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即时时间:未来,在未来!

IMass Time: The Future, in Future!

机构信息

1 Bioyong (Beijing) Technology Co., Ltd. , Beijing, China .

2 School of Medical and Health Sciences, Edith Cowan University , Joondalup, Australia .

出版信息

OMICS. 2018 Nov;22(11):679-695. doi: 10.1089/omi.2018.0162.

DOI:10.1089/omi.2018.0162
PMID:30457467
Abstract

Joseph John Thomson discovered and proved the existence of electrons through a series of experiments. His work earned him a Nobel Prize in 1906 and initiated the era of mass spectrometry (MS). In the intervening time, other researchers have also been awarded the Nobel Prize for significant advances in MS technology. The development of soft ionization techniques was central to the application of MS to large biological molecules and led to an unprecedented interest in the study of biomolecules such as proteins (proteomics), metabolites (metabolomics), carbohydrates (glycomics), and lipids (lipidomics), allowing a better understanding of the molecular underpinnings of health and disease. The interest in large molecules drove improvements in MS resolution and now the challenge is in data deconvolution, intelligent exploitation of heterogeneous data, and interpretation, all of which can be ameliorated with a proposed IMass technology. We define IMass as a combination of MS and artificial intelligence, with each performing a specific role. IMass will offer advantages such as improving speed, sensitivity, and analyses of large data that are presently not possible with MS alone. In this study, we present an overview of the MS considering historical perspectives and applications, challenges, as well as insightful highlights of IMass.

摘要

约瑟夫·约翰·汤姆森(Joseph John Thomson)通过一系列实验发现并证明了电子的存在。他的工作使他在 1906 年获得了诺贝尔奖,并开创了质谱(MS)时代。在此期间,其他研究人员也因 MS 技术的重大进展而获得诺贝尔奖。软电离技术的发展是将 MS 应用于大型生物分子的核心,导致人们对生物分子(如蛋白质组学、代谢组学、糖组学和脂质组学)的研究产生了前所未有的兴趣,从而更好地了解健康和疾病的分子基础。对大分子的兴趣推动了 MS 分辨率的提高,现在的挑战在于数据解卷积、异构数据的智能利用和解释,这些都可以通过拟议的 IMass 技术得到改善。我们将 IMass 定义为 MS 和人工智能的结合,它们各自发挥特定的作用。IMass 将提供一些优势,例如提高速度、灵敏度和分析大型数据集的能力,而这些目前仅凭 MS 是无法实现的。在这项研究中,我们概述了 MS 的历史观点和应用、挑战,以及对 IMass 的深刻见解。

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