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无标记液相色谱-质谱联用蛋白质定量的数据处理方法与质量控制策略

Data processing methods and quality control strategies for label-free LC-MS protein quantification.

作者信息

Sandin Marianne, Teleman Johan, Malmström Johan, Levander Fredrik

机构信息

Department of Immunotechnology, Lund University, BMC D13, 22184 Lund, Sweden.

出版信息

Biochim Biophys Acta. 2014 Jan;1844(1 Pt A):29-41. doi: 10.1016/j.bbapap.2013.03.026. Epub 2013 Apr 6.

Abstract

Protein quantification using different LC-MS techniques is becoming a standard practice. However, with a multitude of experimental setups to choose from, as well as a wide array of software solutions for subsequent data processing, it is non-trivial to select the most appropriate workflow for a given biological question. In this review, we highlight different issues that need to be addressed by software for quantitative LC-MS experiments and describe different approaches that are available. With focus on label-free quantification, examples are discussed both for LC-MS/MS and LC-SRM data processing. We further elaborate on current quality control methodology for performing accurate protein quantification experiments. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

摘要

使用不同的液相色谱-质谱联用(LC-MS)技术进行蛋白质定量正成为一种标准做法。然而,由于有众多实验设置可供选择,以及用于后续数据处理的大量软件解决方案,为特定生物学问题选择最合适的工作流程并非易事。在本综述中,我们强调了用于定量LC-MS实验的软件需要解决的不同问题,并描述了可用的不同方法。重点在于无标记定量,讨论了LC-MS/MS和LC-SRM数据处理的示例。我们进一步阐述了用于进行准确蛋白质定量实验的当前质量控制方法。本文是名为:鉴定后时代的计算蛋白质组学的特刊的一部分。客座编辑:Martin Eisenacher和Christian Stephan。

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