Hyunjin Shim

The paper tracks microbiome changes in urban compost piles over 6 weeks, showing microbial succession and reduced foodborne pathogens during thermophilic phases.

This paper develops genetic-information-free protein-only phages (POPs) that inhibit bacteria without replicating, showing comparable antimicrobial effects to wild-type phages.

This study evaluates nanopore sequencing's ability to classify and assemble hypervariable genomes from metagenomic samples, showing high accuracy in identifying Trypanosoma brucei in infected mouse blood.

The paper analyzes the underrepresentation of ESKAPE bacteriophages in public databases and shows its impact on machine learning models.

CRISPR-Cas-Docker predicts optimal crRNA-Cas pairs using in silico docking and machine learning classification.

This study optimizes RNA-protein interactions for CRISPR-Cas13-based antimicrobials by improving in silico docking of crRNAs with Cas13 proteins.

This paper uses accurate structure prediction to analyze anti-CRISPR proteins and identifies new strategies for protein drug design.