VIROQUANT Research Group Modeling
Research Focus
Knowledge discovery in and analysis of high-throughput data generated in biological research requires novel mathematical and algorithmical methods, which reflect the complexities of life at the molecular level. In the post genomic era, biology and medicine face the challenge of analyzing quantitatively biological processes resulting from interactions of molecular and cellular ensembles in order to understand fundamental mechanisms and their development. Systems biology aims at understanding how biological systems function by studying the interactions and relationships between various parts of the system (e.g. metabolic pathways, cellular components, cells, etc).
We develop methods required for both model-based and data-driven understanding of cellular systems. Working at the interface of mathematics, computer science, statistics, machine learning and bioinformatics, we develop in close collaboration with our biological partners tools to analyze high-throughput biological data, as well as models to understand biological entities and their interactions.
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VIROQUANT
Our group is one of the central research groups within the FORSYS initiative center VIROQUANT: Systems Biology of Virus-Cell Interactions. Within VIROQUANT, we integrate the RNAi screening and imaging data acquired in VIROQUANT into a quantitative and comprehensive modeling framework, including also other data sources. We then develop spatio-temporal models of relevant signaling pathways, describing virus-cell interactions at a quantitative level. By combining quantitative modeling based on differential equations with statistical and machine learning methods, we integrate both mechanistic and statistic descriptions of the host cell-virus system. Using techniques from different methodological fields and in close collaboration with biology groups in VIROQUANT, ultimately, we aim at developing models which are able to describe how viruses hijack cellular mechanisms.