Phage bioinformatics tools: a review of computational approaches for bacteriophage research.

Over 80 bioinformatics tools, achieving over 0.95 Matthews correlation in identification, now support comprehensive bacteriophage research across multiple computational paradigms.

• Why it matters: The rapid growth of metagenomic data and clinical interest in phage therapy highlight the need for reliable, standardized tools to improve phage identification, annotation, and host prediction, addressing current gaps in functional understanding and practical application.
• What they did: The review synthesizes recent computational approaches—sequence homology, machine learning, and foundation models—mapping key infrastructure components and proposing workflows tailored to user expertise and sample types, while identifying gaps in functional annotation and host prediction.
• The result: Advancing phage research requires rigorous evaluation, interoperable infrastructure, and clinically relevant prediction targets, as progress depends on overcoming annotation challenges and establishing community benchmarks for validation.