRUG DISCOVERY TODAY | 2004年 / 9卷 / 04期

关键词：

D O I：

10.1016/S1359-6446(03)02978-7

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

Tandem mass spectrometry has been used increasingly for high-throughput analysis of complex protein samples. A major challenge lies in the consistent, objective and transparent analysis of the large amounts of data generated by such experiments and in their dissemination and publication. Here, we review currently available computational tools and discuss the need for statistical criteria in the analysis of large proteomics datasets.

引用

页码：173 / 181

页数：9

共 75 条

[71] The application of new software tools to quantitative protein profiling via isotope-coded affinity tag (ICAT) and tandem mass spectrometry - II. Evaluation of tandem mass spectrometry methodologies for large-scale protein analysis, and the application of statistical tools for data analysis and interpretation [J].