ArticleNAR genomics and bioinformatics2020
A network-based integrated framework for predicting virus-prokaryote interactions.
Article in NAR genomics and bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 2 of them syntheses 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.
The trial behind it
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
71 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- From genomic signals to prediction tools: a critical feature analysis and rigorous benchmark for phage-host prediction.Briefings in bioinformatics · 2025Pooled it
- Antimicrobial resistance crisis: could artificial intelligence be the solution?Military Medical Research · 2024Pooled it
- Fecal microbiota transplantation alters gut phage communities in a clinical trial for obesity.Microbiome · 2024Trial
- Review
- Innovative Applications of Artificial Intelligence in Bacteriophage Research: A New Chapter in Future Medicine.Microorganisms · 2026Review
- Chemical prophage induction selectively removes Vibrio from a pelagic Sargassum-derived multispecies biofilm.Environmental microbiome · 2026Article
- Identifying host-specific patterns in viral protein sequences to predict host spillover risk in animal and plant kingdoms.Scientific reports · 2026Article
- Tools and approaches to study the human gut virome: from the bench to bioinformatics.mSystems · 2026Review
- High-resolution phage-host assignment through key proteins using large language models.Nature communications · 2026Article
- Gut virome dynamics: from commensal to critical player in health and disease.Nature reviews. Gastroenterology & hepatology · 2026Review
- Plasmids as persistent genetic reservoirs of bacterial defense systems in wastewater treatment.Microbiome · 2026Article
- Bacteriophages in gut metagenomes: from analysis to application.Virology journal · 2026Review
- Co-occurrence of diverse defense systems shapes complex microbe-virus relationships in deep-sea cold seeps.Nature communications · 2026Article
- A comprehensive review of AI innovations for tackling antimicrobial resistance.Le infezioni in medicina · 2026Review
- A deep Siamese network framework for precision phage selection in pulmonary infections.Frontiers in medicine · 2026Article
- Unexplored diversity and molecular genetic signatures of chimallin and phuz encoding phages.BMC genomics · 2025Article
- Exploring diversity and distribution patterns of chicken gut bacteriophage community.Animal microbiome · 2025Article
- A machine learning approach to predict strain-specific phage-host interactions.Scientific reports · 2025Article
- Phage quest: a beginner's guide to explore viral diversity in the prokaryotic world.Briefings in bioinformatics · 2025Review
- Global biogeography of airborne viruses in public transit systems and their host interactions.Microbiome · 2025Article
11 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
9 authors.
Funding
Abstract
Metagenomic sequencing has greatly enhanced the discovery of viral genomic sequences; however, it remains challenging to identify the host(s) of these new viruses. We developed VirHostMatcher-Net, a flexible, network-based, Markov random field framework for predicting virus-prokaryote interactions using multiple, integrated features: CRISPR sequences and alignment-free similarity measures ([Formula: see text] and WIsH). Evaluation of this method on a benchmark set of 1462 known virus-prokaryote pairs yielded host prediction accuracy of 59% and 86% at the genus and phylum levels, representing 16-27% and 6-10% improvement, respectively, over previous single-feature prediction approaches. We applied our host prediction tool to crAssphage, a human gut phage, and two metagenomic virus datasets: marine viruses and viral contigs recovered from globally distributed, diverse habitats. Host predictions were frequently consistent with those of previous studies, but more importantly, this new tool made many more confident predictions than previous tools, up to nearly 3-fold more (
Identifiers
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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.