Hannah-Marie Martiny

PanRes is a curated database of antimicrobial resistance genes that uses structural clustering and HMMs to improve detection of resistance determinants in metagenomes.

The paper identifies co-occurring antimicrobial resistance genes (ARGs) in metagenomic datasets to highlight potential co-selection in resistomes across different environments.

The paper curates a large metagenomic dataset to study the global distribution and dynamics of antimicrobial resistance genes.

NetSolP predicts protein solubility in E. coli from sequence using transformers, achieving state-of-the-art performance with reduced dataset bias.

The paper develops a machine learning model to predict recombinant protein expression in Bacillus subtilis using deep protein representations, achieving moderate performance for prioritizing expression candidates.