SBI – Department of Systems Biology and Bioinformatics
Faculty of Computer Science and Electrical Engineering
University of Rostock
Ulmenstrasse 69 | 18057 Rostock
Germany
+49 381 498-7571
olaf.wolkenhauer@uni-rostock.de
Projects
Research Projects
The research training group GRK 2901/1 SYLOBIO funded by the German Research Foundation (DFG), analyses the local as well as the systemic response to these biomaterials. The central research question is whether the systemic reaction to biomaterials is either triggered by biological factors from the biomaterial environment or whether systemic exposure to degradation products leads to inflammation in organs/tissues distant from the biomaterial.
Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease (NAFLD), has a complex pathogenesis that requires an in-depth understanding of diagnostic and prognostic molecular patterns to develop effective clinical treatment strategies. Here, we present the MASLD Map, a comprehensive, web-based to investigate and simulate molecular processes involved in MASLD progression.
In collaboration with the Division of Gastroenterology at the Rostock University Medical Center (as part of the EnErGie project) we are developing an in-depth, standardized, and computationally encoded disease map of the molecular interactions regulating muscle growth and function. We integrated the two disease states intestinal dysfunctions (ID) and liver cirrhosis (LC) into the map to investigate their contribution to the loss of muscle function (sarcopenia).
The AIR is to provide an interactive platform connecting scientific and medical communities.
Academic background
| 2024 - Present | Postdoctoral Fellow at the SBI |
| 2019 - 2024 | PhD Student at the SBI |
| 2017 - 2019 | Master's degree in Medical Biotechnology, University of Rostock |
| 2014 - 2017 | Bachelor's degree in Medical Biotechnology, University of Rostock |
Selected publications
Cell-Type-Specific Gene Regulatory Networks of Pro-Inflammatory and Pro-Resolving Lipid Mediator Biosynthesis in the Immune System
Network analyses reveal new insights into the effect of multicomponent Tr14 compared to single-component diclofenac in an acute inflammation model
DOI: https://doi.org/10.1186/s12950-023-00335-0
Pubmed: 36973809
In silico investigation of molecular networks linking gastrointestinal diseases, malnutrition, and sarcopenia
Frontiers in Nutrition (2022)
Network- and enrichment-based inference of phenotypes and targets from large-scale disease maps
The Atlas of Inflammation-Resolution (AIR)
Identification of key factors for malnutrition diagnosis in chronic gastrointestinal diseases using machine learning underscores the importance of GLIM criteria as well as additional parameters
Large-scale knowledge graph representations of disease processes
NaviCenta – The disease map for placental research
COVID-19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms
A systems appraoch to investigate inflammation resolution by multicomponent medicinal product TR14
(Re-)Programming of Subtype Specific Cardiomyocytes
Advanced Drug Delivery Reviews
Mechanistic Understanding of Inflammation Resolution Using the Atlas of Inflammation Resolution (AIR)
In: Tripathi, A., Dwivedi, A., Gupta, S., Poojan, S. (eds) Inflammation Resolution and Chronic Diseases. Springer, Singapore.
ISBN 13 (print): 978-981-97-0156-8
ISBN 13 (online): 978-981-97-0157-5
DOI: https://doi.org/10.1007/978-981-97-0157-5_13
URL: https://link.springer.com/chapter/10.1007/978-981-97-0157-5_13
Are Multi-Component Drugs Better in Resolving the Inflammation Compared to the Single-Component Drugs?
In: Tripathi, A., Dwivedi, A., Gupta, S., Poojan, S. (eds) Inflammation Resolution and Chronic Diseases. Springer, Singapore.
ISBN 13 (print): 978-981-97-0156-8
ISBN 13 (online): 978-981-97-0157-5
DOI: https://doi.org/10.1007/978-981-97-0157-5_10
URL: https://link.springer.com/chapter/10.1007/978-981-97-0157-5_10
Inflammation Resolution Mediators: Future Prospects
In: Tripathi, A., Dwivedi, A., Gupta, S., Poojan, S. (eds) Inflammation Resolution and Chronic Diseases. Springer, Singapore.
ISBN 13 (print): 9789819701568
ISBN 13 (online): 9789819701575
DOI: https://doi.org/10.1007/978-981-97-0157-5_9
URL: https://link.springer.com/book/10.1007/978-981-97-0157-5
Accessible Tools for Biomolecular Data Analysis using Large-Scale Knowledge Graphs
Biomolecular experiments generate data to improve our understanding of biological systems and their response to external stimuli. In the context of diseases, the goal is to use this information to modulate such systems in a desired fashion. However, data interpretation proves challenging due to the heterogeneity of data types across multiple levels of structural and functional organization. With a substantial number of potentially significant molecules, cell types, processes, and disease phenotypes, there is a need for tools to explore data from various sources and types. To this day, there is no single all-encompassing multi-level approach to analyzing such heterogeneous biomolecular data. In this PhD research project, I constructed knowledge graphs (KGs) to represent disease-related multi-level processes in a standardized format. I then developed tools to explore these knowledge graphs together with experimental data. The KGs are accessible through public, interactive, and community-driven platforms, referred to as “Disease Maps”. I demonstrate the approach with three Disease Maps. First, I introduce the Atlas of Inflammation Resolution (AIR) as a Disease Map of the molecular and cellular processes involved in acute inflammation and inflammation resolution. I present a novel enrichment-based analytical approach called 2DEA, which was integrated into the AIR. The approach facilitates in silico perturbation experiments and inferences from experimental data. I demonstrated the applicability of the AIR and the 2DEA through two studies in which I evaluated the mode of action of multi-target anti-inflammatory drugs and investigated cell type-specific gene regulation of lipid mediator synthesis. Secondly, I present the Sarcopenia Map that links molecular processes of food intake, gastrointestinal diseases, and sarcopenia through Boolean modeling. Finally, I describe the MASLD Map, which combines multicompartmental and Boolean approaches to study spatiotemporal mechanisms in steatotic liver diseases. The results of my work have been developed in several interdisciplinary collaborations with experimental, clinical, and industry partners. With the outcomes presented in this thesis, I provide accessible tools for biomolecular data analysis using large-scale knowledge graphs. They support the integrative analysis of diverse data types across multiple levels of functional and structural organization in biological systems.
Curation of an immune cell interactome and its analysis
2019
Master thesis within the study degree of Medical Biotechnology
The interconnectivity of immune cells has been the subject of research numerously due to its importance in different diseases such as autoimmune defects, (microbial) infections and cancer. Various cell types have already been identified that are regulated by a complex network of cytokines and small molecules, of which many may not have been discovered yet. Therefore, it is of great interest to understand these mechanisms as they form the basis for drug development and therapy design. In this project, methods were described to create and analyze a cell interactome of molecular intra- and intercellular communication processes. Many molecular interaction maps (MIMs) have already been developed to evaluate molecular processes in certain diseases or cells. However, they either lacked essential information necessary for accurate modeling of cell-cell interactions or were poorly clinically assessed. Here, systems biology-based rules were defined to model the molecular pathways of intercellular interactions of cells in detail. By mapping expression data of immune cell samples, individual cellular MIMs were created automatically and validated by comparing the results with the current knowledge in the field of immunology. In addition to analyzing intracellular signaling pathways, intercellular communication processes were investigated by connecting the MIMs. The outcomes of this work improve the system biology modeling of molecular interaction networks and further provide the basis for the efficient development of complex intercellular networks to investigate biological and molecular processes in silico.
Identification of activated signaling pathways in cardiac stem cell types by using network analysis
2017
Bachelor thesis within the study degree of Medical Biotechnology