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Automatic peak assignment and visualisation of copolymer mass spectrometry data using the ‘genetic algorithm’
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 mon...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507196/ https://www.ncbi.nlm.nih.gov/pubmed/31721321 http://dx.doi.org/10.1002/rcm.8654 |
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author | Town, James S. Gao, Yuqui Hancox, Ellis Liarou, Evelina Shegiwal, Ataulla Atkins, Christophe J. Haddleton, David |
author_facet | Town, James S. Gao, Yuqui Hancox, Ellis Liarou, Evelina Shegiwal, Ataulla Atkins, Christophe J. Haddleton, David |
author_sort | Town, James S. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7507196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75071962020-09-28 Automatic peak assignment and visualisation of copolymer mass spectrometry data using the ‘genetic algorithm’ Town, James S. Gao, Yuqui Hancox, Ellis Liarou, Evelina Shegiwal, Ataulla Atkins, Christophe J. Haddleton, David Rapid Commun Mass Spectrom Polymer Mass Spectrometry 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. John Wiley and Sons Inc. 2020-02-12 2020-08 /pmc/articles/PMC7507196/ /pubmed/31721321 http://dx.doi.org/10.1002/rcm.8654 Text en © 2019 The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Polymer Mass Spectrometry Town, James S. Gao, Yuqui Hancox, Ellis Liarou, Evelina Shegiwal, Ataulla Atkins, Christophe J. Haddleton, David Automatic peak assignment and visualisation of copolymer mass spectrometry data using the ‘genetic algorithm’ |
title | Automatic peak assignment and visualisation of copolymer mass spectrometry data using the ‘genetic algorithm’ |
title_full | Automatic peak assignment and visualisation of copolymer mass spectrometry data using the ‘genetic algorithm’ |
title_fullStr | Automatic peak assignment and visualisation of copolymer mass spectrometry data using the ‘genetic algorithm’ |
title_full_unstemmed | Automatic peak assignment and visualisation of copolymer mass spectrometry data using the ‘genetic algorithm’ |
title_short | Automatic peak assignment and visualisation of copolymer mass spectrometry data using the ‘genetic algorithm’ |
title_sort | automatic peak assignment and visualisation of copolymer mass spectrometry data using the ‘genetic algorithm’ |
topic | Polymer Mass Spectrometry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507196/ https://www.ncbi.nlm.nih.gov/pubmed/31721321 http://dx.doi.org/10.1002/rcm.8654 |
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