ArticleBriefings in bioinformatics2022
Accurate identification of bacteriophages from metagenomic data using Transformer.
Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.
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Who cites it
32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 56 citations in OpenAlex.
- Precision phage therapy in the AI/ML era: a systematic review of discovery-to-clinical translation evidence.Frontiers in microbiology · 2026Pooled it
- Bibliometric analysis of the application of artificial intelligence techniques in bacteriology: a PRISMA-guided research agenda.Frontiers in microbiology · 2025Pooled it
- Phage bioinformatics tools: a review of computational approaches for bacteriophage research.Briefings in bioinformatics · 2026Review
- Dental wastewater reveals a hidden reservoir of oral bacteriophage diversity.Microbiology spectrum · 2026Article
- PhaBOX2: an enhanced web server for discovering and analyzing viral contigs in metagenomic data.Nucleic acids research · 2026Article
- Evolutionary interplay: virulence, endolysin-like hydrolases, and defense correlations in the Erwinia amylovora pangenome.BMC microbiology · 2026Article
- Large-scale genomic analysis of jumbo phages: coevolution, genome architecture, and host interaction mechanisms.Animal microbiome · 2026Article
- Unraveling the activity of phage-carrying antibiotic resistance genes in constructed wetlands.Frontiers in cellular and infection microbiology · 2026Article
- Artificial intelligence empowers gut microbiota research in neurodegenerative diseases molecular mechanisms and precision therapy.iScience · 2025Review
- Emerging multifaceted roles of the microbiome in cancer susceptibility.World journal of clinical oncology · 2025Review
- Phage quest: a beginner's guide to explore viral diversity in the prokaryotic world.Briefings in bioinformatics · 2025Review
- Viral Diversity in Polar Hydrocarbon-Contaminated Soils: A Transect Study from King George Island, Antarctica.Food and environmental virology · 2025Article
- GiantHunter: accurate detection of giant virus in metagenomic data using reinforcement-learning and Monte Carlo tree search.Bioinformatics (Oxford, England) · 2025Article
- Red Mud Potentially Alleviates Ammonia Nitrogen Inhibition in Swine Manure Anaerobic Digestion by Enhancing Phage-Mediated Ammonia Assimilation.Microorganisms · 2025Article
- A review of neural networks for metagenomic binning.Briefings in bioinformatics · 2025Review
- Diversity of DNA viruses in the atmosphere of sub-Antarctic South Georgia.Frontiers in microbiology · 2025Article
- Comprehensive analysis of phage genomes from diverse environments reveals their diversity, potential applications, and interactions with hosts and other phages.Frontiers in microbiology · 2025Article
- Comprehensive genome analysis uncovers the diversity of jumbo phages in the pig gut microbiome.Frontiers in veterinary science · 2025Article
- Article
- Characterizing the gut phageome and phage-borne antimicrobial resistance genes in pigs.Microbiome · 2024Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationBacteriophages are viruses infecting bacteria. Being key players in microbial communities, they can regulate the composition/function of microbiome by infecting their bacterial hosts and mediating gene transfer. Recently, metagenomic sequencing, which can sequence all genetic materials from various microbiome, has become a popular means for new phage discovery. However, accurate and comprehensive detection of phages from the metagenomic data remains difficult. High diversity/abundance, and limited reference genomes pose major challenges for recruiting phage fragments from metagenomic data. Existing alignment-based or learning-based models have either low recall or precision on metagenomic data.
resultsIn this work, we adopt the state-of-the-art language model, Transformer, to conduct contextual embedding for phage contigs. By constructing a protein-cluster vocabulary, we can feed both the protein composition and the proteins' positions from each contig into the Transformer. The Transformer can learn the protein organization and associations using the self-attention mechanism and predicts the label for test contigs. We rigorously tested our developed tool named PhaMer on multiple datasets with increasing difficulty, including quality RefSeq genomes, short contigs, simulated metagenomic data, mock metagenomic data and the public IMG/VR dataset. All the experimental results show that PhaMer outperforms the state-of-the-art tools. In the real metagenomic data experiment, PhaMer improves the F1-score of phage detection by 27%.
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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.