Lara Urban

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 study verifies nanopore sequencing for CRE surveillance by comparing it to routine diagnostics and determining required sequencing depths for various clinical tasks.

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

The paper presents a framework for real-time genomic characterization of pathogens, resistance, and host range in wetlands using passive sampling and nanopore sequencing, finding higher pathogen and AMR gene abundance in anthropogenically impacted sites.

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 study uses airborne eDNA to monitor terrestrial vertebrates in the Luangwa Valley, detecting 120 taxa with high sensitivity and showing that extended sampling improves detection of less common species.

This study uses long-read nanopore sequencing to analyze carbapenem resistance dynamics in a hospital setting, revealing plasmid spread and environmental reservoirs.

This paper quantifies genomic erosion and its impact on species recovery, proposing a Genomic Green Status framework to integrate genomic metrics into conservation planning.

The paper evaluates nanopore sequencing for eDNA metabarcoding in Zambia, showing it can match or exceed Illumina sequencing for biodiversity assessments in remote areas.

The paper evaluates nanopore sequencing for rapid AIV profiling, showing its ability to accurately reconstruct viral genomes and detect RNA modifications.

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 paper demonstrates that nanopore sequencing can effectively monitor air microbiomes by analyzing microbial diversity in controlled and natural environments.

The paper uses genomic and phenotypic data to study the evolution of kakapo color polymorphism, finding genetic variants and evidence of balancing selection.

This paper uses whole-genome sequencing of kakapo to analyze genetic diversity and breeding values, showing how conservation management has maintained genetic diversity and providing tools for future recovery efforts.

The paper compares eDNA sources from water, bivalves, sponges, and ethanol to assess their utility for biodiversity monitoring, finding sponges are reliable while bivalves are not.

This study uses non-invasive genomic methods to monitor kakapo populations, enabling individual identification through environmental DNA sequencing and providing insights into genomic diversity and inbreeding.

The paper identifies hundreds of genes deregulated by SVs in cancer, showing increased expression linked to SV breakpoints and enhancer elements.

The paper uses single-cell profiling of expression and DNA methylation to study splicing regulation and heterogeneity in human induced pluripotent stem cells.

Kipoi provides a framework for standardized, reusable machine learning models in genomics, enabling tasks like variant effect prediction and model benchmarking.

The paper analyzes RNA alterations across 27 cancer types using whole-genome sequencing data, identifying gene expression associations with DNA variants and structural fusions.

This study analyzes whole genome and RNA-Seq data from 1,188 cancer patients to map the effects of somatic and germline genetic variation on gene expression in cancer.