Recent developments in quantitative proteomics.
Recent developments in quantitative proteomics.
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DOI：
10.1016/j.mrgentox.2010.06.016
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发表时间：
2011-06-17
影响因子：
1.9
通讯作者：
Bern, Marshall
中科院分区：
文献类型：
--
作者：
Becker, Christopher H.;Bern, Marshall
关键词：
蛋白质组学是对蛋白质的大规模研究，包括科学家和医生对蛋白质表达和物理性质的许多兴趣。蛋白质组学仍然是一个快速发展的领域，大量的报告定期出现在技术增强和科学研究使用这些新的工具。这篇综述主要集中在蛋白质表达的定量方面和相关的计算机器，用于大规模鉴定蛋白质及其翻译后修饰。主要重点是液相色谱-质谱（LC-MS）方法和相关串联质谱（LC-MS/MS）的组合。串联质谱法或MS/MS涉及在分子解离事件之后在仪器内的第二次分析，以获得结构信息，包括但不限于序列信息。这篇评论进一步主要集中在体外消化蛋白质的研究称为自下而上或鸟枪蛋白质组学。最近的仪器改进的简要讨论之前的讨论亲和富集和蛋白质的消耗，然后通过审查的主要方法（无标记和同位素标记），使蛋白质表达定量测量，特别是在大量的蛋白质分析的背景下。然后讨论了用于从LC-MS/MS数据中识别肽和蛋白质的各种计算技术。这篇综述文章然后包括LC-MS方法的三维结构测定的简短讨论，并以蛋白质组学的统计和数据挖掘部分结束，包括对适当的临床研究和避免过度拟合大型数据集的评论。
Proteomics is the study of proteins on a large scale, encompassing the many interests scientists and physicians have in their expression and physical properties. Proteomics continues to be a rapidly expanding field, with a wealth of reports regularly appearing on technology enhancements and scientific studies using these new tools. This review focuses primarily on the quantitative aspect of protein expression and the associated computational machinery for making large-scale identifications of proteins and their post-translational modifications. The primary emphasis is on the combination of liquid chromatography-mass spectrometry (LC-MS) methods and associated tandem mass spectrometry (LC-MS/MS). Tandem mass spectrometry, or MS/MS, involves a second analysis within the instrument after a molecular dissociative event in order to obtain structural information including but not limited to sequence information. This review further focuses primarily on the study of in vitro digested proteins known as bottom-up or shotgun proteomics. A brief discussion of recent instrumental improvements precedes a discussion on affinity enrichment and depletion of proteins, followed by a review of the major approaches (label-free and isotope-labeling) to making protein expression measurements quantitative, especially in the context of profiling large numbers of proteins. Then a discussion follows on the various computational techniques used to identify peptides and proteins from LC-MS/MS data. This review article then includes a short discussion of LC-MS approaches to three-dimensional structure determination and concludes with a section on statistics and data mining for proteomics, including comments on properly powering clinical studies and avoiding over-fitting with large data sets.
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影响因子：
7.4
作者：
Clauser, KR;Baker, P;Burlingame, AL
通讯作者：
Burlingame, AL
影响因子：
15
作者：
BIEMANN, K;CONE, C;ARSENAUL.GP
通讯作者：
ARSENAUL.GP
影响因子：
5.8
作者：
Craig, R;Beavis, RC
通讯作者：
Beavis, RC
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y
影响因子：
64.8
作者：
Bennett, Eric J.;Shaler, Thomas A.;Kopito, Ron R.
通讯作者：
Kopito, Ron R.