Marcus Nguyen

TL;DR: The recent updates to the PATRIC resource are reported, including new web-based comparative analysis tools, eight new services and the release of a command-line interface to access, query and analyze data.

TL;DR: A collection of 5,278 nontyphoidal Salmonella genomes was used to generate extreme gradient boosting (XGBoost)-based machine learning models for predicting MICs for 15 antibiotics, showing that highly accurate MIC prediction models can be generated with less than 500 genomes.

TL;DR: This study shows that machine learning can be used to build a complete in silico MIC prediction panel for K. pneumoniae and provides a framework for building MIC prediction models for other pathogenic bacteria.

TL;DR: This report provides the first molecular characterization of SARS-CoV-2 strains causing two distinct COVID-19 disease waves, and sequenced the genomes of 5,085 Sars- CoV- 2 strains from these two waves.

TL;DR: This study is the first analysis of the molecular architecture of SARS-CoV-2 in two infection waves in a major metropolitan region, and exploited the genomic data to generate defined single amino acid replacements in the receptor binding domain of spike protein that produced decreased recognition by the neutralizing monoclonal antibody CR30022.