What type of study is this?

This is a Systematic Review study.

November 28, 2025VirusesOpen Access

Bioinformatics Tools and Approaches for Virus Discovery in Genomic Data: A Systematic Review

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Authors

JGJULIA GALEEVA PKPolina KuzmichenkoInSysBio (Russia)AMAlexander Manolov

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Implication

Systematic review highlights bioinformatics tools, including hidden Markov models and k-mer approaches, indicating advances in viral metagenomic data analysis.

Key Points

Viral metagenomic data presents challenges for traditional sequence comparison methods, affecting virus discovery.
Analysis reviews over 54 studies, showcasing bioinformatics tools like hidden Markov models and k-mer approaches.
Review conducted following PRISMA 2020 guidelines, emphasizing various methodologies for virus detection.
Continuous improvements in machine learning approaches highlight the evolution of virus detection strategies.

Cite This Study

GALEEVA et al. (2025) studied this question.

synapsesocial.com/papers/6928f12ea65b730b9ea7a873 https://doi.org/10.3390/v17121538

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Implication

Systematic review highlights bioinformatics tools, including hidden Markov models and k-mer approaches, indicating advances in viral metagenomic data analysis.

Bioinformatics Tools and Approaches for Virus Discovery in Genomic Data: A Systematic Review

Discussion

Member takes

Implication

Key Points

Cite This Study

Bioinformatics Tools and Approaches for Virus Discovery in Genomic Data: A Systematic Review

Discussion

Member takes

Implication

Key Points

Cite This Study

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