ArticleMethods in molecular biology (Clifton, N.J.)2025
Bioinformatic Identification of Viral Genomes from High-Throughput Metagenomic Sequencing Data.
Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- The gut virome and regulatory T cell axis in health and systemic disease.Microbiome research reports · 2026Review
- Advanced Strategies in Phage Research: Innovations, Applications, and Challenges.Microorganisms · 2025Review
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
Virus identification has historically been performed through cell culture isolation and low-throughput methodologies that are limited often requiring previous information about the investigated viruses. These classical virological methods have been pivotal to many discoveries, but overall, they have a limited capacity for characterization of highly divergent and novel viruses. Nowadays, new technologies such as next-generation sequencing have revolutionized the virology field, enabling unbiased high-throughput viral genome characterization. But although the sequencing bottleneck has been surpassed, we could not say the same for the bioinformatics bottleneck of fishing new viral genomes from these large datasets littered with host and other microbes sequencing data. Here, we describe a bioinformatic framework to process metagenomic or metatranscriptomic data, aiming to assemble, identify, and study the evolutionary relationship of viral sequences and genomes.
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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.