COMPUTATIONAL BIOLOGY • BIOINFORMATICS • SCIENTIFIC COMPUTING

Hi, I’m Kim Casa.

I build reproducible computational pipelines to analyze microbial genomic data and uncover insights in pathogen evolution, antimicrobial resistance, and public health.

Featured Projects

A selection of my recent work in pathogen genomics and computational biology.

AMR Profile Across Salmonella Serovars

Heatmap visualization of antimicrobial resistance gene prevalence across Salmonella enterica isolates.

AMR heatmap View Project →

AMR Trends Over Time

Temporal analysis of antimicrobial resistance prevalence across major Salmonella serovars.

AMR trends View Project →

Serovar Trends Over Time

Population-level genomic analysis of dominant Salmonella serovars across time.

Serovar trends View Project →

About Me

I am a bioinformatics researcher interested in using genomic data to better understand infectious disease, antimicrobial resistance, and pathogen evolution.

My work focuses on building reproducible computational workflows for bacterial genomics, including genome assembly, quality control, annotation, antimicrobial resistance detection, serotyping, and population-level analysis.

My recent research has focused on Salmonella enterica in food production and public health contexts, where I developed a Snakemake-based workflow to analyze large-scale genomic datasets and identify patterns related to antimicrobial resistance and strain diversity.

I am especially interested in computational biology, infectious disease genomics, epidemiology, and scientific computing.