Stephanie Pillay

The paper predicts other meta-omics data from metagenomics using machine learning, showing reliable predictions for transcript and metabolite abundances but challenges in protein profiles, and demonstrates utility for inflammatory bowel disease classification.

This study compares the fecal microbiome of pigs with and without antibiotic exposure to assess changes in microbial communities and antibiotic resistance genes.

This study evaluates portable in-field DNA sequencing for pathogen and antimicrobial resistance detection, finding it feasible and comparable to traditional lab methods.

This study analyzes antibiotic resistance patterns in soil metagenomes across different types and locations, identifying key resistance genes and their environmental influences.

The paper benchmarks long-read de novo assemblers for eukaryotic genomes, finding that Flye performs best overall, and longer reads can improve assembly quality depending on genome complexity.