ReviewArchives of virology2018
Virus classification - where do you draw the line?
Review in Archives of virology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
56 citing papers in PubMed.
- Tailoring virus-inspired nanoparticles for advanced drug and gene delivery.Materials today. Bio · 2026Review
- Oncogenic HPV types identified in Paleolithic and Chalcolithic human genome sequencing data from Ust'-Ishim and Ötzi.Scientific reports · 2026Article
- Genome-wide comparative and taxonomic characterization of prophages in Stenotrophomonas maltophilia.Archives of microbiology · 2026Article
- Isolation and characterization of TayeBlu, a novel bacteriophage ofMicrobiology spectrum · 2026Article
- Drugs in the environment, viruses in the balance: a review of the untold nexus of pharmaceuticals and virology.Frontiers in public health · 2026Review
- Viral emergence and pandemic preparedness in a One Health framework.Nature reviews. Microbiology · 2026Review
- Review
- The Role of Gut Microbiota in Gastrointestinal Immune Homeostasis and Inflammation: Implications for Inflammatory Bowel Disease.Biomedicines · 2025Review
- Shedding light on the cell biology and diverse physiological functions of the migrasome.Cell & bioscience · 2025Review
- Multifractal analysis and support vector machine for the classification of coronaviruses and SARS-CoV-2 variants.Scientific reports · 2025Article
- Integrating Sequence- and Structure-Based Similarity Metrics for the Demarcation of Multiple Viral Taxonomic Levels.Viruses · 2025Article
- Biological characteristics and genome analysis of Citrobacter freundii phage K1M.Archives of virology · 2025Article
- Isolation and characterization of a roseophage representing a novel genus in the N4-like Rhodovirinae subfamily distributed in estuarine waters.BMC genomics · 2025Article
- Bacteriophages: A Challenge for Antimicrobial Therapy.Microorganisms · 2025Review
- Article
- There and turn back again: the application of phage serine integrases in eukaryotic systems.Frontiers in bioengineering and biotechnology · 2025Review
- In Vitro Evaluation of the Anti-Chikungunya Virus Activity of an Active Fraction Obtained fromViruses · 2024Article
- Article
- The use of phages for the biosynthesis of metal nanoparticles and their biological applications: A review.Journal of cellular and molecular medicine · 2024Review
- Genomic and Phenotypic Analysis ofMicroorganisms · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-throughput sequencing (HTS) and its use in recovering and assembling novel virus sequences from environmental, human clinical, veterinary and plant samples has unearthed a vast new catalogue of viruses. Their classification, known by their sequences alone, sets a major challenge to traditional virus taxonomy, especially at the family and species levels, which have been historically based largely on descriptive taxon definitions. These typically entail some knowledge of their phenotypic properties, including replication strategies, virion structure and clinical and epidemiological features, such as host range, geographical distribution and disease outcomes. Little to no information on these attributes is available, however, for viruses identified in metagenomic datasets. If such viruses are to be included in virus taxonomy, their assignments will have to be guided largely or entirely by metrics of genetic relatedness. The immediate problem here is that the International Committee on Taxonomy of Viruses (ICTV), an organisation that authorises the taxonomic classification of viruses, provides little or no guidance on how similar or how divergent viruses must be in order to be considered members of new species or new families. We have recently developed a method for scoring genomic (dis)similarity between viruses (Genome Relationships Applied to Virus Taxonomy - GRAViTy) among the eukaryotic and prokaryotic viruses currently classified by the ICTV. At the family and genus levels, we found large-scale consistency between genetic relationships and their taxonomic assignments for eukaryotic viruses of all genome configurations and genome sizes. Family assignments of prokaryotic viruses have, however, been made at a quite different genetic level, and groupings currently classified as sub-families are a much better match to the eukaryotic virus family level. These findings support the ongoing reorganisation of bacteriophage taxonomy by the ICTV Phage Study Group. A rapid and objective means to explore metagenomic viral diversity and make evidence-based assignments for such viruses at each taxonomic layer is essential. Analysis of sequences by GRAViTy provides evidence that family (and genus) assignments of currently classified viruses are largely underpinned by genomic relatedness, and these features could serve as a guide towards an evidence-based classification of metagenomic viruses in the future.
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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.