Herwig lab / Bioinformatics Group
Research covers i) the development of computational methods for the analysis of molecular data often in collaborative research projects with the focus on human diseases and ii) the integration and interpretation of these data in the context of biological networks.
The group has developed computational methods for RNA-seq and MeDIP-seq and works on the integrative analysis of these data in order to elucidate the interplay of methylation, gene expression and genome structure that are operative in human (disease) processes related to cancer, diabetes and drug toxicity. For analyzing genome data at the network level, the group has developed and maintains the ConsensusPathDB molecular interaction resource which is a widely used research resource (~2,500 paper citations). Furthermore, the group has developed a novel network propagation framework and applied this to the identification of drug toxicity mechanisms from multi-omics data and the biological explanation of “black-box” machine learning predictions for the survival of cancer patients. Additionally, we work in the field of long-read sequencing analysis and the elucidation of alternative splicing. For this we have developed the software package IsoTools for long-read RNA from PacBio and Nanopore sequencing and analyzed the effect of aberrant splicing regulation in cancer.