SynthesisBriefings in bioinformatics2024
Advances in phage-host interaction prediction: in silico method enhances the development of phage therapies.
Synthesis in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Phylogeny-agnostic strain-level prediction of phage-host interactions from genomes using machine learning.Nature microbiology · 2026Article
- Distinct Evolutionary Selection Patterns in Temperate and Filamentous Phages of Phocaeicola vulgatus in Health and IBD.Research square · 2026Article
- Pharmacology of Bacteriophage Therapy in Children: A Re-Emerging Paradigm in Antibacterial Therapy.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2026Article
- Cross-family and phage-specific gene requirements for Klebsiella infection revealed by scalable RB-TnSeq genetic screens.PLoS genetics · 2026Article
- Artificial Intelligence in Bacteriophage Science: A Comprehensive Narrative Review of Applications, Challenges, and Translational Opportunities.Antibiotics (Basel, Switzerland) · 2026Review
- Isolation and characterization of novel bacteriophage, vB_AbaA_SWMUZ8, targeting multidrug-resistant Acinetobacter baumannii strains.BMC microbiology · 2026Article
- Phage-Microbiota Interactions in the Gut: Implications for Health and Therapeutic Strategies.Probiotics and antimicrobial proteins · 2026Review
- PhageCGRNet: Integrating Chaos Game Representation of Genomes with Convolutional Neural Network for accurate phage host classification prediction.PLoS computational biology · 2026Article
- Towards accurate artificial intelligence models for strain-level phage-host prediction.Briefings in bioinformatics · 2026Article
- Artificial intelligence-driven phage therapy in veterinary medicine: an adaptive One Health strategy to mitigate antimicrobial resistance in livestock systems.Frontiers in veterinary science · 2026Review
- Phage biobanks as enabling infrastructure for precision phage therapy in the era of antimicrobial resistance.Frontiers in antibiotics · 2026Article
- FusionPHI: A phage-host interaction prediction network model based on attention-driven multi-modal feature fusion.PloS one · 2026Article
- MVPHI: a multi-view learning framework for predicting complex microbial interactions.Scientific reports · 2025Article
- NRG-P0074 Viral Sample RU1 from UnclassifiedPHAGE (New Rochelle, N.Y.) · 2025Article
- Multivalent Immune-Protective Effects of Egg Yolk Immunoglobulin Y (IgY) Derived from Live or InactivatedInternational journal of molecular sciences · 2025Article
- Factors Affecting Phage-Bacteria Coevolution Dynamics.Viruses · 2025Review
- Predicting phage-host interaction via hyperbolic Poincaré graph embedding and large-scale protein language technique.iScience · 2025Article
- Review
- Comprehensive Genome Analysis of a Human-Derived β-Lactam-ResistantInfection and drug resistance · 2025Article
- PHIStruct: improving phage-host interaction prediction at low sequence similarity settings using structure-aware protein embeddings.Bioinformatics (Oxford, England) · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phages can specifically recognize and kill bacteria, which lead to important application value of bacteriophage in bacterial identification and typing, livestock aquaculture and treatment of human bacterial infection. Considering the variety of human-infected bacteria and the continuous discovery of numerous pathogenic bacteria, screening suitable therapeutic phages that are capable of infecting pathogens from massive phage databases has been a principal step in phage therapy design. Experimental methods to identify phage-host interaction (PHI) are time-consuming and expensive; high-throughput computational method to predict PHI is therefore a potential substitute. Here, we systemically review bioinformatic methods for predicting PHI, introduce reference databases and in silico models applied in these methods and highlight the strengths and challenges of current tools. Finally, we discuss the application scope and future research direction of computational prediction methods, which contribute to the performance improvement of prediction models and the development of personalized phage therapy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.