ArticleNucleic acids research2026
PhaBOX2: an enhanced web server for discovering and analyzing viral contigs in metagenomic data.
Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Phage bioinformatics tools: a review of computational approaches for bacteriophage research.Briefings in bioinformatics · 2026Review
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Authors and funding
6 authors.
Funding
Abstract
Metagenomic sequencing has transformed virus discovery; however, downstream bioinformatic analyses for viral identification, classification, and host prediction remain fragmented across multiple tools. Here, we present PhaBOX2, a major upgrade that extends the platform from a specialized bacteriophage identification tool to a comprehensive and integrated suite for viral sequence analysis. PhaBOX2 broadens its detection, taxonomic, and host prediction scope beyond phages to enable the characterization of archaeal and eukaryotic viruses. The updated workflow incorporates rigorous quality control and quantitative analyses, automatically removes host contamination, clusters sequences into viral operational taxonomic units, and performs phylogenetic analysis based on marker genes. In contrast to traditional "black-box" deep learning approaches, PhaBOX2 combines alignment-based strategies with machine-learning models under a "glass-box" design philosophy, providing interpretable intermediate evidence alongside final predictions to improve transparency and biological interpretability. Powered by a dedicated high-performance computing infrastructure, the server delivers a fully automated, end-to-end workflow, while achieving an ~80% reduction in processing time. PhaBOX2 thus provides a robust and user-friendly ecosystem for viral metagenomic analysis and is freely available at https://phage.ee.cityu.edu.hk/.
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Registered trials
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