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生物信息学与蛋白质组学相遇——弥合质谱数据分析与细胞生物学之间的差距。

Bioinformatics meets proteomics--bridging the gap between mass spectrometry data analysis and cell biology.

作者信息

Kearney P, Thibault P

机构信息

Caprion Pharmaceuticals, 7150 Alexander Fleming, St-Laurent, Québec, H4S 2C8, Canada.

出版信息

J Bioinform Comput Biol. 2003 Apr;1(1):183-200. doi: 10.1142/s021972000300023x.

Abstract

Proteomics research programs typically comprise the identification of protein content of any given cell, their isoforms, splice variants, post-translational modifications, interacting partners and higher-order complexes under different conditions. These studies present significant analytical challenges owing to the high proteome complexity and the low abundance of the corresponding proteins, which often requires highly sensitive and resolving techniques. Mass spectrometry plays an important role in proteomics and has become an indispensable tool for molecular and cellular biology. However, the analysis of mass spectrometry data can be a daunting task in view of the complexity of the information to decipher, the accuracy and dynamic range of quantitative analysis, the availability of appropriate bioinformatics software and the overwhelming size of data files. The past ten years have witnessed significant technological advances in mass spectrometry-based proteomics and synergy with bioinformatics is vital to fulfill the expectations of biological discovery programs. We present here the technological capabilities of mass spectrometry and bioinformatics for mining the cellular proteome in the context of discovery programs aimed at trace-level protein identification and expression from microgram amounts of protein extracts from human tissues.

摘要

蛋白质组学研究项目通常包括鉴定任何给定细胞的蛋白质含量、其异构体、剪接变体、翻译后修饰、相互作用伙伴以及在不同条件下的高阶复合物。由于蛋白质组的高度复杂性以及相应蛋白质的低丰度,这些研究面临重大的分析挑战,这通常需要高度灵敏和高分辨率的技术。质谱在蛋白质组学中发挥着重要作用,已成为分子和细胞生物学中不可或缺的工具。然而,鉴于要解读的信息的复杂性、定量分析的准确性和动态范围、合适的生物信息学软件的可用性以及数据文件的庞大规模,质谱数据分析可能是一项艰巨的任务。在过去十年中,基于质谱的蛋白质组学取得了重大技术进展,与生物信息学的协同对于实现生物学发现项目的期望至关重要。在此,我们介绍质谱和生物信息学在发现项目背景下挖掘细胞蛋白质组的技术能力,这些项目旨在从微克量的人体组织蛋白质提取物中鉴定痕量水平的蛋白质并进行表达分析。

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