Tavis K. Anderson

This paper develops a multivalent mRNA-LNP vaccine with eight swine IAV HA antigens, showing broad neutralizing antibodies and protection against viral challenge.

SmartHisto reduces annotation effort for histopathology images using Bayesian active learning, achieving higher mean IoU than competing methods.

This study shows that influenza viruses use different evolutionary strategies in avian versus mammalian hosts, with reassortment dominating in birds and adaptation in mammals.

The paper introduces normalized asymmetric phylogenetic costs to quantify coevolutionary dynamics, showing they capture complex relationships in virus-host systems and detect novel gene pairings in viral genomes.

This study examines how maternal antibodies and weaning stress affect piglets' susceptibility to human H3N2 influenza A virus, showing that matched maternal antibodies reduce shedding and transmission while weaning increases viral spread.

This study analyzes Swine Influenza A Virus (SwIAV) genomic diversity in England from 2014 to 2021, identifying new HA clades and genotypes within the 1B lineage.

PREMISE improves metagenomic source assignment by using a quality-aware probabilistic framework, achieving high accuracy in both species and strain-level classification.

Splicer performs phylogenetic placement in sub-linear time, enabling efficient classification of large-scale genetic sequences with high accuracy.

This study shows vaccine-induced immunity drives antigenic drift in a human-origin H3N2 virus in swine, altering HA receptor binding and glycan specificity.

This study compares the pathogenicity of PRRSV 1-4-4 L1C.5 to historical Chinese HP-PRRSV JXwn06 and US strain MN184 in weaned pigs, finding L1C.5 and JXwn06 cause more severe disease than MN184.

This study quantifies the sources and sinks of influenza A virus genomic diversity in U.S. swine from 2009 to 2022, showing regional hotspots and the role of swine transport in diversity spread.

The paper conducts active surveillance of influenza A virus in swine farms and nurseries, revealing within-farm reassortment, cocirculation of subtypes, and human-to-swine transmission events.

TreeSort detects influenza A reassortment in thousands of genomes via clock-based tests; avian H7 reassorts most, and HA, NA, MP rarely reassort in human and H5N1.

Phylo-rs provides a fast, extensible Rust library for phylogenetic analysis with WebAssembly support and open-source availability.

This study identifies a reassortment event in wild birds leading to HPAI A(H5N1) infection in cattle and highlights the risk of virus spread through asymptomatic cattle to humans.

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.

The paper identifies genetic signatures in influenza A viruses associated with interspecies transmission between swine and humans using phylogenetic analysis and machine learning.

The paper shows human seasonal H3N2 influenza A viruses can transmit to pigs but are not sustained in the pig population, with limited spread and transmission observed.

This study experimentally reproduces HPAI H5N1 infection in dairy calves and cows, confirming clinical disease and viral transmission through respiratory and mammary routes.

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

The paper assesses the pandemic risk of swine H1N2 influenza viruses by analyzing their transmission potential and immune response in ferrets.

The paper introduces a logistic regression pipeline for classifying genetic sequences, achieving high accuracy even with degraded data and identifying clade-defining mutations.

This study characterizes the genetic and antigenic diversity of H1 and H3 influenza A viruses in Brazilian swine from 2010-2018, identifying distinct lineages and antigenic variation with implications for vaccine development.

This study uses machine learning to predict antigenic drift in swine influenza A viruses and validates predictions with experimental assays.

The paper develops a centralized database for swine pathogen sequences to monitor emerging pathogens and support genomic surveillance.