Bioinformatics-Modeling Core

Prof. Dr. Dr. Melanie Börries

• Z01

Prof. Dr. Harald Binder

• Z01

Prof. Dr. Julijana Gjorgjieva

• Z01

Project Summary

The era of unprecedented advances in sequencing approaches has led to the development of sophisticated analytical methods and computational tools. High-throughput single-cell profi ling has allowed to gain detailed insights on the diversity and plasticity of myeloid cells in the CNS during development, health and disease. Despite these advances, the exponential growth in both the complexity and volume of omics data, spanning genomics, transcriptomics, proteomics, metabolomics, and more, presents a significant challenge. To address these challenges eff ectively, the Z01 project has been structured to combine data analysis, data modeling, and data management.

The Börries lab provides comprehensive support to the projects within the CRC/TRR 167, covering aspects such as experimental design, computational analysis, and distillation of scientific insights from omics data. In this context, M. Börries is not only an expert for in data analysis, but also in data integration and interpretation with regard to Systems Biology and Systems Medicine.

Specializing in building mechanistic models of neural circuit function, the Gjorgjieva’s group will support projects in the TRR 167 by integrating features extracted from comprehensive data analysis as biological constraints in mechanistic models. The models will aim to reveal temporally rich dynamic behaviours of networks of multiple interacting components such as interacting microglia. Both groups will jointly convene regular user meetings to address the analytical needs of the CRC project leaders and offer assistance in interpreting and further analyzing the results.

Data analysis and modeling will be tightly integrated with a system for research data management (RDM) based on the fredato system, which has been developed by the Binder group and will be customized according to the needs of CRC/TRR167. In particular, this system will facilitate collaborative research across all four partner sites, and provide for a comprehensive implementation of the FAIR principles, i.e., for making all data findable, accessible, interoperable, and thus re-usable.