Joel Hellewell

This paper introduces a Bayesian ordered logistic regression GWAS model for bacterial antimicrobial resistance phenotypes, showing improved variant discovery and MIC prediction by accounting for threshold-dependent effects.

The paper develops a mathematical model to predict vaccine replacement dynamics in Streptococcus pneumoniae and identifies optimal genomic surveillance strategies.

VIDRA models genetic dose-response relationships to predict drug mechanisms, therapeutic potential, and adverse events using phenotypically associated variants.

This paper introduces ska lo, a reference-free variant calling tool that uses a coloured De Bruijn graph to detect SNPs, insertions, deletions, and recombination events in pathogen genomes.

CELEBRIMBOR improves core gene identification in metagenome-assembled genomes by adjusting frequency thresholds based on genome completeness.

This paper introduces SKA2, a method for rapid and accurate genotyping of bacterial populations, showing superior variant recall and no false positives in outbreak simulations.

This study evaluates genetic metrics for inferring malaria transmission intensity changes using a transmission model and finds one metric can predict prevalence with 0.055 mean absolute error.