Rafi Ahmad

K-MARVEL is a computational tool that accurately identifies antimicrobial resistance genes and mutations from short and long-read sequencing data, outperforming existing methods in speed and accuracy.

Mango enables interactive correlation analysis of tabular biological data to distinguish biases from causal relationships in genomic and transcriptomic datasets.

This paper develops and evaluates a method for rapid metagenomic sequencing of blood cultures to identify pathogens and antimicrobial resistance in bloodstream infections within 4 hours.

This paper evaluates URINN, a metagenomic workflow for rapid UTI diagnosis, showing high accuracy in pathogen detection and antibiotic resistance prediction.

The paper develops a low-cost in-house culture medium for faster and more accessible detection of bloodstream bacterial pathogens compared to commercial systems.

This study optimizes DNA extraction and sample preparation for long-read metagenomic sequencing of mastitis milk to improve pathogen and AMR detection.

This paper develops and optimizes a method using saponin and SAN nucleases to deplete host DNA from blood cultures, improving bacterial DNA extraction for sepsis diagnosis.

This study demonstrates rapid detection of pathogens and antimicrobial resistance genes in urine using Nanopore sequencing within five hours.

Voyager rapidly maps long-read sequencing reads to reference genomes for taxonomic classification, outperforming existing methods in speed and accuracy.