ArticleVirus genes2025
Global population dynamics and evolutionary selection in classical swine fever virus complete genomes: insights from Bayesian coalescent analysis.
Article in Virus genes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed.
- Post-vaccination seroconversion and lineage-level molecular characterization of classical swine fever virus in five northeastern states of India.Tropical animal health and production · 2026Article
- Epidemiological analysis, risk factors, and spatial-temporal clustering of classical swine fever virus in China.Porcine health management · 2026Article
- Emergence of a Candidate Novel Sub-Genotype 1.1d of Classical Swine Fever Virus in India: Insights from a Comprehensive NS5B Gene Analysis and Multi-Locus Phylogeny.Current microbiology · 2026Article
- Comparison of Viral RNA Extraction Protocols for Senecavirus A and Classical Swine Fever Virus.Folia microbiologica · 2025Article
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Authors and funding
9 authors.
Funding
Abstract
Classical swine fever virus (CSFV) is a pathogen that affects pigs and wild boars. This contagious RNA virus is a high threat to swine industries throughout the world because it has high mortality and morbidity rates, leading to economic losses. Although some studies have analyzed whole-genome sequences, but often focus on isolates from only a few countries, while others started with whole-genome analysis before narrowing down to specific gene region like E2. In addition, several studies have predominantly focused on isolated geographic regions. Our study leverages a global dataset of 220 CSFV whole-genome sequences retrieved from the NCBI repository along with two CSFV complete genome sequence from our laboratory (Accession Number: MH734359.1 and OR4282229.1) and carefully curated to 66 sequences. The refined dataset was subjected to Bayesian analysis along with selection pressure analysis. The outcome of this experiment, the mean substitution rate was estimated at 2.06 × 10
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