This paper develops a machine learning model to predict cross-neutralization potential between FMDV serotype O viruses using sequence data and identifies key genomic predictors.

PLoS Computational Biology · Sep 17, 2025Peer-reviewedImmunology

PRRSV-2 variant classification: a dynamic nomenclature for enhanced monitoring and surveillance

Kimberly L. VanderWaal, Nakarin Pamornchainavakul, Mariana Kikuti, Jianqiang Zhang, Michael A. Zeller, Giovani Trevisan, Stephanie Rossow, Mark Schwartz, Daniel C. L. Linhares, Derald Holtkamp, João Paulo Herrera da Silva, Cesar A. Corzo, Julia P. Baker, Tavis K. Anderson, Dennis N. Makau, Igor A. D. Paploski

This paper introduces a dynamic classification system for PRRSV-2 genetic variants using clustering algorithms and demonstrates its effectiveness in tracking genetic diversity over time.

mSphere · Jan 23, 2025Peer-reviewedMicrobiology

Phylogenetic-based methods for fine-scale classification of PRRSV-2 ORF5 sequences: a comparison of their robustness and reproducibility

Kimberly L. VanderWaal, Nakarin Pamornchainavakul, Mariana Kikuti, Daniel C. L. Linhares, Giovani Trevisan, Jianqiang Zhang, Tavis K. Anderson, Michael A. Zeller, Stephanie Rossow, Derald Holtkamp, Dennis N. Makau, Cesar A. Corzo, Igor A. D. Paploski

This study compares phylogenetic-based methods for fine-scale classification of PRRSV-2 ORF5 sequences, identifying robust approaches that improve resolution over RFLP-typing.

Frontiers in Virology · Aug 13, 2024Peer-reviewedBioinformatics