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Title:
Data Management and Analysis in Interdisciplinary Research Groups using Disease Maps

Authors:
Matti van Welzen, Shailendra Gupta, and Olaf Wolkenhauer

Abstract:
In the research consortium SYLOBIO, funded by the German Research Foundation, 10 research groups from the University of Rostock and University Hospital of Rostock and Greifswald are investigating the local and systemic (immune) reactions in response to biomaterials used for joint prostheses and skin injuries. The interdisciplinary project combines in vitro and in vivo experiments with epidemiological analysis of clinical studies and systems biology approaches to link the results on a systemic level.

Here, we present a workflow for data management in such interdisciplinary research groups using the disease map approach. In SYLOBIO, we are utilizing our Atlas of Inflammation Resolution (AIR) which describes the of molecular and cellular processes in inflammation (https://air.bio.informatik.uni-rostock.de/) [1]. Recently, we developed tools for the AIR that enable data integration and analysis through network-based approaches [2] and showed how these tools can help understanding the mode of action of multi-target drugs [3].

For SYLOBIO, the AIR will be extended with tissues, cells, and molecular processes studied in the individual research groups to visualize the experimental data in molecular networks. The data management in SYLOBIO will be organized using FAIRDOMhub, allowing researchers to share SOPs and data between the institutions. Standardized workflows for data processing will further ensure the reproducibility and comparability of results.

To improve the accessibility of the many tools and platforms for researchers in SYLOBIO, access to the data from FAIRDOMhub will be integrated directly into MINERVA. This way, researchers can access, explore, and analyze their and other research groups’ data on any disease map utilizing their functions to provide visual guidance and link their data with prior knowledge. Predictions from in silico simulations of the network-integrated data will then provide new insights into the molecular mechanisms and systematic effects of biomaterial interactions.

1. Serhan, C. N. et al. Mol Aspects Med 2020, 74, 100894.
2. Hoch, M. et al. NPJ Systems Biology and Applications 2022, 8:1 8, 1–11.
3. Hoch, M. et al. Journal of Inflammation 2023, 20, 1–15.