Nicole E. Wheeler

The paper introduces a screening method for protein design tools that evaluates functional and structural features to identify potentially harmful targets, showing high accuracy and distinguishing between benign and damaging mutations.

This study evaluates the effectiveness of biosecurity screening tools against AI-generated synthetic homologs of proteins of concern, finding some tools can detect fragments as short as 50 nucleotides.

The paper develops a rubric to define sequences of concern by analyzing test sequences and refining categorization through stakeholder review, reducing disputed categorization by 44.3% for controlled viruses.

This study introduces ASCT to assess bacterial killing in real-time and links drug tolerance to clinical outcomes in mycobacterial infections.

The paper evaluates sequence screening tools using a NIST dataset to assess their consistency in identifying sequences of concern.

This study shows that biased sampling in bacterial genome data leads to poor performance in machine learning models predicting antimicrobial resistance.

The paper evaluates biosecurity screening tools for detecting AI-generated synthetic protein homologs and reports improved detection rates through patches.

The paper introduces Pathogenwatch, a web tool for genomic surveillance of Klebsiella, showing it identifies drug-resistant clones and vaccine candidate O-types in genomes from low- and middle-income countries.

This study uses whole genome sequencing to analyze antimicrobial-resistant Klebsiella isolates from Nigeria, identifying known and novel lineages, including multidrug-resistant ESBL producers.

This study analyzes CRKP isolates in Colombia using WGS, identifying high-risk clones and carbapenemase genes, emphasizing the need for WGS-based surveillance.

Whole genome sequencing identified three previously unrecognized Klebsiella pneumoniae outbreaks in neonatal intensive care units in the Philippines, revealing an epidemic plasmid associated with carbapenem resistance.

This study characterizes the genomic diversity of carbapenem-resistant Klebsiella pneumoniae isolates from India, identifying high-risk clones and resistance mechanisms.

This study constructs a phylogenetic tree of 131 S. Typhimurium strains to reveal population structure and adaptation to domesticated and wild animal hosts.

The paper evaluates GWAS methods for detecting antibiotic resistance in Staphylococcus aureus genomes, finding they identify novel resistance mutations but are less accurate than literature-based approaches.

The paper uses genome-wide association studies to show human and pneumococcal genetic variation influences susceptibility and severity of pneumococcal meningitis.

The paper uses machine learning to identify genetic signatures of host adaptation in Salmonella enterica strains associated with extraintestinal disease.