Federico Di Marco

PatHoST reconstructs pathogen spatial distributions from host transcriptomes using weakly supervised learning, showing improved detection in both experimental and human SARS-CoV-2 data.

The paper develops a rules-based classifier to predict ciprofloxacin resistance in Klebsiella pneumoniae from genotype data and demonstrates its global distribution association with quinolone consumption.

InterScale models both local and global cellular interactions in spatial transcriptomics data, revealing spatially restricted differentiation programs and disease-associated tissue remodeling.

This paper reclassifies SHV β-lactamase alleles in K. pneumoniae genomes based on mutations, improving genotype-phenotype understanding and updating the Kleborate tool.

The paper demonstrates the use of dual host-bacterial gene expression analysis in FFPE tissues to study pathogenesis and virulence factor regulation during respiratory infections.