Host-driven evolution of PCV2: insights into genetic diversity and adaptation

The findings underscore the complex evolutionary trajectories followed by PCV2 on a global scale and suggest that the intensification of pig farming and associated management practices may have significantly shaped PCV2 evolution, contributing to the current epidemiological landscape.

Authors

Institutions

Publication Details

Journal
Frontiers in Immunology
Published
2025-05-26
DOI
https://doi.org/10.3389/fimmu.2025.1577436
Citations
3
Primary Topic
Animal Virus Infections Studies
Type
article
Field-Weighted Citation Impact
3.58

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Host-driven evolution of PCV2: insights into genetic diversity and adaptation

Michele Drigo, Matteo Legnardi, Giovanni Franzo, Mattia Cecchinato et al.
3 citations
Frontiers in Immunology
Animal Virus Infections Studies
3.58
article

Host-driven evolution of PCV2: insights into genetic diversity and adaptation

Michele Drigo, Matteo Legnardi, Giovanni Franzo, Mattia Cecchinato, Francesca Poletto, Claudia Maria Tucciarone, Riccardo Baston
article en
3 citations

Abstract

The findings underscore the complex evolutionary trajectories followed by PCV2 on a global scale and suggest that the intensification of pig farming and associated management practices may have significantly shaped PCV2 evolution, contributing to the current epidemiological landscape.

Frontiers in ImmunologyVol. 16
University of Padua (IT)
Università degli Studi di Padova
Openalex Percentile: Top 8%
Animal Virus Infections Studies
3.58
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.