Translational Research Informatics
Department of Medical Informatics
Our work group explores the researcher’s needs for infrastructure in translational research. We focus on procedures of data integration, data stewardship, data visualization and legal aspects of medical research. This is strengthened by collaborations with various national and international research groups that collect a wide range of data types. Applying international standards and tools, requirements-driven solutions are being sketched, discussed, iteratively implemented, and evaluated. Methodological core area is the coverage, analysis and annotation of data sources and workflows as well as their assessment, curation and integration. Furthermore, we focus on tools for coverage and visualization of data (“Bring the analysis to the data.”) In this, current tools are applied and customized that allow the simple embedding and use of R-Scripts on proprietary data sets – next to more advanced visualization capabilities. The systematic analysis of data sources, their incremental improvement and tools to discuss the data with the different stakeholders are essential steps towards a sustainable data stewardship along the FAIR guiding principles of data management.
Identifying requirements for improving biomedical research, setting up, customizing and testing adequate infrastructure components.
Preparing the GCP-validation and go-live through sustainable service partners like the UMG MeDIC.
Our group is led by Prof. Dr. Ulrich Sax, an experienced medical informaticist with a strong international background in Biomedical Informatics, Computer Science and long term experience in operating medical computing centers. The group comprises several computer scientists with a solid background in biomedical informatics and project experience. The team is continuously supported by student assistants. Additionally, internships and bachelor’s and master’s theses are being motivated, designed and supported by this work group. Furthermore, the team members are involved in several interdisciplinary research projects and work groups of the GMDS and TMF.
List of Projects
MTB-Report (2020 bis 2022)
MTB-Report: An automated data integration platform for interpreting genomic data and reporting treatment options in molecular tumor boards.
Aims: In the MTB-Report project we aim to develop a tool to support the decision finding in a molecular tumor board (MTB). Biomarkers and other omics data from the patient will be compared to a multitude of available data bases in order to find case studies with a parameter set equivalent to the patient’s one. Based on tumor type and certainty of the study an evidence level is assigned and used to propose the most relevant to the MTB in form a short report. For access to the clinical data and to ensure data privacy the tool will be embedded in the IT-infrastructure. Clinical experts will define use cases for an optimal usage of the reporting tool and will validate the results.
MTB-Report Project Homepage at Inst. of Bioinformatics
NMDR (2016 bis 2021)
NMDR: Further Development and Establishment of a National Metadata Repository in Medical Research
Aims: Das strategische Ziel dieses Projekts ist die Etablierung eines kollaborativen, qualitätsgesicherten, neutralen, dauerhaften, freien und zugreifbaren Metadaten-Registers für die klinische und epidemiologische Forschung in Deutschland. Diese Kategorien sind das wesentliche Ergebnis der Anforderungsanalyse durch Befragung von 30 verschiedenen Anwendern im Rahmen des TMF-Projekts „Community-Evaluation MDR“. Von dem geplanten Vorhaben profitieren alle klinischen Forscher, die wissenschaftsinitiierte Studien, Register oder Kohorten planen und Daten hoher Qualität erheben wollen. Zugleich werden diese Punkte bislang von keinem existierenden System adressiert. Im Laufe des Projekts werden die folgenden wesentlichen Ergebnisse erzielt: Konzept und Methode zur Abstimmung von Kerndatensätzen, Pool von Fachexperten zur Kuration von Datenelementen, Konzept zur Verwaltung und Lizensierung von Datenelementen, Verbessertes Softwarewerkzeug, Konzept einer Schnittstelle (API) für den Zugriff auf CDMS.
MyPathSem (2016 bis 2020)
MyPathSem: A knowledge base for generating patient-specific pathways for individualized treatment decisions in clinical applications
Aims: A data integration platform for generating patient-specific signaling pathways for personalized treatment decisions in clinical applications (PI WP 2, Infrastructure clinical applications). Förderer: BMBF, i:DSem.
SFB1002 Research Data Platform (2016 to 2020)
Sonderforschungsbereich 1002: Modulatorische Einheiten in Herzinsuffizienz (SFB 1002); Enhancing the CRC 1002 research data platform for integrated and sustainable research data management (TP INF, 2. Förderperiode).
SFB1190 Research Data Platform (2016 to 2019)
Sonderforschungsbereich 1190: Transportmaschinerien und Kontaktstellen zellulärer Kompartimente
Aims: The compartmentalization of cells ensures a highly specific distribution of nucleic acids, proteins and metabolites. At the same time, intracellular compartments must communicate and exchange molecules. Two major systems enable exchange between compartments: compartmental gates and contact sites. While compartmental gates mediate the selective partitioning of molecules between cytoplasm and organelles or within a membrane, contact sites represent direct physical connections between compartment-enclosing membranes. Thus, within living cells, compartmental gates and contact sites represent two complementary systems, which functionally cooperate or directly interact with each other to coordinate compartmentalized processes. This SFB-initiative is committed to addressing the role of compartmental gates and contact sites in cellular organization and physiology. We aim to understand how they achieve a selective distribution of molecules and thus functionally define and diversify cellular compartments.
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