ArticleBioinformatics (Oxford, England)2019
PHANOTATE: a novel approach to gene identification in phage genomes.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 210 papers, 1 of them a synthesis that pooled it.
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Who cites it
210 citing papers in PubMed, 1 synthesis or guideline pooled it, 304 citations in OpenAlex.
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- A genomic catalog of the mouse gut virome reveals features associated with ageing.Nature communications · 2026Article
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- Unraveling a new Klebsiella phage KP47 against Klebsiella spp.BMC microbiology · 2026Article
- Decoding Viral Dark Matter: Metagenomic Prokaryotic Virus Characterization With Pharokka, Phold, and Phynteny.Current protocols · 2026Article
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- Genome sequences of 19Microbiology resource announcements · 2026Article
- Characterisation and In Planta Activity of Bacteriophages That Infect the Key Bacterial Species Associated With Acute Oak Decline.Microbial biotechnology · 2026Article
- Characterization ofPHAGE (New Rochelle, N.Y.) · 2026Article
- Novel Silviavirus phages with broad-host-range activity against methicillin resistant Staphylococcus aureus from seafood: comprehending the phenotypic and genotypic variability.Folia microbiologica · 2026Article
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- Eco-evolutionary dynamics of massive, parallel bacteriophage outbreaks in compost communities.Science advances · 2026Article
- Isolation of novel phages from a resistant Dorea longicatena strain reveals genes associated with phage resistance.Npj viruses · 2026Article
150 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationCurrently there are no tools specifically designed for annotating genes in phages. Several tools are available that have been adapted to run on phage genomes, but due to their underlying design, they are unable to capture the full complexity of phage genomes. Phages have adapted their genomes to be extremely compact, having adjacent genes that overlap and genes completely inside of other longer genes. This non-delineated genome structure makes it difficult for gene prediction using the currently available gene annotators. Here we present PHANOTATE, a novel method for gene calling specifically designed for phage genomes. Although the compact nature of genes in phages is a problem for current gene annotators, we exploit this property by treating a phage genome as a network of paths: where open reading frames are favorable, and overlaps and gaps are less favorable, but still possible. We represent this network of connections as a weighted graph, and use dynamic programing to find the optimal path.
resultsWe compare PHANOTATE to other gene callers by annotating a set of 2133 complete phage genomes from GenBank, using PHANOTATE and the three most popular gene callers. We found that the four programs agree on 82% of the total predicted genes, with PHANOTATE predicting more genes than the other three. We searched for these extra genes in both GenBank's non-redundant protein database and all of the metagenomes in the sequence read archive, and found that they are present at levels that suggest that these are functional protein-coding genes. AVAILABILITY AND IMPLEMENTATION: https://github.com/deprekate/PHANOTATE. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.