Software and Scientific Computing

The group Software and Scientific Computing is working on the development of algorithms and software tools for the fast retrieval and exploration of knowledge in structured and unstructured freely available sources. When browsing scientific literature, searching databases or browsing online media, one often asks oneself "Can this be true?" or "What is actually the current state of knowledge?". If you use portals to search the web, you have to search through long lists of results. We are doing research on distributed information systems that are supposed to answer such questions ad hoc. This goes far beyond keyword-based searches. Our data center integrates both structured databases (for example, on proteins, chemicals, active ingredients, clinical studies) and huge unstructured document collections (for example, research articles, patents, package inserts). The goal is to link different sources via the recognition and normalization of concepts and their relationships to highly complex knowledge graphs. To this end, we use modern methods of information extraction to automatically find designations of concepts (including synonyms and abbreviations) using terminologies and ontologies and to put them into relation (relation mining). The knowledge collected in this way is stored in comprehensive graph databases and can thus be used for searches by experts from various biomedical fields (for example, biomedicine, pharmacy, chemistry, biotechnology). We take advantage of modern, big data architectures, open source software solutions (such as Kubernetes, Apache Spark, Apache UIMA, Apache Spring, REACT) and interfaces (such as OpenAPI, OAuth), which we then adapt and extend to suit our needs.
 

We offer:

• Consulting and training in information extraction, modeling of knowledge graphs, setting up and operating micro service architectures that handle big data, digitalization and data processing
• Development and adaptation of graphical analysis tools and programming interfaces (API)
• Participation in national and international research projects
• Collaborations with industry and contract work
• Allocation and supervision of exciting research projects (practical projects, bachelor and master theses)
• Licensing and maintenance of our software products
   

We have:    

• An excellent infrastructure (computer center, data center, fast connections)
• Expert knowledge in chemistry, molecular biology, biomedicine, pharmacology, computer science and mathematics
• a comprehensive range of computer science skills

• Jens Dörpinghaus, Marc Jacobs (2019), Semantic Knowledge Graph Embeddings for biomedical Research: Data Integration using Linked Open Data. Semantics.
• Jens Dörpinghaus, Marc Jacobs, Martin Hofmann-Apitius (2019), Context graph for biomedical research data: A FAIR and open approach towards reproducible research in Medicin. Conference: MAQC2019.
• Jens Dörpinghaus, Jürgen Klein, Johannes Darms, et al. (2018), SCAIView – A Semantic Search Engine for Biomedical Research Utilizing a Microservice Architecture. Semantics 2018.
• Marc Jacobs, Sven Hodapp, Jens Dörpinghaus (2018), SDA: Towards a novel knowledge discovery model for information systems. IADIS Information Systems Conference (IS 2018).
• Juliane Fluck, Philipp Senger, Wolfgang Ziegler, Steffen Claus, Horst Schwichtenberg (2017), The cloud4health Project – Secondary Use of Clinical Data with Secure Cloud-Based Text Mining Services. Scientific Computing and Algorithms in Industrial Simulations.Alle Publikationen des Geschäftsfelds Bioinformatik