ArticleInternational journal of molecular sciences2018
Identification of Bacteriophage Virion Proteins Using Multinomial Naïve Bayes with g-Gap Feature Tree.
Article in International journal of molecular sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.
- Precision phage therapy in the AI/ML era: a systematic review of discovery-to-clinical translation evidence.Frontiers in microbiology · 2026Pooled it
- 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
- Special Protein or RNA Molecules Computational Identification.International journal of molecular sciences · 2023Article
- PhaVIP: Phage VIrion Protein classification based on chaos game representation and Vision Transformer.Bioinformatics (Oxford, England) · 2023Article
- 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
- Article
- Large-scale comparative review and assessment of computational methods for phage virion proteins identification.EXCLI journal · 2022Review
- Component Parts of Bacteriophage Virions Accurately Defined by a Machine-Learning Approach Built on Evolutionary Features.mSystems · 2021Article
- VirionFinder: Identification of Complete and Partial Prokaryote Virus Virion Protein From Virome Data Using the Sequence and Biochemical Properties of Amino Acids.Frontiers in microbiology · 2021Article
- Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation.Journal of computer-aided molecular design · 2020Article
- PVPred-SCM: Improved Prediction and Analysis of Phage Virion Proteins Using a Scoring Card Method.Cells · 2020Article
- Identification of Cancerlectins Using Support Vector Machines With Fusion of G-Gap Dipeptide.Frontiers in genetics · 2020Article
- Identifying Phage Virion Proteins by Using Two-Step Feature Selection Methods.Molecules (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bacteriophages, which are tremendously important to the ecology and evolution of bacteria, play a key role in the development of genetic engineering. Bacteriophage virion proteins are essential materials of the infectious viral particles and in charge of several of biological functions. The correct identification of bacteriophage virion proteins is of great importance for understanding both life at the molecular level and genetic evolution. However, few computational methods are available for identifying bacteriophage virion proteins. In this paper, we proposed a new method to predict bacteriophage virion proteins using a Multinomial Naïve Bayes classification model based on discrete feature generated from the g-gap feature tree. The accuracy of the proposed model reaches 98.37% with MCC of 96.27% in 10-fold cross-validation. This result suggests that the proposed method can be a useful approach in identifying bacteriophage virion proteins from sequence information. For the convenience of experimental scientists, a web server (PhagePred) that implements the proposed predictor is available, which can be freely accessed on the Internet.
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