Michael Biggel

This paper develops a method to link plasmid-encoded AMR genes to their bacterial hosts using nanopore sequencing methylation data, achieving high accuracy in clinical samples.

This paper evaluates standalone Oxford Nanopore sequencing for foodborne pathogen surveillance, showing it can achieve high accuracy with quality control tools like alpaqa.

This paper develops a metagenomic framework for detecting Listeria monocytogenes in food environments, showing that direct metagenomics captures more strain diversity than culture-based methods.

This paper develops shuttle vector-based transformation systems for Chlamydia pecorum and Chlamydia caviae, showing successful transformation and fluorescent protein expression, but not for C. abortus.

This paper introduces a computational framework using nanopore sequencing and deep learning to infer microbial viability from raw signal data, showing high accuracy in controlled and real-world applications.

This study evaluates Oxford Nanopore Technologies for Listeria monocytogenes outbreak detection, finding most assemblies suitable for high-resolution genotyping but with challenges from methylation motifs.