In our group we are aiming at a quantitative understanding of biological systems to an extent that one is able to predict systemic features and with the hope to rational design and modify their behaviour. This applies to any system comprising biological components that is more than the mere sum of its components, or, in other words, the addition of the individual components results in systemic properties that could not be predicted by considering the components individually. By achieving this objective we are aiming at new global understanding and treatment of human diseases in which the target will not be a single molecule but a network. For this purpose in our group we develop on one hand new software and theoretical approximations to understand complex systems and on the other we do experiments to validate our predictions.
Unraveling the hidden universe of small proteins in bacterial genomes
Abstract: Identification of small open reading frames (smORFs) encoding small proteins (≤ 100 amino acids; SEPs) is a challenge in the fields of genome annotation...Read More
Tissue-specific DNA methylation loss during ageing and carcinogenesis is linked to chromosome structure, replication timing and cell division rates
Abstract: DNA methylation is an epigenetic mechanism known to affect gene expression and aberrant DNA methylation patterns have been described in cancer. However, only a...Read More
PADA1 predicts the DNA-binding regions of resolved protein structures
Abstract: The speed at which new genomes are being sequenced highlights the need for genome-wide methods capable of predicting protein–DNA interactions. Here, we present PADA1,...Read More