Wolfgang Müller

PoLiMeR is funded through the EU Marie Skłodowska-Curie Innovative Training Network (ITN), which drives scientific excellence and innovation. ITNs bring together universities, research institutes, industry and clinical partners from across the world to train researchers to doctorate level.

Metabolic diseases are a burden on the European population and health care system. It is increasingly recognised that individual differences with respect to history, lifestyle, and genetic make-up affect disease
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MESI-STRAT: Systems Medicine of Metabolic-Signaling Networks -A New Concept for Breast Cancer Patient Stratification.
Breast cancer is a complex disease with high prevalence in the European Union and world-wide. 75%-80 of the patients have estrogen receptor-positive (ER)-positive tumors and are treated with endocrine therapies. Endocrine therapies, which block ER-driven tumor growth, show high efficacy. Yet, a significant proportion of the patients will eventually relapse with metastatic breast
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Here we share resources and best practices to develop a disease map for COVID-19. The project is progressing as a broad community-driven effort. We aim to establish a knowledge repository on virus-host interaction mechanisms specific to the SARS-CoV-2. The COVID-19 Disease Map is an assembly of molecular interaction diagrams established based on literature evidence.

The project "INtegrative COllaborative modeling in systems MEdicine" aims at connecting different heterogenous datasets and individual models within systems medicine.

The GMDS project group bundles activities for health-related FAIR data infrastructures in the fields of biomedical research, clinical data management and medical informatics in Germany. It aims at providing a platform for information exchange about best practice for and implementation of FAIR data management in these fields and constructing a network of FAIR data managements providers in these fields. Through bridging between providers and potential users of such data management platforms within
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FAIRDOM will establish a support and service network for European Systems Biology. We will serve projects in standardising, managing and disseminating data and models in a FAIR manner: Findable, Accessible, Interoperable and Reusable.

The main objectives of SysMO-DB are to: facilitate the web-based exchange of data between research groups within- and inter- consortia, and to provide an integrated platform for the dissemination of the results of the SysMO projects to the scientific community. We aim to devise a progressive and scalable solution to the data management needs of the SysMO initiative, that:

* facilitates and maximises the potential for data exchange between SysMO research groups;
* maximises the ‘shelf life’ and
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The Systems Biology Service Center of de.NBI (de.NBI-SysBio) provides bioinformatics support and a standards-based data management for systems biology projects, with focus on the provenance of experimental results and on the reproducibility of modeling experiments, as well as high-quality curated biochemical data to modelers and experimentalists.
The node concentrates on two tools for the data management in life sciences research: SEEK, a catalogue for storage, registration and exchange of data
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Public showcase and collection of training material

The workshop focuses on the publication, curation, retrieval, and usage of kinetic data from the reaction kinetics database SABIO-RK and on the use of data in modeling. There will be experience reports from scientists who successfully used experimental data to formulate or verify biological hypotheses with the computer, and you will experience how experimental data can be used with computational models.

We will contribute to the LiSyM Research Network an open source, freely available and reproducible multiscale model of the human liver from single cell metabolism to whole liver function. The model will be available in existing standards of systems biology, provide standardized interfaces for data integration and be fully annotated to available biological, medical and computational ontologies. All data, models and source code will be shared within the LiSyM Research Network and made available to
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