Evidence map›Paper›PMID 41420049›Full record

ArticleNature biotechnology2025

Machine learning enables scalable and systematic hierarchical virus taxonomy.

Benjamin Bolduc, Olivier Zablocki, Dann Turner, Ho Bin Jang, Jiarong Guo, Evelien M Adriaenssens, Bas E Dutilh, Matthew B Sullivan

Abstract read
PubMed Publisher
In one paragraph

Article in Nature biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Hawaiian Geothermal Fumaroles Contain Diverse and Novel Viruses.bioRxiv : the preprint server for biology · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. We need to talk about the virome.Microbiome research reports · 2026
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Benjamin BolducDepartment of Microbiology, Ohio State University, Columbus, OH, USA. bolduc.10@osu.edu.ORCID http://orcid.org/0000-0003-2420-0755
Olivier ZablockiDepartment of Microbiology, Ohio State University, Columbus, OH, USA.ORCID http://orcid.org/0000-0001-7561-1373
Dann TurnerSchool of Applied Sciences, College of Health, Science and Society, University of the West of England, Bristol, UK.ORCID http://orcid.org/0000-0002-0249-4513
Ho Bin JangCenter for Study of Emerging and Re-emerging Viruses, Korea Virus Research Institute, Institute for Basic Science (IBS), Daejeon, Republic of Korea.ORCID http://orcid.org/0000-0003-1316-316X
Jiarong GuoDepartment of Microbiology, Ohio State University, Columbus, OH, USA.ORCID http://orcid.org/0000-0002-6903-5418
Evelien M AdriaenssensQuadram Institute Bioscience, Norwich Research Park, Norwich, UK.ORCID http://orcid.org/0000-0003-4826-5406
Bas E DutilhInstitute of Biodiversity, Ecology, and Evolution, Faculty of Biological Sciences, Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, Jena, Germany.ORCID http://orcid.org/0000-0003-2329-7890
Matthew B SullivanDepartment of Microbiology, Ohio State University, Columbus, OH, USA. sullivan.948@osu.edu.ORCID http://orcid.org/0000-0001-8398-8234

Funding

National Science Foundation (NSF) DBI-2022070National Science Foundation (NSF) DBI-2149505
6 · The paper itself

Abstract

Although virus ecogenomics has expanded access to and understanding of the virosphere, existing classification tools lack taxonomic resolution and are unable to scale to modern discovery-based datasets or classify previously unknown sequence space. Here we develop vConTACT3-a machine learning-based tool that improves scalability and accuracy of virus taxonomy. By optimizing gene-sharing thresholds and leveraging adaptive, realm-specific cut-offs, vConTACT3 expands classification to both eukaryote and prokaryote viruses for four of the six officially recognized realms, and establishes accurate hierarchical taxonomy from genus to order. Specifically, vConTACT3 achieves >95% agreement with official taxonomy for 35,545 and 13,524 public prokaryotic and eukaryotic virus genomes, respectively, to surpass vConTACT2 across most realms, while still uniquely classifying previously uncharacterized taxa, and doing so even faster. vConTACT3 application provides taxonomy assignments for tens of thousands of unclassified taxa rapidly, automatically and systematically; evaluates virus sequence space to reveal support for fewer taxonomic ranks than currently available and identifies taxonomically challenging areas across the virosphere.

Identifiers

PMID41420049

What OpenQuestion holds

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Registered trials

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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.