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Resume (English only)
Academic Achievements
Develops open-source computational tools shared freely with the scientific community; supports scientific crowdsourcing, particularly through DREAM challenges.
Research Experience
Application-driven research aimed at creating computational models that integrate diverse data sources for better understanding and treatment of diseases; closely collaborates with experimental groups; develops context-specific mechanistic and predictive models; extracts mechanistic features from multi-omics data, including single-cell data; constructs causal networks; builds dynamic models of specific subsystems using logical formalisms.
Background
Focused on understanding the deregulation of signaling networks in disease and applying this knowledge to develop novel therapeutics, with a particular interest in cancer, auto-immune, and fibrotic diseases.
Miscellany
Located at the European Bioinformatics Institute (EMBL-EBI) and the Institute for Computational Biomedicine at the Medical Faculty of Heidelberg University and Heidelberg University Hospital; also part of ELLIS Heidelberg.