ArticleComputational and mathematical methods in medicine2013
Naïve Bayes classifier with feature selection to identify phage virion proteins.
Article in Computational and mathematical methods in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
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Who cites it
56 citing papers in PubMed.
- StackPVP: a stacked ensemble classification framework for predicting phage virion proteins using integrated evolutionary features.Frontiers in microbiology · 2026Article
- Empathi: embedding-based phage protein annotation tool by hierarchical assignment.Nature communications · 2025Article
- A hybrid critical channels and optimal feature subset selection framework for EEG fatigue recognition.Scientific reports · 2025Article
- Machine learning driven dashboard for chronic myeloid leukemia prediction using protein sequences.PloS one · 2025Article
- PhageScanner: a reconfigurable machine learning framework for bacteriophage genomic and metagenomic feature annotation.Frontiers in microbiology · 2024Article
- Investigating alignment-free machine learning methods for HIV-1 subtype classification.Bioinformatics advances · 2024Article
- PhaVIP: Phage VIrion Protein classification based on chaos game representation and Vision Transformer.Bioinformatics (Oxford, England) · 2023Article
- Prediction of Phage Virion Proteins Using Machine Learning Methods.Molecules (Basel, Switzerland) · 2023Article
- Identifying the tumor location-associated candidate genes in development of new drugs for colorectal cancer using machine-learning-based approach.Medical & biological engineering & computing · 2022Article
- A machine learning technique for identifying DNA enhancer regions utilizing CIS-regulatory element patterns.Scientific reports · 2022Article
- DeePVP: Identification and classification of phage virion proteins using deep learning.GigaScience · 2022Article
- SCORPION is a stacking-based ensemble learning framework for accurate prediction of phage virion proteins.Scientific reports · 2022Article
- Large-scale comparative review and assessment of computational methods for phage virion proteins identification.EXCLI journal · 2022Review
- Ensemble Learning-Based Feature Selection for Phage Protein Prediction.Frontiers in microbiology · 2022Article
- Article
- Using multi-layer perceptron to identify origins of replication in eukaryotes via informative features.BMC bioinformatics · 2021Article
- Application of machine learning in bacteriophage research.BMC microbiology · 2021Review
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- iTAGPred: A Two-Level Prediction Model for Identification of Angiogenesis and Tumor Angiogenesis Biomarkers.Applied bionics and biomechanics · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Knowledge about the protein composition of phage virions is a key step to understand the functions of phage virion proteins. However, the experimental method to identify virion proteins is time consuming and expensive. Thus, it is highly desirable to develop novel computational methods for phage virion protein identification. In this study, a Naïve Bayes based method was proposed to predict phage virion proteins using amino acid composition and dipeptide composition. 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 79.15% for phage virion and nonvirion proteins classification, which are superior to that of other state-of-the-art classifiers. These results indicate that the proposed method could be as an effective and promising high-throughput method in phage proteomics research.
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