Johannes Kersting

This paper introduces a Nextflow pipeline to evaluate disease module detection methods, showing variability in results due to method, network, and seed differences.

The paper combines network inference and motif enrichment to identify transcription factors controlling stress responses in barley under drought and Fusarium head blight.

DysRegNet infers patient-specific gene-regulatory networks from bulk RNA-seq data, accounting for confounders and scaling to large sample sizes, showing age-specific bias in breast cancer.

This study shows Trichoderma spp. can distinguish between beneficial ectomycorrhizal fungi and pathogenic fungi, showing accelerated growth toward pathogens and reduced growth toward mycorrhizal fungi.

DICAST benchmarks alternative splicing analysis tools, showing STAR and HISAT2 perform best, and proposes a reporting standard for event detection.