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使用“遗传算法”对共聚物质谱数据进行自动峰分配和可视化

Automatic peak assignment and visualisation of copolymer mass spectrometry data using the 'genetic algorithm'.

作者信息

Town James S, Gao Yuqui, Hancox Ellis, Liarou Evelina, Shegiwal Ataulla, Atkins Christophe J, Haddleton David

机构信息

Department of Chemistry, University of Warwick, Warwick, UK.

出版信息

Rapid Commun Mass Spectrom. 2020 Aug;34 Suppl 2(Suppl 2):e8654. doi: 10.1002/rcm.8654. Epub 2020 Feb 12.

Abstract

Copolymer analysis is vitally important as the materials have a wide variety of applications due to their tunable properties. Processing mass spectrometry data for copolymer samples can be very complex due to the increase in the number of species when the polymer chains are formed by two or more monomeric units. In this paper, we describe the use of the genetic algorithm for automated peak assignment of copolymers synthesised by a variety of polymerisation methods. We find that in using this method we are able to easily assign copolymer spectra in a few minutes and visualise them into heat maps. These heat maps allow us to look qualitatively at the distribution of the chains, by showing how they alter with different polymerisation techniques, and by changing the initial copolymer composition. This methodology is simple to use and requires little user input, which makes it well suited for use by less expert users. The data outputted by the automatic assignment may also allow for more complex data processing in the future.

摘要

共聚物分析至关重要,因为这些材料因其可调谐特性而具有广泛的应用。由于当聚合物链由两个或更多单体单元形成时物种数量增加,处理共聚物样品的质谱数据可能非常复杂。在本文中,我们描述了使用遗传算法对通过各种聚合方法合成的共聚物进行自动峰归属。我们发现,使用这种方法能够在几分钟内轻松地对共聚物光谱进行归属,并将其可视化成热图。这些热图通过展示链如何随不同的聚合技术以及通过改变初始共聚物组成而变化,使我们能够定性地查看链的分布。这种方法易于使用,几乎不需要用户输入,这使其非常适合不太专业的用户使用。自动归属输出的数据未来也可能允许进行更复杂的数据处理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4476/7507196/77d1e9e17fe3/RCM-34-e8654-g001.jpg

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