ReviewFEMS microbiology reviews2016
Computational approaches to predict bacteriophage-host relationships.
Review in FEMS microbiology reviews, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 273 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
273 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advances in phage-host interaction prediction: in silico method enhances the development of phage therapies.Briefings in bioinformatics · 2024Pooled it
- Phage Genomics and Bioinformatics in Therapeutic Development: Evidence Limits, Validation Gates, and Translational Decision-Making.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Innovative Applications of Artificial Intelligence in Bacteriophage Research: A New Chapter in Future Medicine.Microorganisms · 2026Review
- Bacteriophages as Phagobiotics: Scientific Rationale and Translational Boundaries for Gut Microbiome Modulation.Viruses · 2026Review
- Invertebrates gut viromes mediate microbial adaptation to pharmaceutical diversity under warming.Microbiome · 2026Article
- Computational tool choice impacts CRISPR spacer-protospacer detection.Bioinformatics (Oxford, England) · 2026Article
- Comprehensive analyses of archaeal viral genomes reveal genomic characteristics, divergence, and host interactions.Microbiome · 2026Article
- Eco-evolutionary dynamics of massive, parallel bacteriophage outbreaks in compost communities.Science advances · 2026Article
- Review
- Identifying host-specific patterns in viral protein sequences to predict host spillover risk in animal and plant kingdoms.Scientific reports · 2026Article
- RuSpacer: a CRISPR spacer database derived from ruminant-associated prokaryotes for virome analysis.Scientific reports · 2026Article
- Phage-Microbiota Interactions in the Gut: Implications for Health and Therapeutic Strategies.Probiotics and antimicrobial proteins · 2026Review
- High-resolution phage-host assignment through key proteins using large language models.Nature communications · 2026Article
- Diversity and ecological potential of sediment viruses from Chinese continental shelf seas.NPJ biofilms and microbiomes · 2026Article
- Hi-C sequencing deciphers phage and plasmid host networks in wastewater biofilms.Environmental science and ecotechnology · 2026Article
- Metagenomic Hi‑C Protocols for Viral Genome Binning, Taxonomic Annotation, and Interaction Network Visualization.Current protocols · 2026Article
- Viral communities from long-term anaerobic alkane-oxidizing enrichment cultures encode predicted cell surface adhesion functions.The ISME journal · 2026Article
- Towards accurate artificial intelligence models for strain-level phage-host prediction.Briefings in bioinformatics · 2026Article
- VIRE: a metagenome-derived, planetary-scale virome resource with environmental context.Nucleic acids research · 2026Article
- Computational Microbial and Viral Ecology Analysis.Methods in molecular biology (Clifton, N.J.) · 2026Article
213 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metagenomics has changed the face of virus discovery by enabling the accurate identification of viral genome sequences without requiring isolation of the viruses. As a result, metagenomic virus discovery leaves the first and most fundamental question about any novel virus unanswered: What host does the virus infect? The diversity of the global virosphere and the volumes of data obtained in metagenomic sequencing projects demand computational tools for virus-host prediction. We focus on bacteriophages (phages, viruses that infect bacteria), the most abundant and diverse group of viruses found in environmental metagenomes. By analyzing 820 phages with annotated hosts, we review and assess the predictive power of in silico phage-host signals. Sequence homology approaches are the most effective at identifying known phage-host pairs. Compositional and abundance-based methods contain significant signal for phage-host classification, providing opportunities for analyzing the unknowns in viral metagenomes. Together, these computational approaches further our knowledge of the interactions between phages and their hosts. Importantly, we find that all reviewed signals significantly link phages to their hosts, illustrating how current knowledge and insights about the interaction mechanisms and ecology of coevolving phages and bacteria can be exploited to predict phage-host relationships, with potential relevance for medical and industrial applications.
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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.