Markus Glaß

The paper analyzes codon usage patterns in pancreatic cancer to show how oncogenic gene expression is systematically optimized through GC content, preferred codons, and cost-effective amino acids.

The paper compiles a gene set collection of RBP target genes derived from eCLIP-seq data to enable functional enrichment analysis of gene lists.

CENTRA uses gene co-occurrence networks from literature to identify functional master regulators by analyzing centrality and fractality in topic-specific contexts.

This study shows RNA-seq-derived sequence variations can reliably identify cell lines and detect cross-contamination using machine learning.

This paper investigates RAVER1's role in controlling alternative splicing and its impact on miR/RISC activity and EMT in cancer cells.