What do we do?
At the Computational Biology Group we develop concepts and algorithmic tools for the analysis of large-scale biological and clinical data. We focus on the integration of genotypic and phenotypic datasets from mammalian cells or clinical studies. A key approach is the reduction of complexity through modular and network analysis. A complementary direction of our research pertains to relatively small genetic networks whose components are well known.
During the course of 2015, we made substantial progress in the fast and accurate computation of gene and pathway scores [PLOS Genet. 2016; 12(1):e1005616 ]. A direct application of our analysis tool – called PASCAL – resulted from the analysis of data from the FANTOM5 project and revealed that genetic variants associated with different diseases can be used to identify the relevant tissues enriched for genetic networks that are perturbed by the variants [Nature Methods, in press].
Main publications 2015
- Lamparter D et al. Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics. PLOS Comput Biol 2016;12(1):e1004714.
- Marbach D et al. Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases. Nat Methods: in press.
- Vonesch SC et al. Genome-Wide Analysis Reveals Novel Regulators of Growth in Drosophila melanogaster. PLOS Genet 2016;12(1):e1005616.