Bioinformatics strategies for proteomic profiling

被引：53

作者：

White, CN ^{[1
]}

Chan, DW ^{[1
]}

Zhang, Z ^{[1
]}

机构：

[1] Johns Hopkins Med Inst, Ctr Biomarker Discovery, Dept Pathol, Baltimore, MD 21231 USA

来源：

CLINICAL BIOCHEMISTRY | 2004年 / 37卷 / 07期

关键词：

bioinformatics; proteomic profiling; mass spectrometry; SELDI; quality control;

D O I：

10.1016/j.clinbiochem.2004.05.004

中图分类号：

R446 [实验室诊断]; R-33 [实验医学、医学实验];

学科分类号：

1001 ;

摘要：

Clinical proteomics is an emerging field that involves the analysis of protein expression profiles of clinical samples for de novo discovery of disease-associated biomarkers and for gaining insight into the biology of disease processes. Mass spectrometry represents an important set of technologies for protein expression measurement. Among them, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS), because of its high throughput and on-chip sample processing capability, has become a popular tool for clinical proteomics. Bioinformatics plays a critical role in the analysis of SELDI data, and therefore, it is important to understand the issues associated with the analysis of clinical proteomic data. In this review, we discuss such issues and the bioinformatics strategies used for proteomic profiling. (C) 2004 The Canadian Society of Clinical Chemists. All rights reserved.

引用

页码：636 / 641

页数：6

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