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Predicting Bacteriophage Enzymes and Hydrolases by Using Combined Features
Bacteriophage is a type of virus that could infect the host bacteria. They have been applied in the treatment of pathogenic bacterial infection. Phage enzymes and hydrolases play the most important role in the destruction of bacterial cells. Correctly identifying the hydrolases coded by phage is not...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105632/ https://www.ncbi.nlm.nih.gov/pubmed/32266225 http://dx.doi.org/10.3389/fbioe.2020.00183 |
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author | Li, Hong-Fei Wang, Xian-Fang Tang, Hua |
author_facet | Li, Hong-Fei Wang, Xian-Fang Tang, Hua |
author_sort | Li, Hong-Fei |
collection | PubMed |
description | Bacteriophage is a type of virus that could infect the host bacteria. They have been applied in the treatment of pathogenic bacterial infection. Phage enzymes and hydrolases play the most important role in the destruction of bacterial cells. Correctly identifying the hydrolases coded by phage is not only beneficial to their function study, but also conducive to antibacteria drug discovery. Thus, this work aims to recognize the enzymes and hydrolases in phage. A combination of different features was used to represent samples of phage and hydrolase. A feature selection technique called analysis of variance was developed to optimize features. The classification was performed by using support vector machine (SVM). The prediction process includes two steps. The first step is to identify phage enzymes. The second step is to determine whether a phage enzyme is hydrolase or not. The jackknife cross-validated results showed that our method could produce overall accuracies of 85.1 and 94.3%, respectively, for the two predictions, demonstrating that the proposed method is promising. |
format | Online Article Text |
id | pubmed-7105632 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71056322020-04-07 Predicting Bacteriophage Enzymes and Hydrolases by Using Combined Features Li, Hong-Fei Wang, Xian-Fang Tang, Hua Front Bioeng Biotechnol Bioengineering and Biotechnology Bacteriophage is a type of virus that could infect the host bacteria. They have been applied in the treatment of pathogenic bacterial infection. Phage enzymes and hydrolases play the most important role in the destruction of bacterial cells. Correctly identifying the hydrolases coded by phage is not only beneficial to their function study, but also conducive to antibacteria drug discovery. Thus, this work aims to recognize the enzymes and hydrolases in phage. A combination of different features was used to represent samples of phage and hydrolase. A feature selection technique called analysis of variance was developed to optimize features. The classification was performed by using support vector machine (SVM). The prediction process includes two steps. The first step is to identify phage enzymes. The second step is to determine whether a phage enzyme is hydrolase or not. The jackknife cross-validated results showed that our method could produce overall accuracies of 85.1 and 94.3%, respectively, for the two predictions, demonstrating that the proposed method is promising. Frontiers Media S.A. 2020-03-24 /pmc/articles/PMC7105632/ /pubmed/32266225 http://dx.doi.org/10.3389/fbioe.2020.00183 Text en Copyright © 2020 Li, Wang and Tang. http://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 | Bioengineering and Biotechnology Li, Hong-Fei Wang, Xian-Fang Tang, Hua Predicting Bacteriophage Enzymes and Hydrolases by Using Combined Features |
title | Predicting Bacteriophage Enzymes and Hydrolases by Using Combined Features |
title_full | Predicting Bacteriophage Enzymes and Hydrolases by Using Combined Features |
title_fullStr | Predicting Bacteriophage Enzymes and Hydrolases by Using Combined Features |
title_full_unstemmed | Predicting Bacteriophage Enzymes and Hydrolases by Using Combined Features |
title_short | Predicting Bacteriophage Enzymes and Hydrolases by Using Combined Features |
title_sort | predicting bacteriophage enzymes and hydrolases by using combined features |
topic | Bioengineering and Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105632/ https://www.ncbi.nlm.nih.gov/pubmed/32266225 http://dx.doi.org/10.3389/fbioe.2020.00183 |
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