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Identification of Antioxidants from Sequence Information Using Naïve Bayes
Antioxidant proteins are substances that protect cells from the damage caused by free radicals. Accurate identification of new antioxidant proteins is important in understanding their roles in delaying aging. Therefore, it is highly desirable to develop computational methods to identify antioxidant...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766563/ https://www.ncbi.nlm.nih.gov/pubmed/24062796 http://dx.doi.org/10.1155/2013/567529 |
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author | Feng, Peng-Mian Lin, Hao Chen, Wei |
author_facet | Feng, Peng-Mian Lin, Hao Chen, Wei |
author_sort | Feng, Peng-Mian |
collection | PubMed |
description | Antioxidant proteins are substances that protect cells from the damage caused by free radicals. Accurate identification of new antioxidant proteins is important in understanding their roles in delaying aging. Therefore, it is highly desirable to develop computational methods to identify antioxidant proteins. In this study, a Naïve Bayes-based method was proposed to predict antioxidant proteins using amino acid compositions and dipeptide compositions. In order to remove redundant information, a novel feature selection technique was employed to single out optimized features. In the jackknife test, the proposed method achieved an accuracy of 66.88% for the discrimination between antioxidant and nonantioxidant proteins, which is superior to that of other state-of-the-art classifiers. These results suggest that the proposed method could be an effective and promising high-throughput method for antioxidant protein identification. |
format | Online Article Text |
id | pubmed-3766563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-37665632013-09-23 Identification of Antioxidants from Sequence Information Using Naïve Bayes Feng, Peng-Mian Lin, Hao Chen, Wei Comput Math Methods Med Research Article Antioxidant proteins are substances that protect cells from the damage caused by free radicals. Accurate identification of new antioxidant proteins is important in understanding their roles in delaying aging. Therefore, it is highly desirable to develop computational methods to identify antioxidant proteins. In this study, a Naïve Bayes-based method was proposed to predict antioxidant proteins using amino acid compositions and dipeptide compositions. In order to remove redundant information, a novel feature selection technique was employed to single out optimized features. In the jackknife test, the proposed method achieved an accuracy of 66.88% for the discrimination between antioxidant and nonantioxidant proteins, which is superior to that of other state-of-the-art classifiers. These results suggest that the proposed method could be an effective and promising high-throughput method for antioxidant protein identification. Hindawi Publishing Corporation 2013 2013-08-24 /pmc/articles/PMC3766563/ /pubmed/24062796 http://dx.doi.org/10.1155/2013/567529 Text en Copyright © 2013 Peng-Mian Feng et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Feng, Peng-Mian Lin, Hao Chen, Wei Identification of Antioxidants from Sequence Information Using Naïve Bayes |
title | Identification of Antioxidants from Sequence Information Using Naïve Bayes |
title_full | Identification of Antioxidants from Sequence Information Using Naïve Bayes |
title_fullStr | Identification of Antioxidants from Sequence Information Using Naïve Bayes |
title_full_unstemmed | Identification of Antioxidants from Sequence Information Using Naïve Bayes |
title_short | Identification of Antioxidants from Sequence Information Using Naïve Bayes |
title_sort | identification of antioxidants from sequence information using naïve bayes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766563/ https://www.ncbi.nlm.nih.gov/pubmed/24062796 http://dx.doi.org/10.1155/2013/567529 |
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