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A method for identifying moonlighting proteins based on linear discriminant analysis and bagging-SVM
Moonlighting proteins have at least two independent functions and are widely found in animals, plants and microorganisms. Moonlighting proteins play important roles in signal transduction, cell growth and movement, tumor inhibition, DNA synthesis and repair, and metabolism of biological macromolecul...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420859/ https://www.ncbi.nlm.nih.gov/pubmed/36046247 http://dx.doi.org/10.3389/fgene.2022.963349 |
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author | Chen, Yu Li, Sai Guo, Jifeng |
author_facet | Chen, Yu Li, Sai Guo, Jifeng |
author_sort | Chen, Yu |
collection | PubMed |
description | Moonlighting proteins have at least two independent functions and are widely found in animals, plants and microorganisms. Moonlighting proteins play important roles in signal transduction, cell growth and movement, tumor inhibition, DNA synthesis and repair, and metabolism of biological macromolecules. Moonlighting proteins are difficult to find through biological experiments, so many researchers identify moonlighting proteins through bioinformatics methods, but their accuracies are relatively low. Therefore, we propose a new method. In this study, we select SVMProt-188D as the feature input, and apply a model combining linear discriminant analysis and basic classifiers in machine learning to study moonlighting proteins, and perform bagging ensemble on the best-performing support vector machine. They are identified accurately and efficiently. The model achieves an accuracy of 93.26% and an F-sorce of 0.946 on the MPFit dataset, which is better than the existing MEL-MP model. Meanwhile, it also achieves good results on the other two moonlighting protein datasets. |
format | Online Article Text |
id | pubmed-9420859 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94208592022-08-30 A method for identifying moonlighting proteins based on linear discriminant analysis and bagging-SVM Chen, Yu Li, Sai Guo, Jifeng Front Genet Genetics Moonlighting proteins have at least two independent functions and are widely found in animals, plants and microorganisms. Moonlighting proteins play important roles in signal transduction, cell growth and movement, tumor inhibition, DNA synthesis and repair, and metabolism of biological macromolecules. Moonlighting proteins are difficult to find through biological experiments, so many researchers identify moonlighting proteins through bioinformatics methods, but their accuracies are relatively low. Therefore, we propose a new method. In this study, we select SVMProt-188D as the feature input, and apply a model combining linear discriminant analysis and basic classifiers in machine learning to study moonlighting proteins, and perform bagging ensemble on the best-performing support vector machine. They are identified accurately and efficiently. The model achieves an accuracy of 93.26% and an F-sorce of 0.946 on the MPFit dataset, which is better than the existing MEL-MP model. Meanwhile, it also achieves good results on the other two moonlighting protein datasets. Frontiers Media S.A. 2022-08-15 /pmc/articles/PMC9420859/ /pubmed/36046247 http://dx.doi.org/10.3389/fgene.2022.963349 Text en Copyright © 2022 Chen, Li and Guo. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Chen, Yu Li, Sai Guo, Jifeng A method for identifying moonlighting proteins based on linear discriminant analysis and bagging-SVM |
title | A method for identifying moonlighting proteins based on linear discriminant analysis and bagging-SVM |
title_full | A method for identifying moonlighting proteins based on linear discriminant analysis and bagging-SVM |
title_fullStr | A method for identifying moonlighting proteins based on linear discriminant analysis and bagging-SVM |
title_full_unstemmed | A method for identifying moonlighting proteins based on linear discriminant analysis and bagging-SVM |
title_short | A method for identifying moonlighting proteins based on linear discriminant analysis and bagging-SVM |
title_sort | method for identifying moonlighting proteins based on linear discriminant analysis and bagging-svm |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420859/ https://www.ncbi.nlm.nih.gov/pubmed/36046247 http://dx.doi.org/10.3389/fgene.2022.963349 |
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