Adrian Viehweger

The paper introduces CLEAN, a pipeline to remove contaminants from sequencing data, improving reproducibility and analysis quality.

This study evaluates Oxford Nanopore sequencing for outbreak tracing, identifies methylation-induced errors, and proposes a masking workflow to improve accuracy.

This study evaluates Oxford Nanopore's adaptive sequencing for improving microbial sequencing yield in human vaginal samples by selectively depleting host DNA.

What the Phage provides a scalable, parallel workflow for phage sequence identification and analysis using multiple prediction tools and downstream annotation.

DarkQ enables instant sharing and discovery of newly sequenced genomes through a message queue system to improve timely access for stakeholders.

MUFFIN is a metagenomics workflow that integrates short and long reads to produce high-quality bins and annotations for microbial community analysis.

This paper introduces a deep learning method to predict viral hosts using only viral genome sequences, achieving high accuracy across three virus species.

The paper introduces a method to reduce large genome collections by grouping similar genomes using embeddings, improving metagenomic classification accuracy.

This study uses direct RNA nanopore sequencing to analyze full-length coronavirus genomes, identifying structural variants and methylation sites in viral RNAs.

The paper introduces nanotext, a novel representation of genome content for machine learning, and applies it to predict culture media and growth temperatures from metagenome assembled genomes.