Melissa Beth Duhaime

This paper identifies viral biomarkers from oral and nasal metagenomes to detect human respiratory activity in environmental samples.

The paper uses metagenomic analysis and machine learning to study viral diversity and infection dynamics in Microcystis blooms, revealing broad host ranges and environmental adaptations.

The paper develops QuantMeta, a tool to quantify absolute abundances in metagenomes, and applies it to detect and measure DNA viruses in wastewater.

The paper introduces VHIP, a machine learning model that predicts virus-host interactions from genomic data, achieving 87.8% accuracy in predicting interactions at the species level.

The paper benchmarks 63 viral identification rulesets on mock metagenomes and aquatic samples, finding that combining rules increases recall but also false positives, with some combinations achieving high accuracy.

MetaboDirect is an open-source pipeline for processing FTICR-MS metabolomics data, offering automated analysis, visualization, and biochemical network generation.