Noelle Robertson Noyes

RAmpSim simulates hybridization capture in metagenomic sequencing by modeling thermodynamic binding and fragment generation, improving coverage accuracy over uniform baselines.

The paper develops a target-enriched metagenomic workflow to achieve variant-level resolution of microbial populations, demonstrating significant improvements in read targeting and variant detection.

The paper investigates NASM species in organic dairy cows, their antimicrobial activity against mastitis pathogens, and associations with udder health outcomes.

divider reconstructs haplotypes from long-read sequencing data, achieving higher accuracy than existing methods on synthetic and real datasets.

This paper develops a machine learning classifier to predict antibiotic resistance in Mycobacterium tuberculosis using genomic data and achieves high accuracy for first-line antibiotics.

KARGVA identifies antibiotic resistance gene variants from metagenomics data with high accuracy and efficiency, outperforming existing tools in detecting ARGVs.

The paper introduces Syotti, a heuristic method for designing DNA baits that outperforms existing methods in speed and coverage efficiency.

The paper evaluates AMR prediction methods using HTS data from clinical isolates, finding high variance in performance and highlighting issues with sampling bias and uncharacterized AMR genes.

The paper introduces LueVari, a reference-free SNP caller for metagenomic data that reliably detects SNPs in AMR genes across varying coverage levels.