ArticleFrontiers in bioengineering and biotechnology2020
Predicting Bacteriophage Enzymes and Hydrolases by Using Combined Features.
Article in Frontiers in bioengineering and biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Vitamin BISME communications · 2025Article
- A modified multiple-criteria decision-making approach based on a protein-protein interaction network to diagnose latent tuberculosis.BMC medical informatics and decision making · 2024Article
- Novel pelagiphage isolate Polarivirus skadi is a polar specialist that dominates SAR11-associated bacteriophage communities at high latitudes.The ISME journal · 2023Article
- Article
- The Use of Bacteriophages in Biotechnology and Recent Insights into Proteomics.Antibiotics (Basel, Switzerland) · 2022Review
- Treating Bacterial Infections with Bacteriophage-Based Enzybiotics: In Vitro, In Vivo and Clinical Application.Antibiotics (Basel, Switzerland) · 2021Review
- Predicting bacteriophage hosts based on sequences of annotated receptor-binding proteins.Scientific reports · 2021Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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