Our research focuses on novel genomic methods for reconstructing and tracking antimicrobial resistance genes with sequence data. We couple this with expertise in building and applying bioinformatics tools that facilitate data analysis of massive sequence data sets of pathogens and microbiomes.
Our team uses DNA sequences and develops novel computational tools to analyze microbial
populations and communities. We track transmission of bacterial pathogens, and genes that provide resistance to antimicrobials. By employing machine learning, graph theory, and artificial intelligence, we develop bioinformatic tools to reconstruct mobile genetic elements that can spread within and between bacteria. These tools can be applied to infection prevention and public health to understand the spread of resistance.
Using 16S sequencing, we gain a broad understanding of the human microbiome in healthy and diseased patients. For deeper understanding, we employ metagenomic sequencing to annotate genes and metabolic pathways and to assemble partial to full genomes or mobile genetic elements of microorganisms. Analysis of the human microbiome may inform personalized treatments and prevention approaches in the future.