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Advanced Multidimensional Separations in Mass Spectrometry: Navigating the Big Data Deluge

机译:质谱中的高级多维分离:浏览大数据洪水

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摘要

Hybrid analytical instrumentation constructed around mass spectrometry (MS) is becoming the preferred technique for addressing many grand challenges in science and medicine. From the omics sciences to drug discovery and synthetic biology, multidimensional separations based on MS provide the high peak capacity and high measurement throughput necessary to obtain large-scale measurements used to infer systems-level information. In this article, we describe multidimensional MS configurations as technologies that are big data drivers and review some new and emerging strategies for mining information from large-scale datasets. We discuss the information content that can be obtained from individual dimensions, as well as the unique information that can be derived by comparing different levels of data. Finally, we summarize some emerging data visualization strategies that seek to make highly dimensional datasets both accessible and comprehensible.
机译:围绕质谱仪(MS)构建的混合分析仪器正成为解决科学和医学领域许多重大挑战的首选技术。从组学到药物发现和合成生物学,基于质谱的多维分离提供了获得用于推断系统级信息的大规模测量所必需的高峰容量和高测量通量。在本文中,我们将多维MS配置描述为是大数据驱动程序的技术,并回顾了一些新的和新兴的策略来从大规模数据集中挖掘信息。我们讨论了可以从各个维度获得的信息内容,以及可以通过比较不同级别的数据而得出的独特信息。最后,我们总结了一些新兴的数据可视化策略,这些策略试图使高维数据集既可访问又可理解。

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