David L. Robertson

The paper introduces Flu Mutation Explorer, a web tool that integrates IAV genomic data with mutation annotations to help interpret host adaptation mutations.

This study evaluates how protein language models capture mutational processes and fitness landscapes, finding that explicit mutational accessibility improves predictions while historical biases degrade performance.

The paper investigates the emergence of the influenza A/H3N2 K subclade, finding limited antigenic change and age-dependent vaccine responses, suggesting non-antigenic selection pressures.

CD8scape predicts viral escape from CD8+ T cell response using HLA genotype and within-host sequence variation to identify immune escape potential.

Viro3D predicts and curates protein structures for 4,400 viruses, expanding structural coverage 30-fold and enabling functional and evolutionary analysis of viral proteins.

The paper identifies protein networks associated with virus-permissive and hostile cellular states through multi-omics analysis, revealing discrepancies between mRNA and protein levels and the role of phosphorylation in infection control.

The paper shows that XRN1-mediated RNA decay provides nucleotides for alphavirus replication by recycling monophosphate nucleotides through the salvage pathway.

This paper introduces EvoMIL, a deep learning method that predicts virus-host associations using protein language models and multiple instance learning, achieving improved accuracy in both prokaryotic and eukaryotic hosts.

PLM-interact improves PPI prediction by jointly encoding protein pairs, achieving 16-28% AUPR gains across multiple species.

Reanalysis of public environmental metatranscriptomes from the Huanan market links SARS-CoV-2 positivity to one wildlife stall containing raccoon dog, civet and bamboo rat genetic material.

This paper shows that protein language models can assess mutation effects in SARS-CoV-2 spike protein without multiple sequence alignments, capturing evolutionary constraints and variant properties.

HIHISIV is a database that integrates and provides tools to analyze gene expression data from HIV and SIV host immune responses in humans and nonhuman primates.

The paper develops an interactive 3D tool to explain SARS-CoV-2 spike protein mutations and variants, showing it improves public understanding compared to existing resources.

The paper uses machine learning to identify mutational signatures in SARS-CoV-2 genomes and links them to host antiviral molecules, showing these drive most of the virus's evolutionary changes.

The paper identifies conserved recombination patterns across six coronavirus subgenera and links them to transcriptional regulatory sequences and sequence features.

The paper quantifies unknown sequences in human microbiomes, finding 2% on average are taxonomically undefined, with higher rates in skin and oral microbiomes.

This study performs a meta-analysis of transcriptomics data to identify immune dysregulation signatures in SARS-CoV-2 infection, linking gene expression patterns to patient age and disease severity.

The paper introduces a method using profile HMM domains to analyze ASFV genome diversity, identifying differences between virulent and attenuated strains.

The paper shows that disease-associated genes are often the more evolutionarily constrained duplicates, challenging the compensatory model and introducing a new disease prediction model.

This paper applies network controllability theory to study how HIV-1 and HCV infections control host cell networks by targeting critical nodes more efficiently than uninfected states.

The paper reduces pathway redundancy using set cover, achieving significant reductions in redundancy while maintaining gene coverage.

The paper investigates how structural disorder in the HIV-1 V3 loop correlates with coreceptor switch from CCR5 to CXCR4, finding increased disorder in X4 viruses.

This paper introduces an image processing method for metagenomic binning using multi-resolution local binary patterns, showing improved performance over k-mer frequency methods.

The paper analyzes amino acid replacements in the 2013-2016 Ebola virus outbreak, identifying one significant mutation that may affect host specificity and adaptation to humans.