PRISM: A data management system for high-throughput proteomics

被引：59

作者：

Kiebel, GR ^{[1
]}

Auberry, KJ ^{[1
]}

Jaitly, N ^{[1
]}

Clark, DA ^{[1
]}

Monroe, ME ^{[1
]}

Peterson, ES ^{[1
]}

Tolic, N ^{[1
]}

Anderson, GA ^{[1
]}

Smith, RD ^{[1
]}

机构：

[1] Pacific NW Natl Lab, Richland, WA 99352 USA

来源：

PROTEOMICS | 2006年 / 6卷 / 06期

关键词：

database; high-throughput; LC-MS; software;

D O I：

10.1002/pmic.200500500

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Advanced proteomic research efforts involving areas such as systems biology or biomarker discovery are enabled by the use of high level informatics tools that allow the effective analysis of large quantities of differing types of data originating from various studies. Performing such analyses on a large scale is not feasible without a computational platform that performs data processing and management tasks. Such a platform must be able to provide high-throughput operation while having sufficient flexibility to accommodate evolving data analysis tools and methodologies. The Proteomics Research Information Storage and Management system (PRISM) provides a platform that serves the needs of the accurate mass and time tag approach developed at Pacific Northwest National Laboratory. PRISM incorporates a diverse set of analysis tools and allows a wide range of operations to be incorporated by using a state machine that is accessible to independent, distributed computational nodes. The system has scaled well as data volume has increased over several years, while allowing adaptability for incorporating new and improved data analysis tools for more effective proteomics research.

引用

页码：1783 / 1790

页数：8

共 26 条

[1] A proteomic study of the HUPO Plasma Proteome Project's pilot samples using an accurate mass and time tag strategy [J].