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Using machine learning to predict the severity of salmonella infection
David Ussery, a Professor in the Department of BioMedical Informatics at UAMS, and his student, Aakash Bhattacharyya, discuss using Machine Learning methods to predict the pathogenicity of a bacterial infection based on genome sequencing.
Bioinformatics into TB surveillance: A new approach to an ancient foe
David Ussery, a Professor in the Department of BioMedical Informatics at UAMS, and his Ph.D. student Brian Delavan discuss bioinformatics into TB surveillance, presenting a new approach to tackling this ancient foe.
E. coli genomes, big data, and messy biology
Here, David Ussery from the Department of BioMedical Informatics, UAMS, details E. coli genome diversity, big data, and messy biology. New methods, we discover, allow for the comparison of millions of bacterial genomes in a few days and the confident assignment of taxonomic clusters.
