My research interests are in applying machine learning and comparative genomics methods to identify new antimicrobial resistance genes and trends from public sequencing data of microbial pathogens. My aim is to develop robust computational workflows capable of extracting insights on antimicrobial resistance from genome sequences for a wide range of organisms and drugs.
PhD student in Bioinformatics and Systems Biology, University of California, San Diego 2017, B.S. Chemical-Biological Engineering and Biology, Massachusetts Institute of Technology
Hyun, Jason, Erol S. Kavvas, Jonathan M. Monk, and Bernhard O. Palsson. "Machine learning with random subspace ensembles identifies antimicrobial resistance determinants from pan-genomes of three pathogens." PLOS Computational Biology. Accepted Dec 16 2019.
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